183_Sabel_2011

PROGRESS IN BRAIN RESEARCH

VOLUME 192

ENHANCING PERFORMANCE FORACTIONANDPERCEPTION:MULTISENSORYINTEGRATION, NEUROPLASTICITY AND

NEUROPROSTHETICS, PART II

EDITED BY

ANDREA M. GREEN

Département de Physiologie, Université de MontréalMontréal, Québec, Canada

C. ELAINE CHAPMAN

École de Réadaptation, Département de PhysiologieUniversité de Montréal, Montréal, Québec, Canada

JOHN F. KALASKA

Département de Physiologie, Université de MontréalMontréal, Québec, Canada

FRANCO LEPOREDépartement de Psychologie, Université de Montréal

Montréal, Québec, Canada

AMSTERDAM – BOSTON – HEIDELBERG – LONDON – NEW YORK – OXFORDPARIS – SAN DIEGO – SAN FRANCISCO – SINGAPORE – SYDNEY – TOKYO

CHAPTER 13

Vision restoration after brain and retina damage:The “residual vision activation theory”

Bernhard A. Sabel*, Petra Henrich-Noack, Anton Fedorov and Carolin Gall

Institute of Medical Psychology, Medical Faculty, Otto-von-Guericke-University Magdeburg, Magdeburg, Germany

Abstract: Vision loss after retinal or cerebral visual injury (CVI) was long considered to be irreversible.However, there is considerable potential for vision restoration and recovery even in adulthood. Here, wepropose the “residual vision activation theory” of how visual functions can be reactivated and restored.CVI is usually not complete, but some structures are typically spared by the damage. They include(i) areas of partial damage at the visual field border, (ii) “islands” of surviving tissue inside the blindfield, (iii) extrastriate pathways unaffected by the damage, and (iv) downstream, higher-level neuronalnetworks. However, residual structures have a triple handicap to be fully functional: (i) fewer neurons,(ii) lack of sufficient attentional resources because of the dominant intact hemisphere caused byexcitation/inhibition dysbalance, and (iii) disturbance in their temporal processing. Because of thisresulting activation loss, residual structures are unable to contribute much to everyday vision, and their“non-use” further impairs synaptic strength. However, residual structures can be reactivated byengaging them in repetitive stimulation by different means: (i) visual experience, (ii) visual training, or(iii) noninvasive electrical brain current stimulation. These methods lead to strengthening of synaptictransmission and synchronization of partially damaged structures (within-systems plasticity) anddownstream neuronal networks (network plasticity). Just as in normal perceptual learning, synapticplasticity can improve vision and lead to vision restoration. This can be induced at any time after thelesion, at all ages and in all types of visual field impairments after retinal or brain damage (stroke,neurotrauma, glaucoma, amblyopia, age-related macular degeneration). If and to what extent visionrestoration can be achieved is a function of the amount of residual tissue and its activation state.However, sustained improvements require repetitive stimulation which, depending on the method, maytake days (noninvasive brain stimulation) or months (behavioral training). By becoming again engagedin everyday vision, (re)activation of areas of residual vision outlasts the stimulation period, thuscontributing to lasting vision restoration and improvements in quality of life.

*Corresponding author.Tel.: þ49-391-672-1800; Fax: þ49-391-672-1803E-mail: [email protected]

A. M. Green, C. E. Chapman, J. F. Kalaska and F. Lepore (Eds.)Progress in Brain Research, Vol. 192ISSN: 0079-6123Copyright � 2011 Elsevier B.V. All rights reserved.

199DOI: 10.1016/B978-0-444-53355-5.00013-0

Keywords: vision; restoration; rehabilitation; plasticity; current stimulation; training.

Introduction

Humans rely on vision more than on any of theother senses, and more brain tissue is devoted tovisual perception than to all other senses combined(Felleman and Van Essen, 1991). Thus, when thebrain is damaged, the likelihood to suffer visualimpairments is high and the consequences forquality of life are grave. Nineteen percent of per-sons >70 years have visual impairments (Centersfor Disease Control and Prevention, 2004), andvisual loss is the most feared disease in the elderly(Aiello, 2008).

There are many possible reasons forimpairments or loss of vision after damage to thecentral nervous system. Functional deficits dependprimarily on the location of the damage which maybe in the retina, optic nerve, or higher-level visualstructures of the brain. When the visual radiationor visual cortex is damaged, homonymous sectorsof the visual field are lost, leading to scotomata orloss of the entire half of the visual field, a conditionlong known as hemianopia (Baumgarten, 1878;Poppelreuter, 1917). The etiology of visual fielddefects may be traumatic, inflammatory, or vascu-lar, and the vision loss can proceed either acutely(as in stroke or brain trauma) or it can progressmore slowly as in inflammatory degeneration ofthe optic nerve or retinal damage (e.g., glaucomaor age-related macular degeneration (AMD)).

Because of its retinotopic organization andhighly specific cortical organization, the visualsystem is generally believed not to recover verywell after injury. The generally accepted notionis that patients are permanently left with irrepara-ble blindness. However, there is some hopebecause vision loss is usually not complete butpartial, having variable degrees of residual visualfunctions. A better understanding of how to stim-ulate the partially damaged visual system toimprove its function is therefore not only scientif-ically interesting but also clinically relevant.Despite the lingering pessimism that vision loss

is permanent, searching new ways to help patientsregain at least some of their lost vision is a scien-tific and clinical responsibility.

It was long suspected that the brain had nocapability of repair after an early spontaneousrecovery phase which typically ends after the firstfew weeks of injury. But in recent years, we havewitnessed scientific progress showing manyexamples where vision improvements were seeneven well beyond this early recovery phase.

Vision recovery as discussed in our review, alsotermed vision restoration, is limited to visualdysfunctions caused by damage of the central ner-vous system, that is, retina, optic nerve, and differ-ent brain regions. We do not discuss restoration ofanterior eye problems (cornea or lense). Visionrestoration also does not assume a “completereturn” to normal function and it may manifestitself mainly in partial and sometime also in totalrecovery, depending on the individual case. Theterm “vision restoration” should not bemisunderstood as implying “complete” restorationof function at all times because the extent of resto-ration is always rather variable and usually notcomplete. The term “restoration” should also notbe misused to raise unfounded hope in patientswith visual loss. It rather emphasizes the residualpotential of the damage system to improve its func-tion, in whatever extent, form or shape.

Several issues cannot be discussed in detail inthis review such as the role of plasticity in normallearning. Particularly, the study of normal “percep-tual learning”was elegantly studied by other labor-atories (see below) and their work should beconsulted. The present review also does not focuson how patients who suffer from visual field defectsmay be able to “compensate” for their visual fieldloss by scanning the visual world more vigorouslywith eye movements, thus attempting to increasetheir “field of view.” It is possible that this compen-sation actually reduces the chance for restorationas the subjects learn to focus their attention moreon the remaining, intact capacities.

200

The aim of the present review is to first summa-rize the current literature on vision restorationand on this basis formulate a new theory of theunderlying mechanisms. Although visual systemplasticity has been discussed at numerousoccasions, we still lack a coherent theory of visionrestoration after damage to the adult brain and thisshould be rectified. The residual vision activationtheory was therefore conceived to provide a heu-ristic framework to sort and interpret the differentobservations and approaches, helping to guide usin a new and exciting research direction that pro-vides hope for the many partially blind patients.“Neuroengineering”-like approaches that aim

at restoring vision can be only mentioned herein passing: besides efforts to limit the lesioneffects through neuroprotection, there are variousattempts to replace the damaged tissue itself or toprovide some alternative tissue that augments thedamaged tissue or supports its biological regener-ation. These include (i) artificial retinal or brainimplants, (ii) retinal and cortical tissuetransplants, (iii) nerve regeneration, and (iv) stemcell implantation. Because these approaches aremostly experimental at this time, they are notdiscussed in further detail here.Whereas the neuroengineering approach aims

at replacing or augmenting the lost tissue itself—as if trying to fill the hole of a donut—the“neuroplasticity approach” of residual vision aimsat altering the surviving brain tissue itself. It is byfar the clinically more relevant topic and hasreceived a lot of attention from different groups.Neuroplasticity studies focus on the residual (surviv-ing) brain structures both at the site of the lesion(local) and in the brain network as a whole (global).While visual system plasticity is a well-describedphenomenon in the developing, normal brain at anage well before the critical period, it is now consen-sus that the visual system plasticity is possible inolder age; it is observed in perceptual learning inadults and elderly but also after different types ofbrain lesions, both in animals and in man.The present review summarizes the evidence of

post-lesion plasticity of the partially damaged adult

visual system and its clinical impact and thenformulates the residual vision activation theory.This theory was conceived to create a unified viewof current empirical evidence of visual system repairand to explain mechanisms of vision restorationafter lesions of the central visual pathway, includingretina, optic nerve, postchiasmatic tracts, andradiations, striate (V1) but also extrastriate cortex.

Plasticity of the visual system

Plasticity has been observed at many differentlevels of the visual system both in the normaland in the lesioned brain. In fact, plasticity is arather normal, dynamic property that takes placein normal perceptual learning.

Perceptual learning

Perceptual learning is a change in performancefollowing training or practice which is typicallyinvestigated in visually healthy subjects (Fahleand Poggio, 2002; Li et al., 2004). Perceptuallearning may improve different visual abilitiessuch as detection of thresholds, gratings, hyper-acuity, motion, or texture (Fahle, 2002, 2005;Fiorentini and Berardi, 1980; Gilbert et al., 2001;Polat and Sagi, 1994). The improvements are usu-ally specific and they do not transfer easilybetween different stimuli or stimulus locations inthe visual field. This specificity is attributed toresponse modifications of neuron assemblies atthe earliest visual processing stages such as V1(Fahle, 2005; Fahle and Skrandies, 1994; Hirschand Gilbert, 1991). Perceptual learning mayinvolve training attention to discriminate distinc-tive stimulus features (Gibson, 1969), increasealertness (Wolford et al., 1988), and establishstimulus–response associations (correlatedactivities) in sensory system of the brain.

Practice is also able to increase the range of thelateral interactions sixfold in collinearity tasks(Polat et al., 2004; Polat and Sagi, 1994) which

201

appears to increase the efficacy of the collinearinteractions between neighboring neurons. This,in turn, may improve the connectivity of remoteneurons via local interactions which are alsothought to be involved in receptive field (RF)plasticity after retinal lesions (for discussion seebelow).

Plasticity after retinal lesions

Plasticity after acute retinal damage

When the retina is damaged, visual impairmentscan recover spontaneously and there is consider-able RF reorganization in upstream areas(Dreher et al., 2001; Eysel, 1997; Eysel andGrüsser, 1978; Eysel et al., 1999; Gilbert andWiesel, 1992; Kaas et al., 1990). RF reorganiza-tion is a well-studied field showing how the brainreacts to injury by numerous neurophysiologicalchanges on the molecular, cellular, and networklevel (see also Huxlin, 2008). Retinal lesions areoften used in experimental animal models tostudy recovery and RF plasticity.

Rather limited RF plasticity occurs in the lateralgeniculate nucleus (LGN) of the thalamus afterretina damage (Eysel and Grüsser, 1978), whereasin the visual cortex, up to 98% of the deafferentedneurons developed new RFs within 3 months afterretinal lesion in cats (Chino et al., 1995). Corticalreorganization is typically reflected in a displace-ment of the RF position and RF enlargement.The shift of RFs following retinal lesions has beenreported both in cat's area 17 and 18 (Kaas et al.,1990; Young et al., 2002). The properties of theseRFs are normal, except for elevation of contrastthreshold (Chino et al., 1995) and changes in tem-poral characteristics of response (Darian-Smithand Gilbert, 1995; Heinen and Skavenski, 1991;Waleszczyk et al., 2003). Lesions of both retinaland cortical areas are typically accompanied byreducedGABAergic inhibition and increased glut-amatergic excitation, leading to an increased spon-taneous activity and excitability change of visual

activity in the region of cortical scotoma (corticalrepresentation of retinal lesion; Giannikopoulosand Eysel, 2006) or in regions surrounding the cor-tical lesion (penumbra) (Dohle et al., 2009; Eyselet al., 1999; Imbrosci et al., 2010).

Recovery of visual responses in the silencedarea of the visual cortex is suggested to be medi-ated by anatomical (Darian-Smith and Gilbert,1994) and functional changes of intrinsic corticalhorizontal connection (Calford et al., 2003; Dasand Gilbert, 1995; Palagina et al., 2009; Younget al., 2007). Keck et al. (2008) recently observedin adult mice with small retinal lesions a completereorganization of dendritic spines in thedeafferented cortex within 2 months. The rate atwhich postsynaptic connections perished andwere reestablished was three times higher thanin normal brain. Smirnakis et al., (2005) havequestioned the existence of cortical reorganiza-tion as they could not see topographic changesin the BOLD response of adult macaques 7.5months after retinal lesion, but the BOLDresponse was considered to be insensitive tochanges in RFs by most investigators in the field(Calford et al., 2005). The body of literature onRF reorganization in the visual system is too largeto be reviewed here and numerous publicationsby the groups of Eysel and Gilbert (see above),Chino et al. (1995), Calford et al. (2000), andothers can be readily found (Huxlin, 2008).

Plasticity in AMD

Age related macular degeneration (AMD) is aprogressive, degenerative disorder that oftencauses a large scotoma in the central visual fieldwhich leads to fixation and reading problems.Such patients also show signs of perceptual plas-ticity as seen in the “filling-in” phenomenon(Cohen et al., 2003; McManus et al., 2008;Mendola et al., 2006; Zur and Ullman, 2003).

Another sign of perceptual plasticity in AMDpatients is that the patients spontaneously adopt

202

a new preferred retinal location (PRL) toachieve eccentric fixation (note: “preferredlocus” does not imply that it is the most optimallocus). In such cases, patients compensate theirfoveal damage by using intact (or partly intact)regions at the edge of the damage to better beable to fixate objects (Greenstein et al., 2008;Schuchard and Fletcher, 1994). Eccentric fixa-tion can also be learned which may improvereading (Nilsson et al., 1998, 2003; Watsonet al., 2006), and, in cases where an unfavorablePRL has spontaneously developed, behavioraltraining can be used to shift the PRL to a moreoptimal location (Nilsson et al., 2003; Radvayet al., 2007). This is needed because anuntrained PRL is sometimes located in an unde-sirable area such as on the left side of the sco-toma, that is, in a position that is not optimalfor reading. When patients are trained to relearna new PRL above or below the scotoma, theymay experience substantially increased readingspeed (Nilsson et al., 1998, 2003), though it isstill unclear, what the best position for such aPRL might be.Imaging studies showed that the visual cortex

of AMD patients shows signs of cortical reorgani-zation in areas of the cortex that topographicallymatch the fovea (Baker et al., 2005, 2008). Corti-cal regions that previously processed only central(foveal) visual information could now beactivated by peripheral stimuli and this reorgani-zation is associated with development of eccentricvision (Schumacher et al., 2008). This type ofreorganization apparently only occurs when thefunctional loss at the fovea was complete, that is,without tissue sparing. However, only smallpatient numbers were studied so far, requiringconfirmation in larger clinical trials, which arecurrently underway in the UK (G. Rubin, per-sonal communication). Yet, the spontaneousdevelopment of PRLs and the ability to retraintheir location are signs of how the visual systemuses plasticity mechanisms to adapt to the loss.Here, intact tissue takes over the role of thedamaged regions.

Plasticity in glaucoma

Glaucoma is the leading cause of visual field lossin all age groups (Ramrattan et al., 2001). It is aslowly developing retinal disease where elevatedintraocular pressure leads to retinal ganglion cell(RGC) death. In contrast to AMD, field defectsin glaucoma typically emerge from the peripheryof the visual field. This may be one of the reasonswhy visual field impairments remain undetectedby the patient for a long time until nerve cell losshas already progressed significantly with seriousfield impairments. Another reason for the latedetection may be that the brain adapts to the slowloss by plastic changes: it compensates the retinalcell loss by some yet unknown mechanism (suchas filling-in), keeping it subclinical or below con-scious perception.

While the progression of glaucoma-inducedvisual field loss can mostly be arrested by propermedication, the scotoma, once detected, is consid-ered to be permanent, with no chance to improve.However, some RGCs survive within the damagedretinal regions (Pavlidis et al., 2003) and perhapsby the process of RF plasticity, the functionallydeafferented visual cortex undergoes sensitivitychanges. Gudlin et al. (2008) have carried out apilot study with five patients that suffered stableprimary open-angle glaucoma and trained themwith near-threshold repetitive light stimuli (visionrestoration training, VRT). They observedimprovements in the perception of light stimuli inperimetries of the central visual field in fourpatients. This observation was later confirmed bya randomized, placebo-controlled clinical trial with30 glaucoma patients with stable visual field loss atbaseline who were randomized to one of twogroups: either “VRT”, or “stimulus discriminationtraining” for 3 months (Gudlin, 2008). VRT signif-icantly increased the detection performance in dif-ferent perimetric tasks which confirms that evenvisual loss after retinal damage can be improvedby training the visual field border.

In summary, there are signs of considerableplasticity even in cases of retinal lesions which

203

can happen spontaneously (as shown in thePRLs) or are induced by perceptual training.While it is possible that there is plasticity on theretinal level as well or even in the damaged nerveitself, it appears that the functionally relevantchange requires central visual pathway plasticityat the level of the lateral geniculate, the visualcortex or higher cortical networks.

Plasticity after optic nerve lesions

Prechiasmatic (optic nerve) lesions typically havea traumatic or inflammatory origin with concen-tric narrowing of the visual field after compres-sion of the outer portions of the optic nervefibers.

Animal models

Optic nerve damage has been a popular model tostudy neuroprotection, regeneration, and func-tional restoration after acute complete or incom-plete injury (e.g., Benowitz and Yin, 2007, 2008;Heiduschka and Thanos, 2000; Lorber et al.,2008). Here, we will focus our discussion on resto-ration of function after partial optic nerve crush(ONC), which was studied for many years in ourlaboratory. ONC can be induced in adult rats bymeans of cross-action forceps which producedefinable, reproducible lesions (Duvdevaniet al., 1990). Though the rat has a relatively sim-ple visual system compared to higher mammals,its contrast sensitivity function is roughly compa-rable to that of cats, monkeys, and humans(Keller et al., 2000). After ONC, only a definable,small number of cells survive after the injury, thusproviding a small remnant of residual fibers (sim-ilar to Lashley's work, e.g., Lashley, 1939). If thisspares just a small, minimum number of neuronsand axons, spontaneous recovery of some visualfunctions can take place such as brightness or pat-tern discrimination, or orientation toward smallmoving targets (Duvdevani et al., 1990; Sautter

and Sabel, 1993; Sautter et al., 1991; Schmitt andSabel, 1996a,b).

Because the slope of recovery is typically about2–3 weeks, ONC recovery can be correlated wellwith cellular and molecular changes that accom-pany recovery (Sabel et al., 1995; Sautter andSabel, 1993; Sautter et al., 1991). Within the first1–2 weeks, the number of RGCs is reduced byas much as 70–90% as a result of retrogradedegeneration (Sabel et al., 1995, 1997; Sautterand Sabel, 1993). After that time, only about10–30% of the RGCs survive and remainconnected with their principle target, the superiorcolliculus (Prilloff et al., 2007; Rousseau andSabel, 2001; Rousseau et al., 1999; Sabel et al.,1997; Sautter and Sabel, 1993). Although recov-ery is usually incomplete, the extent of recoveryis remarkable: performance in visual tasks imme-diately after the damage is only 10–30% (whichcorresponds to the cell number at that time) butvision improves to about 80–90% within 2–3weeks (Rousseau and Sabel, 2001; Sabel et al.,1997). The surviving, residual cells show morpho-logical and functional signs of plasticity: their cellbody size moderately increases (Rousseau andSabel, 2001; Rousseau et al., 1999) and their cal-cium activity levels rise in a delayed and moder-ate manner (Fig. 1), unlike the fast calciuminflux that precedes cell death (Prilloff et al.,2007). We believe that these cellular changes con-tribute to vision restoration because (i) the timecourse of the delayed cellular and metabolicchanges is similar to the time course of functionalrecovery (Prilloff et al., 2007), and (ii) the hyper-activation of residual neurons leads to hyper-responsiveness to visual stimulation (Prilloffet al., 2007). These correlations in time of behav-ioral and neurobiological changes are an exampleof “within-systems” plasticity (see below).

Recovery of optic neuritis in humans

Spontaneous restoration (recovery) of vision afteroptic nerve lesions is also seen in humans and

204

typically happens within the first weeks andmonths after damage. Recovery can happen evenif conduction speed remains impaired as evidentin longer latencies of the visual evoked potentials(VEPs; Levin et al., 2006; Russ et al., 2002;Werring et al., 2000). This suggests thatmechanisms of recovery are probably notrestricted to the optic nerve (within-systems

plasticity) but may also involve associatedstructures along the visual pathway (networkplasticity). Korsholm et al. (2007) measured theeffects of visual stimulation with functional imag-ing in 19 patients recovering from acute opticneuritis (ON) and found activations in the LGNof the thalamus and in the visual cortex in boththe acute condition and after 3 and 6 months

Recovery from optic nerve damage

No. of neurons

0

100

200

300

400

500

600

700

800

900

−2 2 4 6 10 15

Pre crush Days after crush

FI (%

Bg)

BgRGC type IRGC type IIRGC type IIIDying RGCs

*

* *

**

*

*

Calcium activation in residual neurons

(a)

(b)

Metabolic activity (2DG)

Visual function

Days after crush

80

70

60

50

40

30

20

10

00 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30

Per

cent

age

of c

ontro

l

Fig. 1. Recovery frompartial optic nerve damage. The partial optic nerve crush in the rat serves as amodel to study recovery frompartialvisual system damage. (a) Time course of behavioral and anatomical change after optic nerve crush. Despite an ongoing loss of retinalganglion cells (RGCs), there is recovery of vision and metabolic (2DG) activity. The surviving cells seem to be able to compensate theloss rather well. (b) RGCs that manage to survive (RGC type II and III) show increased calcium activation and greater responsivity tovisual stimulation starting at day 10-postlesion which is the time that significant recovery has taken place. These hyperfunctional cellsmay contribute to recovery of vision (see Prilloff et al., 2007); RGCs with massive calcium influx die within 6 days.

205

post-lesion. In the acute phase, the LGN andvisual cortex activation were significantlyreduced. The difference in activation of the intactand the damaged eye, however, became smaller(recovered) over time and was no longer signifi-cant at 6 months. This could be explained by anincreased activation of the retina of the damagedeye and also an activation reduction of the retinain the intact eye.

Patients with ON undergo cortical and subcor-tical neuroplasticity as revealed by functionalmagnetic resonance imaging (fMRI; Korsholmet al., 2007, 2008). While adaptive cortical reorga-nization in higher visual areas was not directlyobserved in the Korsholm studies, extrastriateactivations may happen, which is a sign of anadaptive reorganization of cerebral activity afteracute ON (Toosy et al., 2002, 2005). Toosy et al.(2002) observed activations in the right insula/claustrum, lateral parts of the temporal–parietalcortex and in thalamus. Thus, not only the pri-mary structure of the visual system damage isinvolved in the post-lesion plasticity responsebut also secondary (and probably tertiary)structures.

In summary, activity patterns along the entireaxis of the visual system may change during spon-taneous vision restoration (recovery), particularlyin extrastriate areas, and these may very well beassociated with performance improvements(Henriksson et al., 2007; Toosy et al., 2002,2005). It has not been resolved to which extentthese activation changes are necessary or suffi-cient for the recovery process, if they are adaptiveor maladaptive, and which mechanisms andstructures are involved. This needs further study.

Plasticity after post-chiasmatic lesions

In contrast to lesions of the retina and opticnerve, damage in upstream brain regions (suchas primary visual cortex) may leave differentalternative pathways intact, depending on thelesion location. Especially in the early literature

the question of interest was this: Which structuresare necessary for vision and how well can animalsrecover when visual structures are damaged?

Spontaneous recovery of vision in animals

Lashley (1939) was, to the best of our knowledge,the first to report recovery of vision in rats. Hefound that with only small remnants of survivingtissue, amounting to as few as 700 cells in theLGN of the thalamus (which is about one-fiftiethof the normal number), visual discrimination abil-ity was maintained. After cortical lesions, rats, justlike other species (such as hamsters, hedgehogs,tree shrews, cats, and monkeys), were initiallyimpaired in their ability to solve visual problems,but over time some visual functions recovered.

To determine which brain areas are involved inrecovery from visual cortex damage, Baumannand Spear (1977) first allowed the animals torecover from a visual cortex lesion and thenremoved additional areas of the brain. Loss ofthe lateral portions of the suprasylvian gyrus leftthe animals unable to recover, suggesting that thisarea played a special role in recovery. AlsoFischman and Meikle (1965) suspected that otherbrain areas (pretectum or the suprasylvian gyrus)might be critical for recovery in such combinedlesion cases.

Recovery of vision has also been studied incats. Wiesel and Hubel (1965), for example, notedsome limited recovery in kittens with early visualdeprivation induced by eye sutures, even if thedeprived eye was reopened at a time well beyondthe “critical period.” Also in adult cats, recoveryof brightness discrimination was described afterbilateral cortex or superior colliculus removal orsimultaneous removal of both structures (in whichcase additional training was required, see below)(Urbaitis and Meikle, 1968). Only when all alter-native pathways of the visual system were dam-aged simultaneously (total network lesion),recovery was no longer possible (Fischman andMeikle, 1965).

206

Since these early observations, many studieshave been published on either electrophysiologi-cal measures of cortical reorganization or behav-ioral measures of vision restoration andreorganization following cortical deafferentationor silencing by retinal lesions. This includes stud-ies of (i) RF reorganization after retinal (Chinoet al., 1995; Gilbert and Wiesel, 1992) or corticallesions (Eysel, 1997) which depends in its extenton visual experience (Milleret and Buser, 1984);(ii) recovery from monocular deprivation duringor after the early critical period when the compet-ing, intact eye is occluded or removed (He andLoop, 1991; Maire-Lepoivre et al., 1988; Mitchellet al., 1984; Smith and Holdefer, 1985; Spearand Ganz, 1975; van Hoff-van Duin, 1976); (iii)restoration of visual functions after additionalbrain lesions which lift inhibition by competingfibers to the deafferented zone (Di Stefano andGargini, 1995; Wallace et al., 1989) or after lossof the intact, fixating eye in amblyopia (Tiemanand Hirsch, 1983); and (iv) complete or incom-plete spontaneous recovery of vision after lesionsof the cortex (Baumann and Spear, 1977; DeWeerd et al., 1993, 1994; Fabre-Thorpe et al.,1994; Wallace et al., 1989) or optic tract(Jacobson et al., 1977, 1979).In the macaque monkey, the primary visual

cortex and visual association areas occupy about50% of the total cortical mantle (Van Essen andMaunsell, 1980). Monkey studies on restorationof vision are more rare and they typically employonly very few animals. While specific lesionswithin visual pathways usually lead to stabledeficits, there have been a few reports showingrecovery of some visual functions in monkeysindicating that an initial loss of vision must notalways be permanent.Zee et al. (1983), for example, created bilateral

occipital lobectomies in monkeys, rendering theanimals incapable of smooth pursuit eye move-ments 1 month postsurgery. In the subsequentmonths, however, the function recovered to nor-mal levels. Also Mohler and Wurtz (1977) notedrecovery in a visual detection paradigm within 3

weeks following either cortical or tectal injury,but no recovery was seen when both lesions werecombined. Also, lesions in area MT producedpursuit eye-movement deficits from which themonkeys recovered within the relatively shortperiod of about 1 week (Dürsteler et al., 1987;Newsome et al., 1985). This was attributed tothe relatively small size lesion.

Surprisingly, unilateral lesions produce some-times more permanent deficits from which theanimals do not recover. Segraves et al. (1987)offer the following explanation for this apparentparadox: “First, the monkey with unilateral striatelesions presumably relies upon the intact striatecortex for input to the smooth pursuit system.However, a monkey with a bilateral striate lesionis left with only subcortical and residual extra-striate visual mechanisms, and so may use themmore fully. The effect is analogous to the ten-dency of monkeys with unilateral rhizotomies toavoid use of the deafferented limb until the intactone is mechanically restrained” (p. 3056). This isrelated to the “Sprague effect” as discussedbelow.

Spontaneous recovery of vision in humans

Traditionally, geniculostriate lesions were consid-ered to result in complete and permanent visualloss in the topographically related area of thevisual field (Holmes, 1918; Poppelreuter, 1917)though the maintenance of movement perceptionwas noticed by some clinical investigators(Riddoch, 1917). Lesions of the occipital cortextypically cause contralateral visual field defects ter-med hemianopia or quadrantanopia, depending ontheir size. Teuber et al. (1960, 1975) was amongthe first to systematically observe recovery ofvision in patients. He extensively studied soldierswith gunshot wounds of the brain acquired duringthe Korea war and found better recovery in youn-ger patients. Further, the spontaneous shrinkage ofthe resultant scotoma depended on the age atlesion (Teuber, 1975).

207

In humans with brain injury, recovery of visualfunctions is the rule and not the exception. Butpatients with visual field defects typically have apoor prognosis if they do not spontaneously recoverearly on. The speed of recovery depends on thelesion characteristics: whereas in cases with partialdefectsmaximal recovery is achievedwithin the first48 h (Pambakian and Kennard, 1997; Pambakianet al., 2005), recovery from complete hemianopiaoccurs usually within the first fewweeks.About halfof the patients show partial recovery and less than10%of patients recover their full field of vision back(Zhang et al., 2006). There are only very rare casesof spontaneous vision recovery beyond this timepoint (Poggel et al., 2001).

Nelles et al. (2002, 2007) studied patients withischemic lesions of the visual cortex using func-tional imaging. While in a control group, theyobserved the maximum activity in hemifield stim-ulation in the contralateral visual cortex and bilat-erally in the extrastriate cortex, the patientsshowed increased ipsilateral activation in theextrastriate cortex when stimulating thehemianopic hemifield. Although many studiesare available on spontaneous and training-induced visual field recovery, cortical reorganiza-tion processes after acquired visual cortex lesionsare rarely examined (Dilks et al., 2007).

Schoenfeld et al. (2002) described a younghemianopic patient (age 22 years), who spontane-ously recovered some motion and color perceptionat 1 month post-lesion. Functional neuroimagingshowed activation of areas V4/8, V5, and V2/3 withno activation in his damaged V1. Magne-toencephalographic recordings revealed more pos-terior activation areas V2/3 followed by activationof the MTþ and V4/8 complex. Other functionalimaging studies have also shown that stimulatingfields of residual (or recovered) vision leads toactivation of extrastriate cortical regions whichwas interpreted as a sign of reorganization(Rausch et al., 2000). But other studies could notconfirm this (Barbur et al., 1993; Zeki and Ffytche,1998). Clearly, this is an area requiring furtherexperimentation.

In this context, it is noteworthy that patients,especially those with blindness early in life, showa massive reorganization of the brain involvingmultimodal activation of nonvisual senses. Here,the brain recruits visual cortex for otherfunctions, for example, processing of tactile inputin reading Braille (Sadato, 2005). This type of“transmodal plasticity” is important for thepatient to compensate their vision loss andremain able to orient and navigate in space.

Reorganization in congenital and early blindness

Congenital and early blindness are different inthat they originate early in life, when the brainhas a considerable developmental plasticitypotential. Here, the “visual” cortex of the blindprocesses somatosensory and auditory informa-tion, which suggests a rewiring of neuralassociations sending nonvisual sensory informa-tion to the visual cortex (Noppeney, 2007; Ptitoand Kupers, 2005; Ptito et al., 2008). Conse-quently, “intermodal plasticity” appears to out-pace within-systems plasticity in the early blind.

Park et al. (2007) studied the neural reorgani-zation in the visual cortex in early blind patientswith diffusion tensor functional imaging. Mainlyin the primary visual pathway, reduced anisotropyand increased diffusion were found compared toemmetropic subjects. Changes in regional diffu-sion were observed not only in the visual pathwaybut also in nonvisual areas such as the U-fibers ofthe parietal lobe, the striatum, the pulvinar, andthe inferior and superior longitudinal fasciculus.These changes are adjustments to the early lossof visual system structures. These adjustments,in turn, may represent hyperfunctions of othersensory systems (especially hearing and somato-sensory functions) which the blind need for orien-tation in space (Ptito et al., 2008).

Another study that highlights the potential ofresidual capacities of congenitally blind peoplewas presented by Gothe et al. (2002) who appliedtranscranial magnetic stimulation (TMS) to excite

208

the visual cortex of patients with congenital blind-ness. Patients reported phosphenes in differentretinotopic positions even inside areas of per-imetric blindness, and these phosphenes couldbe provoked by TMS more easily in patients withsome residual vision.Recently, a remarkable case of plasticity in con-

genital blindness was reported by Ostrovsky et al.(2006). An adult subject from India, S.R.D., whowas blind from birth on until age 12 at which timeshe underwent surgery for removal of dense con-genital cataracts on both eyes, still had acuityimpairments at age 32, but, surprisingly, S.R.D.'sacuity was proficient on mid- and high-level visualtasks. The authors concluded that the human brainretains an impressive capacity for visual learningwell into late childhood which was observed alsoin three other subjects in a later study (Ostrovskyet al., 2009).

Residual vision

Clinically relevant plasticity occurs not primarilyin regions of “absolute blindness” but in “areasof residual vision” (ARVs). They are located atthe visual field borders and in islands of residualvision in regions of presumed “total” blindness.

Residual vision at the visual field border

The difficulty to appreciate the existence of resid-ual vision at all has, besides conceptual issues, atechnical origin. Current perimetric methods werenot designed to measure ARVs, visual cognition,or subjective vision. They were designed to mea-sure vision loss that results from eye diseases(such as glaucoma). Thus, standard perimetrymethods are not very detailed (low resolution)and have other limitations when applied to thestudies of the more subtle phenomenon of visualsystem plasticity: they simply ignore the weakerresidual visual functions. This may be onesource of some controversy over the

interpretation of visual field expansion results(Sabel and Trauzettel-Klosinski, 2005). Just pay-ing attention to intact regions and damaged areas(absolute defects) is insufficient. Rather, ARVsthat are known also as “relative defects” are keyin our understanding of visual system recovery(Kasten et al., 1998a; Sabel, 1999; Sabel andKasten, 2000; Sabel et al., 2004; Widdig et al.,2003; Zihl and von Cramon, 1979).

Thus, a more precise diagnostic with higher res-olution needs to complement the existing staticsupraliminal- and threshold-perimetry. Also,visual information in daily life is normallyprocessed binocularly. For these reasons in ourlaboratory, we usually evaluate visual fields withboth eyes open using a specifically developedcomputer-based method termed “high-resolutionperimetry” (HRP; Kasten et al., 1998a,b). Thismethod presents suprathreshold light stimulirepeatedly in random sequences (Kasten et al.,1998a). As Fig. 2 shows, binocular HRP revealsareas of inconsistent detections (gray areas),intact areas (white), with reliable stimulus detec-tion, and areas of absolute blindness (blackareas). The brightness of the light stimuli is ofdecisive relevance for the characterization of theintact, residual (partially damaged), and absolutedamaged areas. When using brighter (high-con-trast) light stimuli, the intact visual field areaappears larger than when darker (low-contrast)light stimuli are used. Typically, there is not asharp border between the damaged and intactvisual field but rather a more smooth “transitionzone” (relative defects) which varies considerablybetween patients in size or shape (Kasten et al.,1998a). These “fuzzy” transition zones are partic-ular prominent in patients with prechiasmatic(optic nerve) lesions as they have a rather inho-mogeneous, scattered visual field defect (Fig. 2).

We have proposed that these transition zonesare the functional representation of partially dam-aged brain areas and termed them “ARVs”(Fig. 3). They are the regions where plasticitymostly occurs. Here, neurons survived the dam-age similar to what we found in our rat

209

−25 −20 −15 −10 −5

−5

−10

−15

−20

0 5 10 15 20

20

15

10

5

0

25

−25 −20 −15 −10 −5

−5

−10

−15

−20

0 5 10 15 20

20

15

10

5

0

25

−25 −20 −15 −10 −5

−5

−10

−15

−20

0 5 10 15 20

20

15

10

5

0

−5

−10

−15

−20

20

15

10 100 %

Areas of residual vision(a)

(b)

(c)

(d)

80 %60 %40 %20 %0 %Fixpoint

5

0

25

−25 −20 −15 −10

Intact ARV

Reducedinput

Completedamage

Full input

blind

−5 0 5 10 15 20 25

Fig. 2. Areas of residual vision (ARVs). (a) To assess the visual fields with high-resolution computer-based perimetry (HRP),suprathreshold stimuli are presented at random from which simple detection charts (here: 3) can be created. Intact visual field sectoris shown in white; black represents regions of absolute blindness. When superimposed, the new chart (right) reveals gray areaswhere response accuracy is inconsistent. They are known as ARVs or relative defects. Gray regions are interpreted by us asrepresenting partial damage where only some cells remain connected with their target structure. Thus, partial structure leads topartial function (b, c). The disconnected cells will degenerate retrogradely due to lack of trophic support. (b) Different brain regions(square) can suffer different severities of deafferentation, shown in different shades of gray in the visual field map. The extent ofdeafferentation has a functional correlate: the greater the loss, the lower the functional accuracy, ranging from intact (white)through shades of gray (i.e., ARV) to black (blind). (c) The concept of stimulation-induced synchronization after partial nervoussystem damage. While neurons of the intact regions fire in a synchronized manner to drive normal vision (here they jointly fireaction potentials in perfect temporal coordination), areas of partial damage are nonsynchronized, with poor firing synchrony. Inblind (black) regions, no neuronal firing is elicited due to complete loss of neurons. After external stimulation which is induced bytraining or during electric current stimulation, the partially damaged regions are forced to fire jointly in temporal coordination. It ishypothesized that repeated stimulation induces a synaptic plasticity of the partially damaged structures (shown here) anddownstream areas (not shown here), stabilizing their synchronous firing beyond the treatment period (aftereffects). This improvedor stabilized synchronization is one of the proposed neurophysiological mechanism of vision restoration.

210

10%V1

V2–V5

90%

Tectum/pulvinarLG

N

Retina

Striate

Extrastriate

P1

P2

P4

P3

Plasticity in striate and extrastriate regions

Restored visual fields(b)

(a)

Trai

ning

AC

S

Before After

5

20

15

10

5

0

–5

–10

–15

–20

–25 –20 –15 –10 –5 0 5 10 15 20 –2530 –20 –15 –10 –5 0 5 10 15 20

100 %80 %60 %40 %20 %0 %Fixpoint

20

15

10

0

–5

–10

–15

–20

Fig. 3. Vision restoration pathways: striate and extrastriate. (a) This highly simplified diagram shows the primary and secondary visualstructures in the human brain. In the normal brain, the main retinofugal pathway is the retino-geniculo-striate pathway (striate route)which comprises the majority (>90%) of retinofugal fibers. It supplies striate cortex and higher cortical regions with neuronalinformation for normal perception. Only a small proportion of retinofugal fibers (probably <10%) travel an alternative (extrastriate)route, that is, via the direct geniculo-V5 connection or the retino-tectal/pulvinar pathway. When a lesion damages the primary visualpathway (e.g., lesion in V1 as shown in black here), plasticity can occur in different places (P1–P4) along the neuronal pathway so thatinformation traveling to higher cortical regions are facilitated: (i) via intact tissue in V1, (ii) via partially damaged, residual regions inV1 (the gray zones surrounding the lesion), or (iii) via the extrastriate pathways. These alternative pathways mediate different kinds ofresidual visions, depending on the lesion size and location. Vision restoration may be mediated by any one of these pathways or acombination of them. (b) Examples of visual fields of two patients showing vision restoration (the x- and y-axes display degrees ofvisual angle). For explanation of the charts, see legend to Fig. 2. The upper visual field charts are taken from a stroke patient sufferingfrom hemianopia, the lower charts from a patient suffering from optic nerve damage (Gall et al., 2010b). The stroke patient wastreated with behavioral vision training for 6 months and the optic nerve patient with alternating current stimulation (ACS) for 10 days.Note the marked improvement of visual detection ability after the treatment in both cases. Both black and gray areas showed markedfunctional improvements, leading to significant visual field expansions. These cases show that vision restoration is possible.

211

experiments after optic nerve lesions (Fig. 1),though visual information is processed at a subop-timal level. These residual structures are the pri-mary targets for therapeutic intervention(Kasten et al., 1998a; Sabel, 1999; Sabel andKasten, 2000). Both objective tests and subjectivepatient reports indicate that the quality of thevisual perception in ARVs is significantlyreduced. ARVs also show increased reactiontimes to stimuli of different brightness, and colorsand shapes are insufficiently discriminated(Kasten et al., 1998b; Sabel and Kasten, 2000).Subjectively, patients reported them as shadowsor “diffuse” vision.

ARVs, by their nature of being functionallycompromised, are also the largest source ofvariability in visual field testing (Poggel et al.,2010). Zihl et al. (1977) observed daily variationsin visual field size up to 10�. A possible cause offluctuations in the visual field size and intra-individual variations of residual vision areperiodic fluctuations in brain activity, in particularin the alpha-band (8–14 Hz) (Romei et al., 2008a,b): fluctuations in the alpha-band correlatedhighly with the probability of visual stimulusdetection. Therefore, fluctuations may be anexpression of the activation state of the visualsystem and this may, in part, explain the inconsis-tent stimulus detections in these areas of thevisual field. The activation state depends muchon the state of general attention and vigilance(arousal).

In summary, spontaneous plasticity is a rathercommon event, irrespective of where the lesionis located along the axis of the visual pathway.Plasticity is not a unique feature of the humanbrain but can be found in all species. In fact, ani-mal experiments have helped a lot to delineatepossible mechanisms underlying vision restora-tion and recovery. But besides partially injuredARVs of the primary visual pathway, there areother routes whereby higher cortical regions canreceive visual input after lesions of the visualcortex.

Blindsight

Since the seminal work by Schneider (1969) andothers (Felleman and Van Essen, 1991), it isknown that the retina has different routes to sendvisual information to higher cortical regions.Lesions limited to the coronal radiation or thevisual cortex do not directly injure the “extra-striate” pathways which therefore survive theinjury (Fig. 3). In a way, damage in one regionof the visual system network leaves other detouroptions intact. For many years, the role of thesesurviving pathways in mediating residual visionhas been explored. Despite cortical blindness, cer-tain levels of perceptual processing aremaintained inside the blind visual field sector.Pöppel et al. (1973) were the first to report thatpatients were able to make saccades when stimuliwere presented at different eccentricities insidetheir blind fields. Later, Weiskrantz et al. (1974)described a patient with partial occipital ablationwho was able to carry out not only manual andsaccadic localization but also discriminated lineorientations, shapes (X and O), and color by cor-rect guessing. But because the patient was notaware of a conscious percept, this phenomenonwas termed “blindsight” (Sanders et al., 1974).Since then, there have been many reports ofblindsight and this field has been discussed exten-sively (for reviews, see Cowey and Stoerig, 1995;Stoerig, 2006; Stoerig and Cowey, 1997). It hassince been described that motion perception islargely maintained in the blind area as some(but not all) patients with striate lesions are capa-ble of detecting moving stimuli in the scotoma,being able to indicate the direction of simple orcomplex stimuli. This intact perception of visualmotion is probably mediated by a direct gen-iculate–V5 connections (Azzopardi and Cowey,2001; Benson et al., 1998).

There was a controversy if blindsight is an exclu-sive affair of extrastriate, alternative pathways by-passing V1 (Stoerig, 1993; Weiskrantz, 1996) or ifit is rather mediated by intact residual areas of

212

the primary visual cortex in islands of residualvision (Fendrich et al., 1992, 1993; Sabel andKasten, 2000; Wessinger et al., 1997) (Fig. 3).The correct answer is probably that it couldbe both. The reason we believe also in a roleof residual fibers of the primary retino-genulate–striate route is that even patientssuffering optic nerve damage show blindsightinside the blind field (Wüst et al., 2002). Thisargues for the existence of partially surviving tissueinside the blind field which is able to mediatevisual functions without awareness. Today,blindsight is thought to be sustained by three dif-ferent mechanisms (Cowey and Stoerig, 1991): (i)extrageniculate activity via the subcortical pat-hways, (2) geniculo-extrastriate involvement, or(3) partial sparing of visual cortex with preserva-tion of cortical processing sufficient for stimuli toreach a subjective threshold. So the issue is notwhich one of these hypotheses is correct but ratherhow much each of the different routes contributesto a particular patients’ response. It seems reason-able to assume that all available retinofugal routesare involved in vision restoration: the partiallydamaged, primary structures as well as the undam-aged, non-V1 projections (Fig. 3). Perhaps, itmatters less which exact residual structures con-tribute to vision restoration but how much activa-tion is produced in areas downstream of V1(V2–V5 and other higher cortical areas). Whateverthe mechanisms of blindsight are, it is indeed avery impressive example of how the brain is capa-ble of processing residual functions, being able tocreate visual percepts by information reroutingdespite the lack of primary visual cortex.

Activating residual vision

Ever since the studies by Held and Hein (1963)and Hubel and Wiesel (1970), it is known thatvisual stimulation is required for normal visualsystem development. Early in life, active visualexperience shapes the structure and function ofthe visual system, particularly during the criticalperiod which is thought to end at the age of

around 7–10 years for binocular visual functionsin humans (Greenwald and Parks, 1999; Prieto-Diaz, 2000; von Noorden, 1981). But also in theadult brain, visual experience shapes neuronalfunction, as it is known from studies of perceptuallearning. Even after damage in the adult visualsystem, recovery of function happens and this isalso stimulation dependent.

There are different means of stimulating thedamaged visual system: (i) visual experience, (ii)active behavioral training (massed practice), and(iii) electrical brain stimulation. As we nowshow, all of these methods have some capabilityto activate residual visual functions.

Activating residual vision by experience

Experience-dependent plasticity is a well-researched field in developmental neurobiology.Deprivation early in life produces long-lastingvisual deficits, and environmental stimulationand enrichment is beneficial for normal functionaldevelopment (Karmarker and Dan, 2006).For example, enriched environments can enhancerecovery from amblyopia by reducing intra-cortical inhibition (Cooke and Bear, 2010; Saleet al., 2007).

To study the role of experience during post-lesion recovery after CNS damage, we exposedadult rats with partial ONC during the first 4weeks of recovery to different visual environmen-tal conditions: (i) standard 12:12-h light:darkcycle; (ii) visual enrichment, which consisted of a2 h selective visual activation (strobe lights,blinking lamps, and moving bars) and 22 h dark-ness; and (iii) total darkness only (Prilloff et al.,2010). Behavioral tests with a 6-choice brightnessdiscrimination task revealed that rats kept undernormal daylight conditions recovered their visualfunctions rather well, but rats housed in completedarkness failed to recover. However, only 2 h ofdaily exposure to visual enrichment (in an other-wise dark environment) led to significant recov-ery, the speed of which was even faster than in

213

rats housed under normal daylight conditions.Thus, visual experience, even if provided for shortdaily periods, is a critical factor determining theearly phases of recovery. Without any stimulationof residual vision, recovery seems impossible.

Whereas during the early recovery phase visualexperience is critical, once a plateau has beenreached, visual experience is apparently not suffi-cient to generate further vision restoration. This islargely due to the overpowering influence of theintact visual field (see discussion below). Conse-quently, a specific activation of residual visionby behavioral training or electrical stimulation isneeded.

Activating residual vision by training

Behavioral training is more demanding than envi-ronmental enrichment. It typically involves a“massed repetition” of certain behavioral tasksand this is carried out for up to 1 h daily for weeksand months. The goal of visual training is not toenhance the early recovery rate but to improvefinal outcome in older lesions with stable visualimpairments. During training, visual stimuli arepresented to which the subject (animal or patient)has to respond. In a way, training produces a syn-chronized firing of the residual cells in a smallregion of the retina (within a few degrees ofvisual angle which leads to visual fieldimprovements (Figs. 3–5). In contrast, after non-invasive brain electrical stimulation, the entirevisual system is simultaneously synchronized(see section “Activating residual vision by electri-cal current stimulation”).

Training residual vision in animal studies

Though visual-training tasks have been studied inrats (Spear and Barbas, 1975; Stein andWeinberg, 1978), more studies are available incats and monkey. In cats, the effects of visualstimulation are typically studied after eye closure

early in life (to simulate amblyopia). Chow andStewart (1972) showed that in newborn kittenswhich had one eye sutured for 16–24 months,subsequent visual stimulation (experience) byreopening of the sutured eye, together with theforced use of it (training), was beneficial. Uponreopening the eye, the kittens initially appearednot to use their deprived eye but rather reliedon their intact eye to perform visual tasks, as ifthe deprived eye had been “switched off.” Theanimals kept walking into objects, failed to followa moving light, and did not blink in response to asuddenly approaching hand. Over the course ofseveral months, however, vision graduallyreturned to levels where no more blindness couldbe found, which is what others also found (Ganzand Fitch, 1968; Riesen, 1961). Chow and Stewart(1972) attributed much of the recovery to the sev-eral hundred trials of training the animalsreceived in a pattern discrimination task whichwas carried out during the recovery phase.Though it is unclear if the improvement wascaused by the normal visual experience or bythe training sessions, it highlights the fact thatdeprivation effects must not be permanent, evenwhen the eye reopening occurred well after thecritical period. Also in other studies, massivetraining of about 1200 trials allowed the cats torelearn brightness discrimination (Payne et al.,1996; Urbaitis and Meikle, 1968).

These training effects were also seen in monkeys.Cowey (1967) studied two rhesus monkeys withmacular blindness and found that training was inef-fective. Visual field defects after cortical damage, incontrast, could be trained to improve sensitivitythreshold. Pasik and Pasik (1973) observed thatbilateral occipital cortex lesions led to an initialblindness, but 3 months after the injury, themonkeys showed evidence of brightness discrimina-tion. They were now again able to reach for visualstimuli. As in other studies, the functional improve-ment required massive testing (i.e., trainingbetween 300 and 6000 trials with visual tasks).Moore et al. (1996) described a single case of anadult monkey with a large unilateral striate cortex

214

–25 –20 –15 –10 –5 0 5 10 15 20 25

–25

Cas

e 4

Cas

e 3

Cas

e 2

Cas

e 1

–20 –15 –10 –5 0 5 10 15 20 25 –25 –20 –15 –10 –5 0 5 10 15 20 25

–25 –20 –15 –10 –5 0 5 10 15 20 25 –25 –20 –15 –10 –5 0 5 10 15 20 25

–35 –30 –25 –20 –15 –10 –5 0 5 10 –35 –30 –25 –20 –15 –10 –5 0 5 1510

20

15

10

5

0

–5

–10

–15

–20

20

15

10

5

0

–5

–10

–15

–20

25

20

15

10

5

0

–5

–10

20

Baseline After trainingStructure–function mismatch

Improvements in

HRP ADL

++

––

–+

+–

15

10

5

0

–10

–5

–15

–20

20

15

10

5

0

–5

–10

–15

–20

25

20

15

10

5

0

–5

–10

–15

20

15

10

5

0

–10

–5

–15

–20

–25 –20 –15 –10 –5 0 5 10 15 20 25

20

15

10

5

0

–5

–10

–15

–20

Fig. 4. Objective–subjective mismatch. Visual fields (HRP) of four different patients are shown before versus after 6 months ofbehavioral training. Some patients show detection improvements but others do not. The detection changes not always match thepatients’ subjective visual gains as shown by activities of daily living (ADL). Some patients show visual field improvements butdo not notice this subjectively. Others show no alterations of their visual field charts but clearly subjectively report visionrestoration. This mismatch of objective versus subjective visual improvement highlights the fact that the method of measuringdetection of small visual stimuli is not sufficiently sensitive to document all aspects of vision restoration and, when taken alone,gives us only a limited view as to the patients subjective vision.

ablation which improved by training, lowering theerror rate from 75% to only 25%.Anothermonkey,which had not profited from repeated testing at thattime, however, profited at later time points (2 yearsafter injury) at which point it had received a moremassive training of over 5500 trials. This animalnow also improved from a 75% error rate to about25% (Moore, T., personal communication). Inter-estingly, the retrieval of residual vision was easierwhen the fixation point was not present during tar-get stimulus presentation (extinction phenomenon)and recovered (retrained) functions were lost againwhen the luminance of the target stimuli wasreduced (see also Mohler andWurtz, 1977). A veryimpressive observation was made with a trainedmonkey, namedHelen, that had received a bilateraloccipital lesion at the age of 19 months (Humphrey,1970, 1974). Helen showed hardly any visuallyguided behavior right after the lesion, but thenHelen first learned to reach for moving objects,then detected a flashing light and thereafter a sta-tionary light. Autopsy revealed that Helen hadsome peripheral sparing of V1 tissue, that is, anisland of vision in the far periphery. It is this sparingthat could possibly have mediated visual perfor-mance such as stimulus detection in nonperipheralparts of the field. Just as in other studies (Cowey,1967), Helens functions did not develop spontane-ously but took months of repeated training toimprove.

Thus, different monkey studies clearly showthat visual stimulation (training) is beneficial afterstriate cortex injury, but regaining vision requiresextensive visual testing/training in the order ofthousands of stimulus presentations which is simi-lar to the experience with patients (Kasten andSabel, 1995; Kasten et al., 1998b, 2006).

Training residual vision in humans

The body of literature on vision restoration inhumans has significantly grown in recent years(see Table 1). As in the animal models,

behavioral stimulation (training) aims atstrengthening residual visual structures by repeti-tively activating them, leading to facilitation ofsynaptic transmission, probably similar to long-term potentiation (LTP). Today, behavioral stim-ulation (training) of residual vision is by far themost widely used method to stimulate the injuredvisual system. This includes the method of VRT(Kasten and Sabel, 1995; Kasten et al., 1998a,b)which was based on the observation that repeatedtesting at the visual field border may induce bor-der shifts (Zihl and von Cramon, 1979, 1985; Zihlet al., 1977). Other laboratories have used differ-ent kinds of training paradigms, patterns of differ-ent orientations (Sahraie et al., 2006), movingspirals (Jobke et al., 2009), flickering-typestimulations (Henriksson et al., 2007; Raninenet al., 2007; Roth et al., 2009), or Gabor patcheswith (Polat et al., 2004) or without (Sahraieet al., 2006) flanker-tasks to train patients. Thereare only very few null-findings with training(Balliett et al., 1985; Reinhard et al., 2005) andno study exists that found detrimental effects.

There are two major ways to accomplish train-ing effects in patients with brain damage: (i) bystrengthening the function of partially damagedregions (ARVs) typically located at the visualfield border or in islands of vision inside the blindfield or (ii) by training pathways left intact afterthe damage which project directly or indirectlyto higher cortical regions (i.e., those presumablyinvolved in blindsight, see above). The differencebetween the two approaches is both conceptualand practical. Whereas training ARVs is realizedby positioning the training stimuli in the borderzone of the lesion, the latter requires placingtraining stimuli deep in the blind field. Both met-hods of stimulation enhance residual visionand combining them optimizes outcome (Jobkeet al., 2009).

Training residual vision at the border zone Let usfirst consider the behavioral/clinical evidence oftraining effects: training studies aimed at

216

Table 1. Studies reporting visual improvements after intervention

Study Year N Pre-andpost-design

Controlgroup

Results Follow-up

(A) Vision restoration training (VRT) at the lesion borderZihl and vonCramon

1985 44 Yes No Visual field improvements between (VFI) of1.5–38˚˜ in 80% of the patients

No

Balliett et al. 1985 12 Partly No No objective VFI (changes of the visual fieldborder between �2� and þ4�); subjectiveimprovements in four patients

No

Kasten et al. 1998b 19 Yes Yes Visual field border shift of about 4.9� inexperimental group versus �0.9� in the controlgroup; subjective improvements in 72% of theexperimental group versus 17% of the controlgroup

No

Werth andMoehrenschlager

1999 22 Yes Yes Recovery of visual functions in 15/22 childrenwith hemianopia by systematic stimulation ofcerebrally blind areas; no spontaneousrecovery in controls, expansion of visual field>40�

Yes

Kasten et al. 2001 16 Yes Yes VFI of about 2.7� in the experimental groupversus �0.53� in the control group

On average nosignificant decline at23 months follow-up

Julkunen et al. 2003 5 Yes No VFI between 5� and 10� in three patients;partly validated by visual evoked potentials;subjective improvements in four patients

At 3 months follow-up increased orstable area ofnormal vision inthree patients

Sabel et al. 2004 16 Yes No No VFI when checked with Scanning LaserOphthalmoscope, shift of the visual fieldborder about 5–7� in perimetry and computercampimetry

No

Reinhard et al. 2005 17 Yes No No VFI in SLO; increased reading speed in 6%of the patients; satisfaction with training intwo-third of the patients (Note: same patientsample than Sabel et al. (2004) study

No

Werth andSeelos

2005 17 Yes Yes Study of children; VFI improvements only inexperimental group; control of eye movements;validation by fMRI; 11 of 17 patients recoveredvision 1 year after the training; none in thecontrol group

Yes

Kasten et al. 2006 15 Yes No Improvements of stimulus detection incampimetry about 3.8%; decrease errors inperimetry OD (2.2%) and OS (3.5%);improvements of visual field independent fromeye movements

No

Julkunen et al. 2006 1 Yes No Normalization of P100 latencies after visualtraining of the border region, increasedcerebral blood flow restricted to the occipitallobe in a follow-up study at 3 three months

Yes

(Continued)

217

Table 1. Studies reporting visual improvements after intervention (Continued)


Controlgroup

Results Follow-up

Schmielau andWong

2007 20 Yes No VFI of 11.3� on average in 17 patients; subject.improvements in daily life

No

Kasten et al. 2007 23 Yes No VFI in HRP (4.2%), fewer misses within thecentral 30� perimetrically (�3.7% OD, �4.4%OS), VFI did not benefit from double-stimulation

No

Marshall et al. 2008 6 Yes No Significant increase in BOLD activity in borderzone detections after VRT, relativeimprovement in response times in the borderzone, brain activation changes with a shift ofattention from the nontrained seeing field tothe trained border zone

Yes

Gall et al. 2008 85 Yes No VFI<5% detected stimuli in 42% of thepatients, 5–10% in 24% and >10% in 28% ofpatients

No

Gudlin et al. 2008 5 Yes No VFI in HRP and 30� white/white perimetryafter the first treatment, stable effects aftertraining-free interval of 3 months

No

Poggel et al. 2008 19 Yes No Significantly improved detection and reactiontimes in perimetric and HRP-tests along thevisual field border; no improvement in visualacuity

No

Jung et al. 2008 10 Yes Yes VRT compared to intact visual field VRTImproved binocular reading speed, fovealsensitivity (trend), HRP detection by 16–17%,but in both groups

No

Romano et al. 2008 161 Yes No Mean absolute VFI of 12.8% after VRT,improvements of �3% in 76% of patients

No

Mueller et al. 2008 17 Yes No Training effects of 3.5% (OD) and 1.5% (OS)after 6 months of daily VR training, minortraining effects of long-term training

No

Jobke et al. 2009 18 Yes No VFI were twice as good as after extrastriateVRT (4.2%) than after standardVRT (2.4%)

Yes

Poggel et al. 2010 19 Yes No VFI in HRP from 53.6% to 57.6%, increase ofintact field size of more than 16% or bordershifts of more than 18�

Yes (at 6 months)

Marshall et al. 2010 7 Yes No Average improvement in stimulus detectionrate by microperimetry of 12.5% (range–1.4%to 38.9%). Six of 7 patients had � 3%improvement in stimulus detection byhome-based perimetry

No

Raemaekerset al.

2011 8 Yes No VFI with shifts of the central visual fieldborder ranging between 1� and 7�

No

218



Controlgroup

Results Follow-up

(b) Perceptual training with different stimuli inside the blind field or in amblyopiaHyvärinen et al. 2002 5 Yes No Improvement of flicker sensitivity in the blind

hemifield equal to that in the normal hemifieldin two patients, increased recognition of (non-)flickering letters at 20� eccentricity in onepatient

Yes

Polat et al. 2004 77 Yes Yes Training with spatial frequency tasks;improvement in contrast sensitivity, visualacuity improved by 78% above baseline withthe greater improvement in amblyopics withlower initial acuity

Yes

Sahraie et al. 2006 12 Yes No Repeated stimulation inside the blind visualfield resulted in improvements deep in the fielddefect, discrimination performance increasedmonotonically with increasing contrast

No

Raninen et al. 2007 2 Yes No Improvement of flicker sensitivity in the blindhemifield within 20� respectively 30�

eccentricity, recognition of flickering letters at10� eccentricity

Yes

Henriksson et al. 2007 1 Yes No Visual information of flicker training wasmainly processed in the intact hemisphere,representation of both the intact and the blindhemifield takes place in the same set of corticalareas in the intact hemisphere

No

Chokron et al. 2008 9 Yes No Objective improvement of behavioral tasks innine patients and objective enlargement of thevisual field in 8/9 patients

No

Roth et al. 2009 28 Yes No No improvement with flicker-stimulationtraining deep in the blind field

Yes

Jobke et al. 2009 18 Yes No Detection performance increased twice asmuch after extrastriate VRT (4.2%) than afterstandard VRT (2.4%)

Yes

Polat et al. 2009 5 Yes No Training with Gabor patterns; Visual acuityimprovement of 1.5 Snellen lines, improvementof contrast sensitivity in children

No

Sahraie et al. 2010 4 Yes No Improved detection ability in 3/4 patients aftervisual detection training of spatial gratingpatches within the field defect

Yes

(C) Noninvasive alternating current stimulation of the brainGall et al. 2010b 1 Yes No Detection ability increased from 3.44% to

17.75%, mean perimetric threshold from 0 to2.21 dB

No

Fedorov et al. 2010 446 Yes No VFI in 40.4% (OD) and 49.5% (OS) of thepatients after rtACS, significant increase ofvisual acuity (OD: 0.02; OS: 0.015), furtherimprovement after a second treatment course

Yes

(Continued)

219

increasing the function of the border areas havebeen conducted with stroke and trauma patientswho suffered hemianopia or scotomata. Zihl andvon Cramon (1979, 1985) have trained the borderitself using repetitive visual field testing. Othershave stimulated the border region after firstidentifying ARVs and focusing the training areaon them (see Kasten and Sabel, 1995; Kastenet al., 1998a,b,c). The training is aimed at the bor-der region especially at regions of partial damage,that is, ARVs (gray in Fig. 2). This approach istermed VRT. Extensive training over the courseof up to 6 months leads to a reduction of thescotoma size (Julkunen et al., 2003, 2006;Kasten et al., 1998a,b; Marshall et al., 2008;Mueller et al., 2008; Poggel et al., 2008; Romanoet al., 2008; Sabel and Kasten, 2000; Sabel et al.,2004; Werth, 2008; Widdig et al., 2003), effec-tively enlarging the visual field by primarily trans-forming the ARVs into intact areas (Fig. 3).About half to two-thirds of the patients achievevisual field expansions (at an average of 5 degreesof visual angle), but training success varies consid-erably between patients; some patients (1/3) donot respond to the therapy, others show moderateimprovements (1/3), and yet others (1/3) havelarger types of field expansions (Mueller et al.,2008; Romano et al., 2008; Sabel et al., 2004; Sabeland Kasten, 2000).

The effects of VRT were confirmed by othersas well. Romano et al. (2008), for example, car-ried out a clinical observational study and foundimprovements which were even superior to ourprevious studies. However, while in our trials,hemianopics were included irrespective of theirvisual defect characteristics, Romano recruitedpatients that had clearly identifiable ARV beforetherapy, which increased the likelihood ofimprovement. This points toward a special roleof ARVs in the recovery process. While patientswith ARVs respond well to therapy, those devoidof ARVs, that is, with areas of absolute blindnessonly (“sharp” visual field borders), do not benefitas much. Therefore, when the criterion of trainingsuccess is “improvements in the field of absoluteblindness only” (ignoring improvements inARVs) training has no effects (Reinhard et al.,2005; Roth et al., 2009).

Yet others used different forms of visual fieldborder training (Schmielau and Wong, 2007) andfound reliable improvements. Such improvementsare, however, limited: when a second 6-monthstraining period is given to the patients, there areno significant, additional effects detectable, at leastnot when using simple stimulus detections(Mueller et al., 2008). Also Bergsma and van derWildt (2010) trained 11 subjects with cerebralblindness with VRT, confirming a “gradual



Controlgroup

Results Follow-up

Sabel et al. 2010 22 Yes Yes Significantly greater visual field defectreductions in the rtACS group (69.25%) thanin the placebo group (16.93%), decrease ofreaction times in rtACS- but not in placebopatients

Yes

Gall et al. 2011 42 Yes Yes Detection ability increase in the defectivevisual field was significantly larger after rtACS(41.1%) than after sham-stimulation (13.6%)

No

220

shift of the visual field border”which was indepen-dent of the type of stimulus-set used during trainingwhile eye fixation was monitored. Another inter-esting observation was reported by Jung et al.(2008) who stimulated the border region inone group of patients with anterior ischemicoptic neuropathy and the intact region in anothergroup. Here, detection improvements were seenin both.As one would expect, children of different ages

also benefit from vision training. Werth andMoehrenschlager (1999) and Werth (2008)looked at very young children at preschool ages,and Mueller et al. (2008) studied older childrenof school age. In these studies, significant visualfield improvements were noted as well. They ben-efited as much, if not more from the training thanadults, but it is unclear if the training effects atyoung or adolescent age are more pronouncedthan in adulthood or older age. This is anopen issue.Not all experiments found evidence for train-

ing-induced visual field improvements in patientswith brain damage (Balliett et al., 1985; Reinhardet al., 2005), but these studies suffer some meth-odological and interpretative flaws. Balliett et al.(1985), for example, used very small stimuli fortraining, and training time was much shorter (afew weeks only) than those of all other studies(several months). In the study by Reinhard et al.(2005), a visual field expansion could not be con-firmed with a laser scanning ophthalmoscope(SLO), but when the more sensitive high-resolu-tion and standard perimetry methods were used,visual field enlargement could be found in thesame patients (Sabel et al., 2004). A closer analy-sis of the exact visual field topographies indicatedthat SLO measurements were in fact very difficultfor patients to perform, and the detection task ofthe SLO was also not the one which was trained(Sabel et al., 2004). In fact, the SLO chart dis-played ARVs as areas of absolute blindness,suggesting that the SLO is not sufficiently sensi-tive to detect areas of relative loss (for details,see Kasten et al., 2008; Sabel et al., 2004). Yet,

despite their technical and interpretativelimitations, the only two negative studies (Balliettet al., 1985; Reinhard et al., 2005) point us toimportant methodological issues, which havebeen the source of some controversial discussions(Sabel et al., 2004). In summary, the vast majorityof studies found consistently a rather positive out-come of visual training, and they outnumberexperimental studies with null findings by far.

There is also physiological and brain-imagingevidence for training effect. Physiologicalobservations have the advantage of providing amore “objective”means to document vision resto-ration and plasticity after visual field training.Julkunen et al. (2003, 2006), for example,measured VEPs before and after visual trainingof the border region and showed a normalizationof P100 latencies. After therapy, the same patientshowed an increased blood flow in cortical and sub-cortical structures as measured by PET. In a fol-low-up study 3 months after the end of training,the increased cerebral blood flow was restrictedto the occipital lobes (Julkunen et al., 2006).

Raninen et al. (2007) trained with flicker lightor flickering letters twice a week for the periodof 1 year which improved flicker sensitivity inthe blind hemifield although no evidence of visualfield changes were observed in perimetry.Henriksson et al. (2007) found evidence forreorganized visual cortices using both magnetoen-cephalography and fMRI recordings after train-ing. The pattern of change suggests thatstructures surviving the injury had now par-ticipated in the processing of visual information,that is, the training affected not small (residual)areas alone but had an influence on the brain net-work as a whole, that is, other brain regions.

This is in line with Marshall et al. (2008) whotreated six chronic, right hemianopic patients withVRT and applied fMRI while patients wereresponding to stimuli in the trained visual borderzone. The results of the trained region were com-pared with those of the nontrained seeing fieldbefore and after 1 month of VRT. The authorsfound a significant increase in BOLD activity in

221

border zone detections, and this correlated with arelative improvement in response times in theborder zone. An analysis of the BOLD patternsrevealed brain activation changes that were con-sistent with a shift of attention from the non-trained seeing field to the trained border zone.The effect appeared to have been mediated bythe anterior cingulate and dorsolateral frontalcortex in conjunction with other higher-ordervisual areas in the occipitotemporal and middletemporal regions.

In summary, training of the visual field borderregion does not only result in improvedparameters of vision (such as light detection inperimetry), but it also leads to increased neuronalactivation in wider regions of neuronal networks.Because the intact hemisphere also seems to con-tribute to recovery, vision restoration appears tobe the result of both local and global influences(see discussion below).

Training alternative pathways (blindsight) Someinvestigators have repeatedly trained deep in theblind field with the goal to enhance “blindsight-like” responses. Similar to visual field bordertraining, they found improvements in visual detec-tion performance (Chokron et al., 2008; Sahraieet al., 2006). The most famous blindsight case ispatient GY (Weiskrantz, 1996, 2009; Weiskrantzet al., 1974) who was trained (by virtue of repeatedtesting) over many years and showed someremarkable improvements throughout this time(see also Chokron et al., 2008; Stoerig, 2008).

Sahraie et al. (2006) asked a group of 12 corti-cally blind patients to discriminate simple gratingstimuli for a 3-month training period. Repeatedstimulation inside the blind visual field (and notonly at the border zone, as in VRT) resulted inimprovements deep in the field defect. ButSahraie noted (personal communication) that itis important to start first with the stimulation ofthe border region. In this kind of blindsight train-ing it is apparently necessary to costimulate theborder region in a way that patients are able to

see some portion of the visual stimulus at thebeginning of the training, similar to “prompting”during behavioral shaping. This may also explainwhy others failed to improve visual fields: theyused a simple flickering stimulus which was pres-ented deep in the blind field, ignoring or avoidingARVs (Roth et al., 2009). The need to stimulatethe border region in early training phases makesit difficult to clearly separate an “alternative path-way” (blindsight)-training from the classic vision-restoration training. Perhaps ARVs are initiallyneeded for some prompting, an issue requiringfurther study.

Other investigators have studied the effects ofvision training using slightly different trainingparadigms. Chokron et al. (2008) treated ninepatients with unilateral occipital damage for 22weeks using several blindsight-like forced-choicevisual tasks: pointing to visual targets, letter rec-ognition, visual comparison between the twohemifields, target localization, and letter identifi-cation. An improvement was found in all behav-ioral tasks for all patients and visual fieldenlargements of the contralesional visual fieldfor all except one patient. Huxlin et al. trainedboth animals (Huxlin and Pasternak, 2004) andpatients with brain lesions (Huxlin et al., 2009)to perform a movement detection task. Thisbehavioral paradigm stimulated preferentiallyextrastriate pathways that directly innervate V5via the LGN of the thalamus or through the tec-tal/pulvinar route with an array of moving dots.They found that in animals or patients with V1lesions, movement perception could be improved.Das and Huxlin (2010) report brain activationchanges after such a visual training task in a singlesubject with cortical blindness. Before training,they found widespread hyperactivation inV1/V2, V3, and hMTþ of the intact hemisphere,with no measureable activity on the damagedside. However, after intensive global directiondiscrimination training of the blind field (involv-ing as many as 30.000 trials), the hyperactivationof the intact hemisphere was reduced toward

222

control levels while a recovered activation patternwas seen in regions of on the lesioned side,including perilesional tissue (V1/V2) and V3aand hMTþ confirmed the behavioral studies(Huxlin et al., 2009).Jobke et al. (2009) used a combined striate/

extrastriate training approach. Here, visual stimuliwere presented to the border region using classicVRT, while simultaneously stimulating deep inthe blind field with a moving spiral. The aim of this“extrastriate-VRT” (eVRT) was to create a maxi-mal behavioral stimulation of both the residualstructures (ARVs) in the border region plus a stim-ulation of the entire blind field sector to activateextrastriate (blindsight) pathways. Whereasstandard VRT significantly improved stimulusdetection by 2.9%, eVRT patients improved by5.8%, doubling the extent of vision restoration.This confirms the hypothesis that extrastriatepathways, bypassing the damaged visual cortex,can be recruited to contribute to vision restoration.While visual border stimulation and blindsight-

training are different in principle, in practiceresidual regions (“islands of residual vision”within the blind field or border zones betweenintact and blind field) are probably trainedtogether with the alternative pathways in moststudies. Just as in saccadic eye-movement train-ing, it is difficult to fully avoid ARV stimulationwhen presenting visual stimuli to patients withvisual field defects in blindsight paradigms. Like-wise, when attempting to train only the borderregions alone, a certain proportion of stimuli(about 20%) are located in the blind field, leadingto a “mini-blindsight”-training, that is, uninten-tionally also stimulating the extrastriate pathwaysin the blind field. Likewise, when aiming at theblind field only, it can hardly be avoided to alsoexcite residual tissue.

Training amblyopia Amblyopia is another visualdisorder where research of perceptual learning(training) has contributed to our understanding ofresidual vision. Amblyopia refers to a unilateral

or bilateral decrease of vision caused by abnormalbinocular visual experience during the “criticalperiod” early in life (Levi and Carkeet, 1993). Itleads to serious deficits in parameters of spatialvision such as impairments in visual acuity (VA),contrast sensitivity, vernier acuity, spatial distor-tion, spatial interactions, or contour detection (forreviews, see Hess et al., 1990; Levi and Carkeet,1993). On a physiological level, amblyopia isthought to be caused by alterations in orientation-selective neurons and their interactions in theprimary visual cortex (Polat, 1999).

The standard amblyopia therapy in children isto use an eye patch of the normal eye which for-ces the brain to use the visual input from the wea-ker (amblyopic) eye (Li et al., 2005). It has been along-held notion that this approach is effectiveonly when applied up to the critical age of 8–9years. Therefore, any recovery was seen just asan “extension of normal development,” not aninstance of vision restoration. But even in adultswith amblyopia, recovery of visual functions canbe achieved with occlusion therapy (Wick et al.,1992) and it also has been noted spontaneouslyafter the loss of vision in the good eye (El Mallahet al., 2000). In fact, stimulating the amblyopiceye by repetitive practice can induce plasticity inadults, effectively improving visual functions(Fronius et al., 2005, 2006; Levi and Polat, 1996;Levi et al., 1997; Polat et al., 2004).

For example, Polat et al. (2004) described avisual-training procedure specifically designed totrain the abnormal lateral interactions by probingspatial interactions with flanker tasks. Trainingconsisted of a Gabor patch detection task. VAimproved by 78% above baseline with theimprovement being greater in patients with lowerinitial acuity and improvements in contrast sensi-tivity at all spatial frequencies and in binocularfunctions. The authors pointed out that long-last-ing effects are typical for perceptual learning andthat it is a sign that “the high spatial frequenciesare used after the treatment in daily tasks andthus are naturally practiced” (Polat, 2008).

223

An interesting observation was the transfer ofthese improvements to other tasks. Though treat-ment was monocular, targeting the lateralinteractions of the amblyopic eye, led to a trans-fer of improvement to other, unrelated functionssuch as VA and binocular functions. In contrastto perceptual learning, where improvement isusually specific to the trained task (Fahle, 2005),the transfer of functions in amblyopic patientsshows that there are nonspecific elementsinvolved in the vision restoration process. It wasproposed that practice restored normal balancebetween excitation and inhibition (Mizobe et al.,2001; Polat, 1999; Polat and Sagi, 2006; Polatet al., 1997). In summary, training (practice) ofvisual functions is currently the most widely usedmethod to alter visual system plasticity andinduce vision restoration.

Compensatory (eye movement) training Anothertraining method for hemianopia is saccadic explo-ration training. As Das and Huxlin (2010)recently summarized, there is some evidence onhow patients with cortical blindness attempt spon-taneously to compensate their deficit by eyemovements toward the hemianopic field. Basedon this observation, some authors argue thattraining such eye movements would actually helppatients increase visual orientation (though it usu-ally seems not to enlarge visual fields). We do notdiscuss this approach in any detail here, as train-ing of eye-movement behavior does not aim atvision restoration but at field of view enlargementso that patients utilize the intact visual fieldsectors more (for review, see Kerkhoff andSchindler, 2000; Kerkhoff et al., 1992a,b, 1994).Also, we do not believe that training patients tomove their eyes around more vigorously has along-lasting benefit because (i) whenever thepatient looks to the right he misses the left, and(ii) more eye movements means greater effortfor integration of moving images. Still, it is inter-esting to note that patients performing saccadictraining also experience “unintended” visual field

enlargements (Kerkhoff et al., 1992a,b, 1994)which is not really surprising because these typesof trainings never specifically avoided the simulta-neous stimulation of the border regions whereresidual structures are present. Actually, a recentstudy found that eye movement training had nogreater effects than attention training alone (Laneet al. 2010). This suggest that eye movementtraining may actually enhance restoration andnot only compensation.

Activating residual vision by electrical currentstimulation

Invasive current stimulation methods

The attempt to restore visual circuitry by artificialmeans with invasive electrical stimulation has beenaround for almost 100 years. Here, the goal was tostimulate optic nerve or visual cortex by invasivecurrent stimulation methods to replace or augmentlost visual input by artificial electrical signals. His-torically, the first experiment of electrical stimula-tion to excite the visual system was reported byFoerster (1929).He stimulated visual cortex to pro-duce phosphene perceptions and found that theirappearance depended on where the cortex wasstimulated. These findings formed the basis of theconcept of the visual prosthesis, where local electri-cal stimulation in human visual cortex was used toexcite phosphenes to help facilitate visual percep-tion. Chronic stimulation was later achieved byelectrodes which were implanted directly into cor-tex (Brindley and Lewin, 1968; Brindley andRushton, 1977; Brindley et al., 1972; Dobelleet al., 1974, 1976; Pollen, 1977). But it turned outthat such cortical stimulation would be only of lim-ited clinical use: the resolution was not only toolow, but it also carried a high risk of inducingseizures in patients.

Later attempts of applying low current micro-stimulation of visual cortex achieved a better res-olution and improved safety, although this

224

approach has never gone beyond the experimen-tal stage. Here, it was of interest if visually per-ceived phosphenes are useful to create spatialpatterns of sufficiently high resolution such thatsubjects would recognize objects in the environ-ment, to check if perception was stable formonths or years, and to determine how a blindperson with very old visual cortex lesions, whohad become accustomed to the blindness, wouldrespond to electrical stimulation (Bak et al.,1990; Schmidt et al., 1996). In animalexperiments, electrically evoked responses ofvisual cortex were recorded during electrical stim-ulation of the optic nerves (Bartley and Ball,1969; Malis and Kruger, 1956). Intact rabbit opticnerves were stimulated by needle electrodesimplanted in the optic disc and electrically evokedpotentials (EEPs) could be recorded in the pri-mary visual cortex (Sakaguchi et al., 2004).More recently, optic nerves were stimulated by

an invasive method in the clinical setting bySakaguchi et al. (2009) using a chronically(6 months) implanted, direct optic nerve elec-trode in a single blind patient with retinitispigmentosa. Visual sensations were elicited byelectrical stimulation through each electrode. Thistype of study provided the basis for the mostrecent work on retinal implants which is discussedin Chapter 1.There is also an early Russian tradition of

using invasive electrical stimulation approachesto treat vision loss. Here, multiple deep brainmicroelectrodes were used for subcorticographyand diagnostic stimulation for the investigationof extrapyramidal movement disorders, centralpain, epilepsy, and obsessive–compulsive dis-orders (Bechtereva et al., 1972). This initial workin the field of stereotaxic neurology was laterextended to the stimulation of damaged opticnerves using implanted electrodes with the goalto induce recovery of vision (Bechtereva et al.,1985). They found significant vision recoveryafter 3–4 weeks and this recovery remained stablefor over 2 years.

From our own studies, we know that visual cor-tex remains responsive to create visual perceptseven in cases of congenital blindness: when V1is stimulated by TMS in congenitally blindpatients, phosphenes are still generated inretinotopic order (Gothe et al., 2002). It is thisresidual processing capacity that provides ananchor for enhancing visual functions in the blind.

Noninvasive current stimulation methods

In contrast to invasive approaches, noninvasiveapproaches are aimed at influencing brain physi-ology on a network level and this, in turn, mightaffect sensitization of deafferented regions or syn-chronization (entrainment) of neuronal networkfiring with long-lasting (plasticity) changes(so-called aftereffects, see Zaehle et al., 2010).These methods do not aim at “replacing” the lostretinal cells or neuronal circuitry or stimulatingbrain nuclei locally which is what retina or brainimplants try to achieve.

The work on noninvasive electrical currentstimulation in the visual system was first devel-oped in Russia, where Bechtereva's started offwith invasive methods using specific stimulationprotocols (see above). These protocols were sub-sequently applied also noninvasively in patientswith visual system damage (Chibisova et al.,2001; Fedorov et al., 2005). Here, electrodes wereattached to the eye orbit and repetitive,transorbital, alternating current stimulation(rtACS) was applied. In a large clinical observa-tional study of 446 patients with optic nerve dam-age, they measured visual fields before and after10 days of rtACS treatment (Fedorov et al.,2010). rtACS led to significant VA improvementsand visual field enlargements. On average, visualfield sizes improved by up to 9% over baseline.Also, VA significantly increased in both eyes.

In a subsequent double-blind and placebo-con-trolled clinical trial, optic nerve patients were ran-domly assigned to an rtACS or a sham group

225

(Sabel et al., 2010). The treatment was given dailyfor 20–40 min for 10 days (EBS TechnologiesGmbH, Kleinmachnow, Germany). In the rtACSgroup, significant vision improvements were seenin detection accuracy evident as a shrinkage ofthe scotoma by >40% change from baseline,reaction time (�19.63 ms), static near-thresholdperimetry, and VA (Fig. 5). The improvementsof visual functioning in the rtACS group were sta-ble at a 2-month treatment-free follow-up, andthey were associated with improvement in thepatient's quality of life as assessed by standardquestionnaires. Thus, noninvasive current stimu-lation using rtACS can be used to reduce visual

field defects in patients with long-term opticnerve lesions.

Electroencephalogram (EEG) power-spectraanalysis also showed significantly increasedalpha-activity, especially in occipital sites follow-ing rtACS (data not published, see Fig. 6). Inview of these findings, we proposed that rtACSleads to increased neuronal network synchroniza-tion which is substantiated by lasting bilateral syn-chronous waves of alpha- and theta-ranges incentral and occipital brain areas. This “synchroni-zation hypothesis” assumes that by firing “artifi-cial” electrical trains of impulses atpredetermined frequencies to the brain, neuronal

100(c) (d)

(a)

(b)

69.25**

After rtACS

Baseline

16.93*

rtACS-group (n = 12)

Visual field improvement after repetitive transorbitalalternating current stimulation

Sham-group (n = 10)80

60

40

Red

uct

ion

of

visu

alfi

eld

def

ect

(%)

20

0

3

3

3

2

2

2

1

1

14

44

Fig. 5. Visual field dynamics after alternating current stimulation. Patients with optic nerve damage were treated with repetitive,transorbital, noninvasive brain stimulation (rtACS, EBS Technologies GmbH, Kleinmachnow, Germany). (a) The montages ofthe electrodes which were placed on the skin around the eye ball. (b and d) The visual field charts before and after 10 days ofrtACS in a single case with traumatic optic neuropathy (Gall et al., 2010b, for explanation of charts, see Fig. 2). Asdemonstrated by the brightening of the chart, the patient improved from 3% detection performance to 23%. The area ofimprovement was located in the lower left quadrant which already had some minimal residual vision even before therapy. (c)The group results of a double blind, randomized, placebo-controlled study (unpublished).

226

networks are forced to propagate synchronous fir-ing which, when repeated many times, induces a“learned synchronization response (LSR)” in thedamaged pathways. This idea of LSR is compati-ble with the observation that synchronizationcan be entrained by external, transcranial pulsedstimulations and such alpha entrainment hasalready been observed in normal subjects (Zaehle

et al., 2010). As a consequence of this increasedsynchronization, the injured visual system reactsto the reduced and unchanged input in a moresensitive manner (supersensitivity), similar towhat the brain does on its own during the naturalor training-induced recovery phase where sponta-neous visual phosphenes are seen (Poggel et al.,2007; Tan and Sabel, 2006; Tan et al., 2006).

Pre

(a) (b)

Power spectra changes after alternating current stimulation

F7 F3

Fp110

–10–5

*

**

* *

**

*

*

**

*

*

*

*

*

*

*

05 Fp2

Fz F4 F8

FC6FC2FC1FC5

T7 C3 Cz C4 T8

CP6CP2CP1CP5

P7 P3 Pz P4 P8

O2O1

11,5

11,5

13

30,4

-7,4

-10,9

-6,1

-8,6-10

-10,3

-10,9

10,5

-15-15

-11,7-8,1 9,5

-5,8

Post

Alpha power spectra, mV20 95

Alpha activity

Slow waves activity

Fig. 6. rtACS and EEG power spectra changes. When patients with partial optic nerve lesions are stimulated by noninvasive,alternating currents (rtACS), this leads to lasting EEG power spectra changes. (a) Alpha activation in the brain of a singlepatient before and 24 h after a 10-day rtACS treatment. Alpha activity was highest in posterior brain region before treatment,where the visual cortex is located. After 10 days, alpha power increased across the brain, extending more anteriorally. (b)Results of a clinical trial shows average EEG changes in a group of optic nerve patients. The bars show the power of alpha andslow wave activity in different brain regions. Stars indicate significant changes. The percentage change were 11% and 30% ofalpha power at occipital sites (O1 and O2), after rtACS while alpha activity increased slow waves decreased in different brainregions, where primary visual cortex is located. This was not seen in a sham group. These EEG power changes are indicative ofan increased synchronization state of the brain which outlasts the stimulation period.

227

Here, one can think of cortical plasticity as servingthe role of an “amplifier” that increases the signalabove noise in an area with reduced visual input.

There are other studies using noninvasivevisual system stimulation, particular with trans-cranial direct current stimulation (tDCS)protocols: in normal subjects, tDCS induceschanges in phosphene thresholds and excitability(plasticity) of the human primary visual cortex(Antal et al., 2003), affecting different visual per-ception phenomena (Antal et al., 2006, 2008;Chaieb et al., 2008).

The only other alternating current stimulationstudy is one from a Japanese group (Fujikadoet al., 2006) who applied transcorneal electricalstimulation (TES) in patients with ischemic opticneuropathy. TES was applied only once for30 min at 600–800 mA with a frequency of 20 Hzand this led to improvements in VA in six of eighttreated patients. Due to the small sample, a defin-itive conclusion about this approach is still pend-ing. Also, Inomata et al. (2007) studied TES ofthe retina to treat longstanding retinal arteryocclusion. Here, TES (20 Hz biphasic pulses,30 min, up to 1100 mA) was delivered by a bipolarcontact lens electrode once a month for 3 months.VA was found to have improved in two cases, andthe visual fields were improved in all three cases.Improvements in the electroretinogram indicatesome recovery of function distal to RGCs whichmay explain the visual field improvements.

When viewed together, noninvasive currentapplications can (i) provoke visual percepts(phosphenes) in visual cortex, (ii) lead to excit-ability changes in visual cortex and other brainstructures, and (iii) improve visual functions afterdamage to the optic nerve showing some thera-peutic efficacy. This is quite similar to what isseen after visual training (Fig. 7).

Vision restoration, subjective vision, and activitiesof daily life

Improvement of psychophysical parameters orplasticity of RF changes may be of great interest

to scientists, but unless vision restoration is shownto be clinically relevant, contributing to a higherquality of life, clinicians will not pay attentionand patients will not become aware of this newvision restoration option nor use it.

Obviously, vision loss and blindness have amuch feared negative impact on functionalabilities and quality of life. In patients where thevisual field loss is caused by cerebral damage,the reduction of quality-of-life domains is mainlydue to problems in reading, driving, visual clarity,and peripheral vision (Gall et al., 2009, 2010a,c).The status of vision-related quality of life is some-what dependent on the size of visual field lossafter damage to the post-chiasmatic (Gall et al.,2008; Papageorgiou et al., 2007) or prechiasmaticpathway (Cole et al., 2000). These impairmentsare typically assessed by perimetry and VA tests,but this type of evaluation may fail to assess cer-tain aspects of visual disability that are identifiedby visually impaired persons as being importantfor their daily well-being (see below). The opti-mal approach to measure quality of life in visionresearch is therefore to measure both vision-related and health-related quality of life (Frankeand Gall, 2008).

Subjective improvements after visual bordertraining

As discussed above, different types of VRTs canimprove stimulus detection in patients withpostchiasmatic and optic nerve lesions (Julkunenet al., 2003; Kasten et al., 1998a,b; Sabel et al.,2004). Here, about two-third of the patientsreported subjective improvements as measuredin post-training interviews (Mueller et al., 2003)or by analysis of pre- and post-training drawingsof subjective visual field sizes (Poggel et al.,2008). Other studies have developed their ownmethods and confirmed subjective improvements(Chokron et al., 2008; Julkunen et al., 2003; Sabelet al., 2004). Everyday life activities were alsorecorded in hemianopic patients by structured

228

post-training interviews in a larger sample(n¼69) (Mueller et al., 2003). Here, the percent-age of patients reporting training-induced subjec-tive improvements were as follows: reading(43.5%), ability to avoid collisions (31.9%), gen-eral vision improvement (47.8%), ability to per-form hobby activities (29%), and confidence inmobility (75.4%). Objective improvements ofvisual field parameters correlated significantlywith the number of named activities of daily livingcategories, but not all patients who reported sub-jective improvements also showed objectiveimprovements in perimetry results, that is, therewas a certain number of cases with a “mismatch”(see below).

To try getting a better handle on subjectivevision, we recently adopted the National Eye Insti-tute-Visual Functioning Questionnaire (NEI-VFQ) as a standardized instrument to assessvision-related quality of life and found significantimprovements after visual field training inhemianopic patients (Gall et al., 2008) which werealso correlated with objective perimetry results.Given that questionnaires are sufficiently sensitiveto detect VFI, standardized questionnaires ofhealth- and especially vision-related quality oflife should be used on a regular basis in futurerehabilitation studies (Bouwmeester et al., 2007).This will enhance our understanding of theclinical relevance of functional improvements

00

5

10

15

20

No

. of

pat

ien

ts

25

30 Mean change afterrtACS (10 days)

39.6%

Visual field size improvements after optic nerve damage

Mean change afterbehavioral training(VRT, 6 months)

34.7%

15 30 45 60 75 90 120 150

Relative improvement of detection accuracy (%)

0 10 20 30 40 50 60 70 80 90 100 120 140

Fig. 7. Vision restoration after optic nerve damage: rtACS treatment versus behavioral training. To compare the extent of recoveryfrom optic nerve damage after rtACS with vision restoration training (VRT), we plotted the number of patients versus the differentimprovement levels (in percent change over baseline). As the figure demonstrates, 10 days of rtACS resulted in similar activation ofresidual vision (39.6% detection improvement over baseline) as 6 months of visual training (34.7% improvement). The data weretaken from different studies (rtACS: Fedorov et al., 2010; VRT: Kasten et al., 1998b) but plotted on the same scale to allowcomparison.

229

and standardized methods can also be more easilycompared between laboratories.

Subjective improvements after noninvasivecurrent stimulation

One may argue that patients having undergonea long and laborious training for many monthsmay be biased to report subjective visualimprovements after such a substantial effort andtime commitment. We therefore used a non-training type therapy, rtACS, which might be lessprone to such artifacts. We have measured sub-jective visual functioning and vision-related qual-ity of life before and after rtACS and assessedself-estimated visual and health-related qualityof life (Gall et al., 2011). rtACS led to partial res-toration of visual fields which was accompaniedby improvements of vision-related quality of life(NEI-VFQ) and health-related quality of life(Short Form Health Survey, SF-36). Some, butnot all, NEI-VFQ scales were sensitive toimprovements in visual field size after rtACS,and particularly, the subscale “general vision”improved to a clinically relevant extent in thertACS group. The improvements were dependenton the magnitude of the visual field exp-ansion: rtACS-treated patients with detectionimprovements >20% had a significantly greaterincrease in NEI-VFQ scores than patients withsmaller detection improvements (<20%). Thus,rtACS treatment is capable of modifying the adultvisual system in a noninvasive manner and this isof subjective, functional relevance to the patients’everyday life.

It is interesting to note that only some NEI-VFQ scales were sensitive to visual fieldexpansions after visual training or rtACS. In anyevent, vision restoration studies ought to includeassessments of vision-related quality of life, ameaningful and valuable complement to objectivevisual field data that better reflects on thepatient's individual self-perceived situation.Because the correlation of both is modest at best,

these assessments represent different aspects ofvision. One reason why this relationship betweensubjective and objective visual measures is onlysmall to moderate is the mismatch problem, anissue that adds complexity to the discussion ofvision restoration (see section “The mismatchproblem”). In any event, a definitive advantageof using questionnaires such as NEI-VFQ is thatthey help to weigh the risk (ratio of effort/cost)and benefits of interventions.

The mismatch problem

Visual field impairments are typically assessed byperimetry. However, perimetry was not designedto assess vision in everyday life, and the detectionof small dots presented on ambient background isnot a typical real life event. The visual world ismuchmore complex, comprising different shapes, colors,contours, cluttered scenes, moving objects, etc.In reference to vision restoration, the question isfrequently asked how perimetric improvementsand everyday vision relate. Also, critics claim thatself-perceived training effects may be “only psycho-logical” or “subjective” and therefore “not real.”

We have found that there is only a small tomoderate overlap of subjective vision andperimetric measures. In many patients, perimetricimprovements are associated with subjectiveimprovements, but in other patients, there is seem-ingly a mismatch: subjective improvements can bereported without visual field expansions and, viceversa, visual field expansions may happen withoutbeing subjectively noticed (Mueller et al., 2003;Fig. 4). Also Chokron et al. (2008) described apatient who experienced a progression of subjec-tive improvement after vision training despite lackof improvement in perimetry. Of course, the loca-tion and size of the scotoma has a large influenceon individual subjective vision and this alone canaccount for some of the unexplained variance.For example, a gain of visual field size at or nearfixation has a much greater subjective impact thanperipheral visual field gains (Poggel et al., 2008).

230

But both the low correlations and the mismatchproblem raise another possibility: other factors ofvision might account for this mismatch: (i) the“intact field” also has subtle deficits in visual cog-nition (contour integration deficits), (ii) temporalprocessing (reaction time) is impaired, (iii) spatialresolution (VA) is reduced, and (iv) steady fixa-tion of the eyes and eye-movement control maybe impaired, making the perception of stationaryor moving objects more demanding (Muelleret al., 2003; Paramei and Sabel, 2008; Schadowet al., 2009).In the context of a discussion on residual vision,

the issue of subjective visual improvements is com-plex because everyday life vision is dependent ondifferent factors: (i) visual field size, (ii) exact loca-tion of the field defect (foveal vs. peripheral), (iii)deficits in the “intact” field sector, (iv) temporalprocessing deficits, (v) decline in spatial resolution,and (vi) variable degrees of residual vision at theborder zone or deep in the blind field (with uncon-scious elements of vision (blindsight). Further, (vii)fixation accuracy and (viii) eye movements arepart of the subjective vision equation.Thus, mismatch cases, where subjective vision

improves while the visual field size remainsunchanged, cannot disprove vision restoration asbeing “purely psychological.” We rather proposethat functions other than those testedwith perimetryhave improvedaswell. Indeed,VRT speeds up reac-tion time (Kasten and Sabel, 1995; Kasten et al.,1998b; Mueller et al., 2003), increases VA (e.g.,Kasten et al., 1998b), and improves fixation accuracy(Kasten et al., 1998b). Just as subjective visualimpairments are amultifactorial and rather complexaffair, so is the subjective improvement associatedwith vision restoration (Poggel et al., 2008).

Alternative explanations of vision restoration

The claim that vision restoration is possible at allafter lesions in the adult brain is shared by manyscientists (see below), but it has also attractedsome opposition. Although most critics have not

actually studied vision restoration experimentally,their theoretical arguments are based on circum-stantial evidences but nevertheless raised consid-erable debate. Yet, this discussion is valuable asit directs our attention to possible alternativeexplanations which need to be carefully consid-ered, particularly related to the following issues.

Vision restoration is just normal learning

Some sceptics have argued that vision is just aneffect of perceptual learning and that there maybe no true restoration of vision. We concur withthe argument and believe that perceptual learningactually is an important element when the braintries to repair the damage. To the best of ourknowledge, no author studying vision restorationhas claimed that restoration requires pathology-induced repair mechanism(s). In fact, just as innormal perceptual learning—which requiresmany repetitions (Fahle and Poggio, 2002) inmassed practice sessions (see above)—vision res-toration is not easily accomplished either. It alsorequires many stimulus presentations, in theorder of 50,000–100,000, which usually takesmonths of laborious work. Here, it is not onlythe intact structure that is involved, but ratherperceptual learning takes place within the par-tially damaged structures (within-systems plastic-ity) or the remaining (even intact) neuronalnetworks (network plasticity).

Is restoration just the result of spontaneousrecovery?

This argument is frequently raised but ignoresthat all vision stimulation procedures such astraining or current stimulation were given topatients with lesions that were many years old(e.g., 6.8 years in Kasten et al., 1998a,b). Becausespontaneous recovery is only rarely seen beyond6 months postlesion (see discussion above), these

231

clinical improvements many years after damagecannot be explained by spontaneous recovery.

Functional improvements are caused byattention changes

Similar to the “its-just-learning” argument, weagree that there is a special role of attention invision restoration. Attention is, in fact, a majorcontributing factor to vision restoration. Bothbehavioral and brain-imaging evidence existsupporting the special role of attention in restora-tion. Just as in normal perceptual learning, atten-tion is a necessary requirement for improvingvisual functions and also for long-term and stablevision restoration after visual system damage.

Is vision restoration an artifact of eyemovements?

This is perhaps the most serious concern wheninterpreting vision restoration studies. The issuewas raised that vision restoration is not due toincreased visual detection (perceptual improve-ment), but that the visual border shift can ratherbe explained by increased eye movements towardthe scotoma after training, leading to an apparent,but not real, shift of the visual field border.

In principle, there are different ways how eyemovements could influence diagnostic testingand only “mimic” a visual field expansion: (i) theeyes could scan more in both directions, to theright or left side; (ii) the eyes could intermittentlyand preferentially saccade toward the visual fieldborder, resulting in an artificial shift of the sco-toma away from fixation; and (iii) the eye positioncould permanently shift toward the hemianopicside, which would require the establishment ofeccentric fixation which patients with centralvision loss, such as AMD patients, regularly do.

First of all, there are some logical problemswith these possibilities. Let us consider the threecases during the post-therapy perimetric assess-ment: (i) firstly, if the eyes would scan more in

both directions, the patient would have as manydetection gains by looking toward the blind sideas detection losses by looking to the other side;(ii) if the patient would intermittently scan towardthe hemianopic side only, then the patient wouldnot only have to move the eyes just prior to theshort stimulus presentation (which cannot be anti-cipated). Doing this while having to pay attentionto the fixation point would be an extremely hardtask. (iii) Stable, eccentric fixation does not occurin hemianopic patients who are able to fixate well(an inclusion criterion in restoration studies); alsothe blind spot remains in its expected place.

Besides these arguments of logic, there aremany experimental indications why the “eye-movement artifact hypothesis” is unreasonable.

1. The nature of the visual field border: If the“eye-movement artifact hypothesis” was cor-rect, one would expect that the training-inducedvisual field border shifts as a whole to one side.However, the border shift dynamics are rathervariable: some patients show a shift of the entireborder to the hemianopic side, while othersshow a shift only in one sector of the border(Fig. 8a). Also, in patients with glaucoma, thevisual field borders move in a ring-like centrifu-gal direction toward the periphery (Gudlinet al., 2008) which is incompatible with movingeyes preferentially toward one side. Thus, thelocal border shift and the centropedal bordershift dynamics are incompatible with the eye-movement theory.

2. Blind spot position: If patients would intermit-tently or continuously move their eyes towardthe scotoma, the position of the blind spotwould shift, which is not what is seen (Kastenet al., 2006).

3. Measuring eye movements: Actualmeasurements of the eye positions with aneye tracker before versus after training arethe most direct way to clarify the role of eyemovements in restoration. We found noincrease but rather a decrease of eye move-ments after VRT (Fig. 8b) (Kasten et al.,

232

2006). There was also no evidence for pre-ferred directions of the eye movements beforeor after restoration. Moreover, the eye move-ments were rather small: 95% of the timesthe eyes were positioned �2� around fixationbefore training and 99% after training, thatis, fixation quality actually increased.

4. Eye movement-adjusted retinal charts: Anotherapproach to determine the role of eye move-ments is to adjust visual field charts as a func-tion of eye movements. When this is done(Fig. 9), stimulus detections (hits) after training

are observed in areas of the visual field sectorthat previously had been blind.

5. Fixation performance: If eye movements weremore frequent after VRT, then one wouldexpect fixation performance to worsen. Actually,there is no reason to assume that training wouldinduce patients to start moving their eyes aroundmore because the training task requires stablefixation performance. In fact, none of the patientscarrying out training developed eccentric fixation(Reinhard et al., 2005) and fixation performanceactually improved in all of our prior studies.

20

15

10

5

0

−5

−10

−15

−20

−25 −20 −15 −10 −5 0 5 10 15

Vision restoration and eye movements(a)

20 25 −5 0 5 10 15 20 25

20

15

10

5

0

−5

−10

−15

−20

60

%

(b)

50Left Right

PrePost

40

30

20

10

0>−5° >5°−5° −4° −3° −2° −1° 1° 2° 3° 4° 5°

Average visual field border shift (5°)

Fig. 8. Vision restoration and eye movements. Eye movements need to be observed in studies of vision restoration. (a) In a patientwith a complete upper right and incomplete lower right damage before and after vision restoration training (VRT). Visual fieldimprovement occurred mainly in the lower right quadrant shifting the relative border; but the upper visual field border did notchange (the arrows indicate the border position parallel to the vertical midline). If eye movements were responsible for theborder shift, then the entire border would be expected to shift position, not just the lower half. (b) Eye movements can also bedirectly measured before and after VRT. This graph shows the time spent at fixation or to the right or left. A pre- versus post-training comparison did not find any differences. If anything, fixation improved (see Kasten et al., 2006). Thus, eye movementscannot explain visual field border shifts and therefore vision restoration is real.

233

6. Locally induced visual field border shifts:Training residual vision with an attentioncue amplifies restoration precisely in theregion where the cue was positioned (Fig. 10).

This leads to a selective and regionallyrestricted visual field border shift which canalso not be achieved by eye movements.

Eye tracker adjusted visual charts

(a)

100 %

80 %

60 %

40 %

20 %

0 %

Before

After

160

No.

of

stim

uli

140

120

100

80

60

40

20

Pre Pre

**

**

Post

n = 16

PostMissed stimuli Hits

(b)

(c)

–20 –15 –10 –5 0 5 10 15 20

–15

–10

–5

5

10

15

15

10

5

0YY

X

–5

–10

–15

–20 –10 0 10 20

0

(d)15

10

5

0

–5

–10

–15

–20 –10 0 10 20–20 –15 –10 –5 0 5 10 15 20

–15

–10

–5

5

10

15

0

Fig. 9. Eye-tracker adjusted visual charts. Eye movements always occur during perimetric assessment, even when patients areinstructed to fixate well. To evaluate the role of eye movements in restoration, an eye-tracker adjusted visual field chart wascalculated in which the position of the recording was adjusted to accommodate the position of the eye at the time of stimuluspresentation. Upper graph: The left(a, c) shows HRP charts before and after VRT. On the right, the adjusted charts aredisplayed. Clearly, the improved areas as shown in (c) can also be found when the stimulus positions are adjusted as a functionof the eye position at the time of presentation. Numerous stimulus detections (hits) are now seen on the far right after VRT (d)in the previous area of absolute blindness (shown in (b)). Lower panel shows the average results of a group of patients (n¼16).Detection performance was expressed as number of hits (left) and number of misses (right) inside the previously blind field only.Whereas the number of misses significantly decreased, the number of hits significantly increased.

234

7. Visual field improvements were recently con-firmed with microperimetry, which allows theexclusion of eye movement artifacts (Marshallet al., 2010).

While we acknowledge that the majority of visualstimulus presentations are given when the eye is notexactlyat fixation, there is noevidenceof a changeorinduction of preferred saccades toward the scotomaafter restoration training. Actually, eye movementsare a physiological necessity and they do alwaysoccur. Though eyemovements cannot explain resto-ration, they are always a possible source of error(variability) in visual field diagnosis. Monitoring

their influence therefore helps to control and reducethe variability which increases the validity of visionrestoration measurements. In summary, eye-move-ment artifact cannot rule out the available experi-mental evidence in favor of vision restoration.

Factors influencing vision restoration

To understand mechanisms of restoration and tooptimize outcome, several potential factors haveto be considered: patient demographics, thenature of the disease, and the topography of thespecific visual field defects and transfer effects.

Vision restoration and attention

Acute attention

20�

-20

-20�

-15

-15

-5

–5

0

0

5

5

-5

0

5

10

10

15

15

20-10

-20 -15 -5 0 5 10 15 20-10

-10

-15

10

15

-10

0�

100 %80 %60 %40 %20 %0 %

Fixationpoint

Chronic attention (training)

Fig. 10. Vision restoration and attention. To evaluate the role of attention in vision restoration, hemianopic patients were asked tofocus their attention to a cue in the shape of a square (attentional spotlight) that was positioned on the border region. The left panelshows the immediate effects of such local attention on the visual field. When the cue (square) is placed on the upper visual fieldborder, the number of stimulus detections is increased compared to a comparable square shaped region without attention (lowervisual field). Thus, attention led to residual functions in the previously blind regions (see Poggel et al., 2006). The panels on theright show the effects of daily attention training over the course of 6 months with a cue positioned also on the visual fieldborder. Vision restoration developed precisely inside the region (square) which was activated by the attentional spot light(Poggel et al., 2004). This shows that attention is a key factor in vision restoration.

235

Patient parameters

Age of the patient (at least after early adulthood)has no major influence on vision restoration out-come (Mueller et al., 2007; Zihl and von Cramon,1979, 1985). The activation of residual vision andplasticity is also not gender dependent (Muelleret al., 2007). It is possible that restoration isgreater in children before or at school age(Werth, 2008; Werth and Seelos, 2005), but out-come of children versus adults has never beendirectly compared.

Lesion parameters

Lesion age

Our experience is that lesion age (at least at timesbeyond 6 months) has little, if any, influence ontraining-induced vision restoration. Althoughmost of the spontaneous visual field recoveryoccurs early after the lesion, all visual field resto-ration studies (using training or noninvasive brainstimulation) have treated patients with lesionsolder than 6 months. Having very old lesionswas of no apparent disadvantage for prognosis.Little is known if vision restoration is more effec-tive when applied during the very early spontane-ous recovery phase. Our preliminary studies didnot find any evidence for this and patients tendedto actually do worse if behavioral training startedearlier (Mueller et al., 2006), though this needsfurther study before a conclusion can be reached.

Lesion type

Vision restoration occurs no matter where thelesion is located along the visual system pathway.Contrary to our intuition, more peripheral (reti-nal and optic nerve) lesions tend to have greaterrestoration potential than central lesions of thevisual radiation or visual cortex (Kasten et al.,1998a,b). This is surprising but highlights the

special role of visual cortex in post-lesion plastic-ity. Perhaps “cortical amplification” simply worksbetter when the cortex is not deafferented ordamaged directly.

Visual field defect type

It does not matter whether the visual field defectis a smaller type of scotoma, a quadrantanopia,a hemianopia, or a peripheral, concentric visualfield loss (as in glaucoma). All lesion types mayrespond to treatment, with no major differencebetween any of them. The only known parameterthat matters for restoration, though, is the sizeand topography of ARVs (Guenther et al.,2009). This is in line with the argument that visionplasticity is mediated by residual structures.

Visual field topography

Visual field defects may have areas of absoluteblindness or ARVs (relative defects), wherepatients respond unreliably to visual detectiontasks (Fig. 2). The size of these ARVs, that is,the degree of residual vision, is currently the onlyfactor that has a notable influence on outcome.Though large ARVs are no guarantee thatfunctions will improve after therapy, the size ofthe ARVs is positively correlated with outcome.A detailed analysis of the visual field topographyalso attests to the special role of this factor (seebelow). Here, self-organizing map (SOM) chartanalyses revealed that the vision restoration hotspots are not randomly distributed but they area function of the amount of residual activity inthe immediate surround (Guenther et al., 2009).For more detail, see legend to Fig. 11. In ourexperience, 80% of the visual field locations thatimprove (vision restoration hot spots) are locatedin the ARVs; only 20% are found deep in theblind field (unpublished observation).

Though stimulation of only the field of absoluteblindness has been tried by several authors,

236

Distance toscotoma

Dynamic chart construction

Baseline chart20 20

20−20

10 10

10

0 0

(b)

(c)

(a)

−10 −10

20

−20

10

0

−10

−10

−20

−20 201000

15.2 mm 0 mm 0.6 0.8 0.80.330

0 0

+ + +

0

+ Hot spots0 Cold spots

Neighborhoodactivity

Defect-depth

Quadrantanopia Hemianopia

0 0

0 0 0

−10−20 20100−10−20

Horiz. visual angle [°]

Feature calculation: neighborhood activity

Self-organizing maps (SOM): restoration hot spots

Horiz. visual angle [°] Horiz. visual angle [°]

Ver

tical

vis

ual a

ngle

[°]

Posttraining chart Dynamic chart

+ +

Fig. 11. Factors influencing vision restoration hot spots. To study factors (features) of the visual field defect that influence whether agiven spot of the visual field can recover, “restoration hot spots” (improved vision) and “cold spots” (no change) were determinedas shown in (a): Visual field charts before (left panel) and after vision restoration training (middle panel) are used to calculate thedynamic chart (right panel) which shows the change pre- versus post-VRT (for explanation of charts see Fig. 2). “Hot spots” areindicated by dark square, cold spots by gray squares. (b) One sample feature which was of special interest: “neighborhoodactivity.” A computer-simulation used data mining method of SOMs to examine for each spot of the baseline visual chart ((a),left panel) a value that represents this feature (in this example of a feature, low values represents little activity and high valuesmuch activity in each spots immediate surround/neighborhood). The SOM then calculated to what extent this feature at baselineis able to predict a “hot spot.” This feature represents residual visual activity (indicated by levels of gray) in the immediateneighborhood of a given spot. (c) The results of the SOM-analysis for different such features in 2D SOM charts. For eachfeature, a separate chart was created which was subdivided in a hot spot (þ) and cold spot region (0), separated from each otherby a border line. The gray levels represent how well a given feature (e.g., neighborhood activity) is associated with cold or hotspots. In these SOM charts, white represent tight associations while gray and black represent no association. As the graph shows,the features “neighborhood activity” and “residual activity of the spot itself” (defect depth) are closely associated with the hotspot (þ) region. Other features, such as type of visual field defect (quadrantanopia/hemianopia) or distance to the scotoma arenot associated with the occurrence of hot spots. Thus, an SOM analysis revealed that residual activity within a limited surroundhas a great influence on vision restoration and, in fact, predicted the restoration potential rather well (see Guenther et al., 2009).

237

we question if they tested sufficiently for possibleresidual vision inside the blind field. Namely, anarea that appears completely blind may actuallyshow residual vision when tested with brighterstimuli (Kasten et al., 2008).

Specificity and transfer of training effects

When vision restoration is accomplished by train-ing the question arises if training effects are spe-cific or if they transfer to other functions as well.In the normal brain, improvements in perceptuallearning tasks are rather specific to the featuresthat were trained (spatial frequency, orientation),to the retinal position, or to the eye which wastrained (Gilbert et al., 2001; Karni and Sagi,1991). However, there are also examples of trans-fer (Beard et al., 1995), though only “easy-to-learn” tasks seem to be transferable (Gilbertet al., 2001). The information on transfer in clini-cal cases is still rather ambiguous. In patients withhemianopia, for example, vision training of theborder region, that is, in ARVs, a task involvingthe detection of small dots presented at differentbrightness levels, also improved color detection(Kasten et al., 2001) and VA (Kasten et al.,1998b; Mueller et al., 2007), both of which werenot trained. Also in regained regions of the visualfield, there is not only improved detection of sim-ple light stimuli (which were used for training)but also improvement of VA, critical flickerfusion frequency, and color vision (which wasnot trained) (Bergsma and Van der Wildt, 2008).

Thus, there is no clear conclusion as to thetransferability of training effects. This maydepend on the task and the size and localizationof the lesion or other nonspecific factors (suchas attention and temporal processing). We needto keep in mind, though, that in contrast to nor-mal subjects, patients with brain damage mayhave problems with more general cognitivefunctions such as attention, temporal processing,contour integration, brain synchronization, etc.It is therefore reasonable to assume that a specific

training task may lead to gains in these generalfactors which, in turn, would benefit other visualtasks as well (such as color recognition). In fact,it is not conceivable that any particular, specifictraining task is “specific” in the true sense sincecarrying out a visual task (even if simple) alwaysengages other functions (e.g., visual attention) aswell. It is practically impossible to train singlefeatures alone (such as a contour without a shape,a shape without attention, etc.). As a consequence,stimulation of more general functions (such asattention or brain electrophysiological synchroni-zation) might be beneficial to a specific task or toa variety of tasks. In this context, the observationis of interest that visual improvements occur alsoin regions well outside of the trained region itself(unpublished observations). Thus, while the “spec-ificity” issue is difficult to answer at this point, itseems clear that some generalization always occursbecause any specific training task has also moregeneralized, global effects on visual cognition.

Neurobiological mechanisms of vision restoration

The “minimal residual structure” hypothesis

The minimal residual structure hypothesis (Sabel,1997) states the following: as long as a small, min-imum number of cells survive within the damagedstructure, recovery of function is possible. Thishypothesis needs to be expanded to include thedownstream neuronal networks: it is the totalnumber of fibers of the different pathways surviv-ing the lesion that determines how much informa-tion reaches higher cortical regions. For example,after lesions in the retina or optic nerve, no alter-native routes exist whereby visual informationcan travel to the brain. In such peripheral lesions,the functional loss (and the restoration potential)is at least initially a function of the number of sur-viving cells. After post-chiasmatic lesions, even acomplete lesion, for example, of V1, does not leadto a complete functional impairment: informationcan still travel alternative extrastriate routes to

238

reach higher cortical regions (e.g., V2–V5) via thetectal–pulvinar pathways or direct geniculate–V5fibers. The term minimal residual structure shouldtherefore include both the local structure and allother alternative or upstream structures that con-tribute to visual information processing andrestoration.Although a certain minimal number of residual

cells is critical for vision restoration to occur at all,because of the “network” plasticity the precisenumber of surviving cells in the lesion site is arather poor predictor of restoration (Sautter andSabel, 1993). As Fig. 1 shows, with only about20% of the RGCs, rats reach up to 80% perfor-mance in visual tasks. For a given visual perfor-mance, the questions are as follows: (i) Howmuch primary tissue (number of cells and theirconnections) is left? (ii) Are there other(rerouting) pathways for visual information toreach higher-up brain regions? The smaller theresidual capacities of both, the lower the chancesfor vision restoration.The Pasik and Pasik study (1973) may serve to

illustrate this point: 14 macaque monkeys weretrained in a two-choice task (light vs. no light) fol-lowing bilateral occipital cortex removal. Immedi-ately after the injury, the animals were blind,bumping into objects and falling from platforms,though pupillary reactions and eye movementsappeared intact. After 3 months of recovery time,the monkeys were again able to carry out bright-ness discrimination tasks and reach for visualstimuli. Concomitant removal of ventrolateralportions of the temporal lobe, posterior portionsof the parahippocampal gyrus, the pulvinar, thesuperior colliculus, or the medial tectum resultedin only a temporary visual defect from which theanimals recovered. But when the lateral pretectalregion was injured as well, which caused a bilat-eral, severe degeneration of the nucleus of theaccessory optic tract, the monkeys were no longerable to relearn the brightness discrimination task.Thus, not only does the visual system have cap-

acities to recover from damage, but more gener-ally speaking, just as Lashley (1939) stated, the

extent of visual dysfunction depends on howmuch of the visual system as a whole is injured(which Lashley termed the “principle of massaction”). While this somewhat holistic interpreta-tion of visual system function seems perhaps a bitsimplistic, yet from today's point of view it pointsto the great potential that just a small amount ofresidual tissue may have.

Apparently, only a surprisingly small number ofneurons is required for functional restoration totake place and this is also known in other brain sys-tems. In studies of patients with Parkinson's dis-ease, for example, a loss of dopamine cells greaterthan 70% has to occur before patients start evennoticing symptoms, that is, the brain is able to com-pensate up to 70% loss rather well. Also, recoveryof spinal cord lesions is a rule when lesions are notcomplete, that is, leaving behind small remnants ofresidual tissue, in the order of 5–20%, which is sim-ilar to the 80% vision recovery in rats with only20% RGCs (Fig. 1).

Given this tremendous dynamics of the brain, itis perhaps not surprising that the number of sur-viving neurons correlates rather poorly with func-tional outcome. First, the plasticity of the areas ofprimary damage introduces variability to behav-ioral performance, and second, both downstreamneuronal nuclei and alternative pathways contrib-ute in a significant way to recovery and reorgani-zation (amplification) of vision. This markedlydilutes the structural–functional correlation andis a source of variability. The good news is thatit gives more therapeutic wiggle room.

Within-systems plasticity

In order to get a better understanding of themechanisms of vision restoration, we need to dif-ferentiate between plasticity of residual tissue inthe damaged structure itself—within-systems plas-ticity - and the responses of all other brain regionslocated downstream, the “network plasticity”.

Within-systems plasticity relates to changes inthe remnants of the damaged structure itself

239

(see Sabel, 1997). This kind of plasticity involveslocal cellular changes—such as activation (or reac-tivation) of surviving cells (Prilloff et al., 2007)or enhancement of their synaptic transmission(synaptic plasticity). Within-systems plasticity canbest be studied in animal experiments where anincomplete (partial) lesion can be studied at thecellular level, such as in optic nerve preparations.It can also be investigated in areas surroundingthe injured visual cortex (Imbrosci et al., 2010;Wood et al., 1974) or spared tissue remnants ofinjured superior colliculus (Stein and Weinberg,1978). The key question here is this: “How manyneurons need to survive and what changes do theyundergo so that restoration of vision becomespossible?”

We studied this issue by creating partial crushlesions of the ONC in adult rats. Here, only about10–20% of RGCs are sufficient for vision recov-ery to occur (Sautter and Sabel, 1993). That thisrather small number of cells sustain function con-firms observations by Lashley (1939) whoestimated that as little as one-sixtieth of the neo-cortex is sufficient for visual discrimination. Chow(1968) and Galambos et al. (1967) found 2–3% ofthe optic tract fibers to the LGN to be sufficientfor “normal vision” (which appears to be an over-statement). Chow and Stewart's figure is about28% (Chow and Stewart, 1972) much larger thanthe figure given by Hubel and Wiesel (1970) whoobserved that with as little as 1% of the cellsresponsive, limited recovery of form deprivationis possible. The finding of RGC hyperactivationafter partial optic nerve damage supports the con-cept of within-systems plasticity: a delayed, mod-erate calcium hyperactivation of surviving RGCswas associated with greater responsiveness ofthe cells to visual stimuli (Prilloff et al., 2007).

Network plasticity

Network plasticity refers to all changes in areasnot directly affected by the injury but sufferingfrom “primary” and/or “secondary” (functional)

deafferentation. It includes also other,nondeafferented regions involved in the post-lesion response. For example, partial retinal oroptic nerve damage will lead to primarydeafferentation both in the superior colliculus,the main retinofugal target in the rat and in theLGN of the thalamus, the main retinofugal targetin humans. Visual cortex would then be theregion of secondary deafferentation.

If network plasticity exists, one would predictthat damaging all nuclei of the network shouldreduce the chance of recovery toward zero if noother pathways can drive the function. Indeed,combined, simultaneous lesions of all alternativepathways result in more severe deficits and recov-ery is precluded. For example, there is less recov-ery in cats with combined visual cortex andsuprasylvian gyrus lesions (Wood et al., 1974),when creating combined lesions of different visualareas simultaneously, there may still be visualsparing (in luminous flux). But when thesuprachiasmatic nucleus was also damaged, the lastvisual structure still available, there was no restora-tion whatsoever (Pasik and Pasik, 1973).

Thus, a loss of all visual structures clearly pre-cludes restoration (which is not at all surprising).Fortunately, in the clinical world, complete visualsystem lesions are extremely rare (other thancomplete eye or optic nerve damage). As a conse-quence, even in patients considered to be “legallyblind,” there is almost always some degree ofresidual vision and therefore some restorationpotential. In lesions acquired later in life, com-plete (and not only apparent) blindness is anextremely rare exception and at least some resid-ual vision is usually present.

Receptive field plasticity in deafferentedbrain structures

Cell loss in one structure of the brain destroystheir projection fibers to remote areas. If thesefibers are excitatory, deafferentation depressionin remote regions takes place, a phenomenon

240

also known as “diaschisis” (Von Monakow,1914). If the projection fibers are inhibitory,deafferentation excitation results. In cases ofdeafferentation depression, spontaneous recoverymay be achieved by reactivation of metabolicactivity which happens spontaneously during theearly recovery period, for example, after opticnerve damage in the LGN and visual cortex(Schmitt and Sabel, 1996a,b, 1998). This reactiva-tion may be mediated either by surviving neuronsincreasing their strength to above-normal levels(Prilloff et al., 2007) or by excitability changes inthe deafferentation zone itself (Giannikopoulosand Eysel, 2006). In the computation model ofcortical plasticity, increased neuronal gain in thedeafferented zone has been shown to be crucialfor consistent experimental RF shifts (Younget al., 2007). Whatever the mechanism, the regionof primary deafferentation is key in the restora-tion equation and reorganization of its neuronalnetwork.The classic example of network plasticity in the

visual system is RF reorganization, a fieldpioneered by Eysel (e.g., Eysel and Grüsser,1978). He and others showed RF reorganizationafter retinal lesions with RF shifts up to 5–9� ofvisual angle and up to 10-fold initial increase ofRF size followed by shrinkage to nearly normallevels (Darian-Smith and Gilbert, 1995;Giannikopoulos and Eysel, 2006; Gilbert andWiesel, 1992; Heinen and Skavenski, 1991; Kaaset al., 1990; Waleszczyk et al., 2003). Also, directinjury to visual cortex produces a local RF reorga-nization seen as both increases in RF size but alsoin shift of RF location (Eysel, 1997). RF reorgani-zation also occurs in the surround of the lesion,the “penumbra,” leading to physiological hypo-excitability and more distally, hyperexcitability(Dohle et al., 2009; Eysel, 1997). This RF reorga-nization is mediated by long-range intracorticalhorizontal connections which are either activatedafter deafferentation (Darian-Smith and Gilbert,1995) and which show axonal sprouting(Darian-Smith and Gilbert, 1994).

Lateral influences of cortical interneurons havealso been proposed to underlie the “filling-in phe-nomenon,” that is, the curious observation that aretinal scotoma is subjectively perceived to bemuch smaller than expected (Murakami et al.,1997). In fact, the compensation potential of eventhe normal brain is so great that by filling-in theblind spot escapes conscious detection. In addi-tion, the size of the RF varies considerably inthe normal brain, depending on the brain's syn-chronization state (Wörgötter et al., 1998). Thus,RFs plasticity is dependent on lateral influencesfrom neighboring regions, which can exert eitherinhibitory or excitatory influences.

It is likely that RF plasticity is the mechanismof both normal learning and adaptation of thevisual system to damage. Because lateralinteractions in visual cortex are involved in per-ceptual learning (Gilbert, 1998; Gilbert et al.,2001) and RF plasticity (Gilbert and Wiesel,1992), the possibility exists that lateral influencesare also involved in vision restoration followingbehavioral training or electrical stimulation.Recent findings by Raemaekers et al. (2011) areconsistent with this possibility (further discussedbelow).

If the assumption is true that lateral interactioncontributes to vision restoration, one wouldexpect that vision restoration does not exceedthe boundaries imposed by the lateral extent ofthese interactions. We have studied this questionin visual field charts of hemianopic patients aftera repetitive perceptual learning task (training).We reasoned that if RF plasticity is involved invision restoration similar to that found in cats(Giannikopoulos and Eysel, 2006) or monkeys(Gilbert and Wiesel, 1992), improvements shouldnot be distributed randomly in the visual field.Rather, they should be a function of the distanceof the immediate surround and span a finite dis-tance, that is, their influence is spatially limited.

Visually driven spike activity recovers withina deafferented region up to 3.5 mm from thescotoma border (Das and Gilbert, 1995;

241

Giannikopoulos and Eysel, 2006). Others reporteven larger range of RF shifts (5–6 mm;Waleszczyk et al., 2003). Computer simulationsand physiological recordings from macaque areaMT suggest that dynamic alterations in neuralactivation alone are sufficient to allow large RFchanges (Sober et al., 1997) and perilesion corti-cal activity is a critical factor in reorganization(Eysel et al., 1999). Thus, restoration of vision inpatients (i) may be mediated by areas which arenot completely but only partially damaged, (ii) itmay be influenced by perilesion activity of thecortical surround, and (iii) if reorganization ofRFs is the underlying neuronal substrate, visualfield expansions should be spatially limited.

Based on these considerations, we have hypoth-esized that vision restoration is governed by thesame rules and principles imposed by the spatiallimits of lateral interaction. To test this, we havemeasured in visual field charts of hemianopicpatients the precise topography of changes afterstimulation by first creating dynamic visual fieldcharts and then calculating the differences beforeversus after training. The obtained “dynamiccharts” then permitted the identification of areasof the visual fieldwhere vision restoration occurred(hot spots) and those where it did not (cold spots).Using “SOM”-data mining tools, we then relatedthe location of the restoration hot and cold spotsto certain features in the baseline visual fieldtopography (Guenther et al., 2009). The goal ofthis approach was to uncover possible rules of RFplasticity and to check the influence of lateralinteractions (Fig. 11).

Indeed, when the location of the restorationhot spots was compared to the precise topographyof baseline charts, we found that vision restora-tion follows indeed rules of RF plasticity: restora-tion hot spots were primarily located in areas ofthe visual field that had either a high level of localresidual activity and greater amounts of residualactivity in the immediate spatial 5� surround.The level of global activity (lesion size) or otherparameters (such a type of visual field defect)were of no influence (Guenther et al., 2009).

This observation is confirmed by recent imag-ing studies by Raemaekers et al. (2011). Theyfound direct evidence for RF plasticity: inhemianopic patients participating in VRT RFchanges in visual cortex could be imaged. Thefindings are thus compatible with our ownobservations of a special role of lateralinteractions in vision restoration. The authorsconcluded that small visual field enlargements(such as those at the border region of the visualfield) could be explained by this more “local”RF plasticity, but that massive visual fieldexpansions, which are sometimes observed inpatients, cannot be explained by this mechanism.

Yet, one important question remains: Is RFplasticity good or a bad? Whether RF reorganiza-tion (RF location shift or enlargement) is func-tionally adaptive or maladaptive is not yet clear.Enlarged RFs might facilitate detection, but atthe same time, they might reduce the ability tosee in ambient light or detect objects at higherresolution or more complex objects. Likewise, ashift of the RFs location might be helpful toengage deafferented regions of the brain to par-ticipate in visual processing, but if this is helpfulat all or instead leads to scrambling or noise inregions adjacent to the lesion remains to bedetermined.

There is one phenomenon that nicely illustratesthe ambiguous role of RF plasticity. Dilks et al.(2007) described a patient with a left upperquadrantanopia carrying out detection tasks ofdifferent shapes (squares, circles, triangles).When presented near the lesion in the lower leftquadrant, the subject perceived objects as verti-cally elongated, extending toward and intothe damaged area. The lesion affected “vision-for-perception” tasks as well as visually guidedmotor response (vision-for-action). fMRImeasurements confirmed the hypothesis that thedeprived cortex became responsive to nearby(intact) regions in a retinocentric manner, anissue also related to the filling-in effect. Onemay argue that visual distortions might be mal-adaptive from the point of view of “what is it?,”

242

but they might be adaptive from the point of view“is there something?” Currently, we cannot tell ifcortical reorganization after lesions is a good orbad thing (enhancing perception or distorting is).Clearly, this issue is a critical one in need of fur-ther study.

The role of downstream networks

After considering plasticity of the damaged struc-ture itself and the primary deafferented structure,let us now turn to neuronal networks beyond thedeafferented region.It is reasonable to assume that reorganization

does not stop at the area of primarydeafferentation. It also leads to changes in sec-ondary brain structures. In addition, as we knowfrom post-chiasmatic damage, information flowcan bypass the lesion site, using a detour of alter-native routes to higher cortical regions (see thediscussion on blindsight above), leading to a kindof remote neuronal network response.

The excitation–inhibition balance

From the network point of view, reestablishinghomeostasis, an evolutionary principle, is thekey goal, that is, the proper balancing of excita-tion and inhibition. This issue receives sparseattention in the vision restoration literature. Letus consider, for example, the case of an incom-plete hemianopia caused by an incomplete V1lesion. Here, we have a loss of lateral interactions(presumably horizontal cells) which impairs localinformation. Second, there is the loss of long-range interhemispheric fibers that terminate inthe mirror-symmetric position of the opposite,intact hemisphere, particularly in the region thatcorresponds to the vertical midline. Becauseinterhemispheric fibers are believed to be inhibi-tory (Sprague, 1966), their loss would result in ahyperexcitation of the intact hemisphere with asecondary inhibitory ripple effect by the

reciprocal interhemispheric, inhibitory fibersoriginating from the intact side and terminatingon the damaged side. The final outcome wouldbe a disaster for the damaged hemisphere: addi-tional inhibition of all those regions that werepartially damaged (ARVs). ARVs are probablythe greatest victims of excitation–inhibitiondysbalance.

In the RF microenvironment, the consequencesare several-fold. We expect local inhibitory andover-excitatory changes in the immediate sur-round of the lesion plus a functionally hyperactivestate of the intact hemisphere with a secondaryoverinhibition of the reciprocal interhemisphericinhibitory back-projections. In this scenario, anycells that managed to survive inside the blind orpartially blind field would be inhibited from theopposite (intact) hemisphere (ARV suppression)and this happens irrespective of whether theyare located in the ARVs near the visual borderor in any islands of residual vision. The net out-come of all of this would be as follows: the intacthemisphere ends up with subtle deficits in vision,possibly by being hyperexcitable, and addition-ally, residual tissue on the lesion side issuppressed by overinhibition. If this theory ofimbalance is correct, restoration would be arebalancing act: (i) inhibiting the overexcitedintact tissue and/or (ii) increasing excitability ofthe residual tissue in the region of the lesion.

There are several lines of evidence thatnetwork balance is critical for proper vision.There are (i) subtle deficits in the intact hemi-sphere and (ii) visual hallucinations found dur-ing spontaneous and training-induced visualrecovery which have been interpreted as signsof interhemispheric dysbalance. In addition,rebalancing can restore vision: (iii) restorationof vision can be achieved by additional lesionsin the hemisphere contralateral to the lesion(also called the “Sprague effect”), (iv) corticalreorganization as demonstrated by imaging stud-ies, and (v) the restoration effects of functionalsilencing of the intact side while stimulatingARVs (as in VRT).

243

Subtle deficits in the intact hemisphere The pre-sumably intact visual field in hemianopes is actu-ally impaired. It has difficulties to detectincomplete figures embedded in a noisy back-ground (Paramei and Sabel, 2008; Schadowet al., 2009). For example, three hemianopiapatients had to detect with their intact side ofthe visual field a figure (square) composed ofinterrupted contours created by Gabor patchesembedded in a random patch array (Parameiand Sabel, 2008). Two of the patients had markeddeficits in the response accuracy and reactiontimes and also showed “figure confabulations.”This can be explained by impaired top-downinfluences from higher visual centers and/or lossof proper interhemispheric balance, both of whichimpair the function of the intact hemisphere. Thisinterpretation was confirmed by Gammaresponse analyses of EEG recordings (Schadowet al., 2009). Interestingly, Corbetta et al. (2005)found in patients with attentional dysfunctionsafter parietal lesions fMRI evidence of hyper-activation in contralateral, intact cortical regions.As hyperactivation declined, attentional dysfunc-tion recovered. Thus, reduced transcallosal inhib-itory interaction (directly or indirectly) mayreinstate interhemispheric balance after lesionsand interhemispheric modulation may improveperceptual functioning and recovery.

Hyperactivations as a result of the loss of inhib-itory fibers in deafferented brain regions may alsoexplain the figure confabulation in parietalpatients (a kind of “reverse diaschisis”) (Parameiand Sabel, 2008): In a way, the patient's “expecta-tion” of a visual stimulus (such as a square) “out-competed” the evidence from the sensory input,or, in Corbetta's terms, there was a top-down biasalong with a decreased stimulus-driven capture.

Visual hallucinations during recovery ofvision The notion of top-down hyperactivationis also in agreement with observations inhemianopic patients that report simple phos-phene perceptions (hallucinations) during thetime of spontaneous recovery and during

training-induced visual field expansions. Kölmel(1985, 1993) was the first to propose that visualhallucinations in partially blind patients are a pos-itive sign of neural plasticity and recovery of func-tion. But direct proof of a link betweenhallucinations and recovery of visual functionswas first shown by Poggel et al. (2007). Theyobserved hallucinations in hemianopic patientsduring the days and weeks of early spontaneousrecovery and also again when visual field recov-ery was induced by training. Here, simple andcomplex hallucinations were associated in timeand space with increased visual field size andrecovery: (i) hallucinations were more frequentlyin patients who benefited from training, (ii) theywere typically located in ARVs, and (iii)hallucinations coincided in time with the periodof greatest visual field expansion. It should bementioned in passing that patients are usuallyaware that these “hallucinations” are not real.But the patients usually do not talk about itbecause they are worried that it is seen by othersas signs of a psychiatric disorder (which it is not).

Restoration of vision by additionallesions Because the intact hemisphere has aninhibitory effect on contralateral, cortical, andsubcortical areas (such as the superior colliculus),cross-hemispheric inhibition may contribute todysfunction. Consequently, lifting this inhibitionmay restore functions. This was first demonstra-ted by Sprague (1966) in cats where additionallesions in the intact hemisphere restored someof the lost functions induced by a tectal lesion(sometimes referred to as the Sprague effect).Here, a unilateral lesion of the superior colliculusled to orienting deficits which were counteractedby contralateral visual cortex damage.

Perhaps the most impressive proof of inter-hemispheric interactions after brain lesions inhumans was published by Pöppel and Richards(1974). They described a hemianopic patientwho also had a small lesion in the contralateralintact field. Here, an “island of vision” of visionwas seen in the otherwise absolute blind

244

hemifield. Because this island of vision was mirrorsymmetric to the island of blindness, this effectwas interpreted as an example of a liftingdeafferentation effect.

Cortical reorganization as demonstrated byimaging studies fMRI studies have revealed thefirst evidence of visual system reorganization inhumans. Whereas in healthy subjects, brain acti-vation is found particularly in contralateral V1(area 17), in patients with post-geniculate lesions,in contrast, activation changes are found bilater-ally in the extrastriate areas with a stronger acti-vation on the intact (contralesional) hemisphere(areas 18 and 19) (Nelles et al., 2002, 2007).Brodtmann et al. (2009) showed that bilateral stri-ate and ventral extrastriate activation wasreduced in stroke patients, while activationincreased in dorsal sites, indicating a greater utili-zation of the dorsal visual system. These findingsare in agreement with the interhemispheric imbal-ance hypothesis.Cortical reorganization was also reported in

patients suffering from macular degenerationwho develop a preferred retinal locus (PRL)(see discussion above). Imaging studies showedthat the PRL has a larger cortical representationthan other retinal regions of the same eccentricity(Liu et al., 2010) and isoeccentric peripherallocations are represented in the formerly fovealcortex (Dilks et al., 2009). Thus, there are both“active” mechanisms of reorganization which areuse dependent and passive ones which are useindependent.When stimulating the brain by behavioral train-

ing, activation changes in fMRI are observed.After eye-movement training, for example, thereare changes in the unaffected extrastriate cortex(Nelles et al., 2010). Also when patients carryout VRT, activations are found in the anteriorcingulate and dorsolateral frontal cortex togetherwith other higher order visual areas in theoccipitotemporal and middle temporal regions(Marshall et al., 2008). Along similar lines,Henriksson et al. (2007) trained hemianopic

patients using flicker stimulation which causedan ipsilateral representation of the trained visualhemifield in different cortical areas, includingthe primary visual cortex. Similar findings werereported by Raninen et al. (2007).

Retinotopic mapping was used by Ho et al.(2009) to show residual visual function in apatient with complete homonymous hemianopia.Retinotopic representation was found in the sur-viving visual cortex around the infarcted areaand stimulating the blind field led to a responsein extrastriate areas above the calcarine sulcus.

So far, fMRI imaging results are compatiblewith the concept of large scale visual cortex reor-ganization (network plasticity). Unfortunately, inmany studies, the patient numbers have beentoo small (often single cases) to reach final con-clusions on the generality and reliability of corti-cal reorganization by brain imaging (however,see Raemaekers et al., 2011). More informationis now required using larger patient samples incombination with sophisticated behavioralparadigms.

Functional silencing of the intact hemisphere Theeasiest way to achieve functional balance is tosilence the undamaged hemisphere by simplyexposing the subject to darkness. In this manner,both hemispheres are functionally inactivated,processing less visual information. In this situa-tion, a functional “advantage” can be created forARVs by stimulating them selectively while theintact field remains in the dark. This is what theclassic VRT does: here patients train in the darkwhich has two simultaneous effects: functionalsilencing of intact regions while being able to acti-vate ARVs (see discussion of the restorationpotential of VRT above). In a way, VRT createsa double-punch situation: on one hand, a reducedactivation by darkness of the intact hemispherewith the consequence of reduced interhemi-spheric inhibition in the lesioned hemisphere,and on the other hand, the simultaneous activa-tion by visual stimulation of the previouslyinhibited ARVs inside or near the lesion.

245

The net result is a functional rebalancing which,if practiced regularly, is stabilized.

Thus, the imbalance between excitatory andinhibitory neural influences aggravates the visualloss after brain lesions. As the brain can beinduced to reach a more homeostatic, balancedstate (by training or brain current stimulation),partial vision restoration is achieved. If homeo-static balance is the key in vision restoration, thenit should not matter if inhibition is reinstated inregions that are overexcited or excitation isreinstated in areas suffering deafferentationdepression (diaschisis). Preferably both can beused to reestablish the balance at different levelsof the nervous system: at local, lateral interactionsor at long-range intra- and interhemispheric(transcallosal and subcortical) projections.

Both “within-systems plasticity” and “networkreorganization” are part of the post-lesionresponse in the brain. They act in concert to opti-mize residual vision and restoration, but theremay also be some maladaptive elements to reor-ganization which need to be explored. Becauselesions vary greatly from minor loss to completeblindness, the extent of restoration is variable aswell. But it is the sum of local (within-systemsplasticity) and global (network plasticity)influences that will determine the final extent ofrecovery of perception.

Cellular mechanisms of vision restorationand plasticity

How can such within systems and network plastic-ity be explained on a cellular level? We believethat the cellular mechanism of vision restorationinvolves the strengthening of surviving neuronsin the damaged system itself and/or reorganiza-tion of higher-up (intact) neuronal networks. Thisissue was already discussed above. Building onthe assumption that a stable within-systems andnetwork plasticity change requires stable changesat the synaptic level, the questions arise how syn-aptic plasticity can be achieved by surviving cells.

We would like to propose that vision restora-tion rests upon cellular and molecularmechanisms of normal learning. We believe thatjust as in the normal brain, repetitively activatingsurviving (residual) cells lead to synaptic plastic-ity, and this is relevant for both for surviving cellsof the damaged structure itself and for cells inupstream networks (network plasticity).

Interestingly, it seems less critical as to whichprecise method of stimulation is used to achievereactivation of residual structures: (1) regulartraining where patients (or the animals) have torespond to many thousands of visual stimuli or(2) by noninvasive brain current stimulationprotocols which are fairly nonspecific (see above).

At a cellular level, learning was studied inrodents where the concept of LTP was established(Bliss and Lomo, 1973). LTP is defined as a long-lasting enhancement in the cell response to high-frequency stimulation (Fig. 12). LTP maintenanceis mediated by both an increased transmitterrelease per presynaptic impulse and an increasedpostsynaptic responsiveness to a fixed amount oftransmitter (Voronin et al., 1995). LTP has beeninduced also in the human visual system by nonin-vasive “photic tetanus” (Sale et al., 2010). Interest-ingly, LTP as a model of learning and memory hasbeen used already to investigate post-lesional plas-ticity and, of most relevance here, in residualstructures in the vicinity of a lesion (Dohle et al.,2009; Huemmeke et al., 2004). Electrophysiologi-cal recordings of ex vivo/in vitro preparations ofthe post-lesional visual cortex revealed that LTPis enhanced while LTD (long-term depression) isimpaired (Imbrosci et al., 2010). This“metaplasticity” may provide the physiological/molecular basis of the rewiring of synapticconnections and restoration of visual function.Postsynaptic NMDA receptors play a special rolein LTP in the lesion surround, and this is compati-ble with the hypothesis that LTP in horizontalconnections in visual cortex might comprise thecellular mechanism of vision restoration (Imbrosciet al., 2010). However, although these results sug-gest that post-lesion neuronal plasticity is possible,

246

one has to keep in mind that there is still a signifi-cant loss of function in neuronal populations in thevicinity of cell death/damage (Aoyagi et al., 1998;Henrich-Noack et al., 2005). Also, as followingtraumatic optic nerve damage, there are molecularchanges in the surviving cells such as alterations inthe splicing variance of different NMDA receptors(Kreutz et al., 1998). It is not clear if thesealterations are adaptive or maladaptive.In any event, considering the evidence for

both, metaplasticity and silencing of neurons,

post-lesion plasticity may be induced by over-coming injury-related blockades. Interestingly, ata cellular level, this is possible by mechanisms oflearning: high-frequency stimulation which underphysiological conditions induces LTP is also ableto restore lost functions in silent neuronalpopulations after brain injury (Henrich-Noacket al., 2005). However, restoration of function bylearning is not possible at very early post-lesiontimes. It can therefore be hypothesized thatneurons need some time after an impact to

Synaptic plasticity after partial brain injury

Residual neurons

Resting state

Presynaptic Postsynaptic

Stimulated

Fig. 12. Synaptic plasticity after partial brain injury. The hypothesis of within-systems plasticity proposes that synaptic plasticitycontributes to restoration of vision. It assumes that in a partially injured area of the brain, the physiological activity (sum of allaction potentials) produced by surviving neurons is below normal values, insufficient to drive the postsynaptic neuron (partiallydeafferented structure) at full throttle (upper panel). By stimulating the presynaptic neurons of the partially damaged region bytraining or electrical stimulation, the silenced activation state (middle panel) changes to greater activation. Repeated activationthen elevates cell activity (number of action potentials) above-normal levels, strengthening synaptic efficacy (lower panel). This,in turn, leads to induction of long-term synaptic plasticity which outlasts the stimulation period. On a molecular level of analysis,the process of synaptic plasticity is achieved by the release of trophic factors from postsynaptic cells (adapted from Kolarowet al., 2007)

247

recover and adapt their molecular/morphologicalintegrity. After this delay, changes in themicromilieu or inhibitory feedback loops preventthe post-lesion neuronal plasticity as ex vivoinvestigation of silenced neuronal populationshows normal function and plasticity. This resto-ration of plasticity and function also depends onchanges in postsynaptic sensitivity (Henrich-Noack et al., 2005), and this is compatible withthe hypothesis that hallucinations reported byvisually impaired patients are a sign of post-lesiondenervation supersensitivity.

LTP or LTD, supported by the release of tro-phic factors, may explain the strengthening ofsynaptic transmission (plasticity), possibly alsoinvolving axon terminal sprouting, but single cellsalone do not explain the reaction of the entireresidual network. Rather, network reactions as awhole generate function and alter RF plasticity.LTP/LTD may thus provide the cellular conditionfor an overall change at the network level.

Vision restoration and neuronal synchronization

When a visual stimulus hits the retina, retinal cellsfire together in a timely synchronized fashion andinformation travels to higher brain centers. Undernormal conditions, this synchronization worksperfectly, evoking many secondary ripple effectsin the brain (such as oscillations) which jointlycreate the percept. However, when cells are lostand primary and secondary disorganization ofneuronal networks happens, one would expect aloss of synchrony, that is, a worst coordinationof timed events. A slowing of mental processingwould be expected which is what we see inpatients who show reduced reaction times andfeel uncomfortable observing the fast movingworld (navigating in a busy crowd or driving acar). Thus, to restore vision requires a better neu-ronal synchronization.

Figure 2 shows the concept of “stimulation-induced synchronization” after partial nervoussystem damage. While neurons in intact brain

regions fire in a synchronized manner to drivenormal vision (jointly firing action potentials andoscillating network in perfect temporal coordina-tion), areas of partial damage are initially non-synchronized, with poor firing synchrony. Afterexternal stimulation (induced by training or dur-ing electric current stimulation), the partiallydamaged regions are forced to fire jointly in tem-poral coordination. We hypothesize that such arepeated stimulation induces a “forced synchroni-zed firing” which then leads to synaptic plasticityof the partially damaged structures and down-stream areas. By doing this repeatedly, LTP-likemechanisms lead to stabilized synchronous firingin the network which lasts beyond the treatmentperiod (aftereffects). This improved or stabilizedsynchronization is a key mechanism of the pro-posed neurophysiological mechanism of visionrestoration.

Vision restoration and attention

It is well known that neural activation enhancesvisuospatial attention. Behavioral, neurophysiolog-ical, and imaging experiments show that focusingattention to a specific part of the visual fieldbenefits visual processing in that area, for example,reaction times are reduced, and stimuli are detectedor discriminated more easily then when attention isdistributed more diffusely across the visual field orfocused elsewhere (Eriksen and Rohrbaugh, 1970;Nakayama and Mackeben, 1989; Posner, 1980;Treisman and Gelade, 1980). This can be explainedby increased neuronal activation (synchronization)in circumscribed regions of the visual cortex asshown in single-cell recordings in animals (Gilbert,1998; Ito and Gilbert, 1999), electrophysiologicalexperiments in humans (Mangun and Hillyard,1987) and in brain-imaging studies (Martinezet al., 1999; Somers et al., 1999). In the attentionspotlight, the signal-to-noise ratio increases,resulting in improved performance of the normalbrain. The benefit of attention is particularly obvi-ous under difficult perceptual conditions with low

248

signal-to-noise ratio. Attentional load modulatesnot only responses of invisible stimuli in human pri-mary visual cortex, but it also improves normalvision at low contrast viewing conditions (Bahramiet al., 2007).Such an attentional advantage is also found in

patients with visual field defects. Here, visuospa-tial cues can acutely improve detection perfor-mance: when patients are asked to focus theirattentional spotlight at the visual field border, thisimmediately enhances perceptual performancewithin a few hundred milliseconds after stimuluspresentation precisely in the region of the cue(Poggel et al., 2006; see Fig. 10). Thisdemonstrates that residual vision can be immedi-ately accessed by activating attentional resources.In this context, a rather curious observation bySchendel and Robertson (2004) might be of inter-est. They reported that visual detection can be(acutely) increased in hemianopic patients byplacing their arm near the visual stimuli whenthis was located in the blind hemifield. Thisarm placement might have simply increased theattention to the stimulus location, elevating itsexcitability. Another example is a patient withnear-blindness that one of us (B. A. S.) studiedin Wisconsin/USA in 2000. When asked todescribe what he sees he said: “just darkness,nothing else.” When being confronted with a sud-den noise (B. A. S. clapped his hands unexpect-edly near the patients ears, a rather startlingsound), the patient suddenly said he could see aperson (the attending physician) standing in frontof him, stating with joy: “I can see the doc, he iswearing a red tie” (which he actually did). Thisis a dramatic example of how temporary visionimprovement that can be achieved by raising thepatients level of alterness or attention.Directing the attentional spotlight repetitively

onto the ARVs in a repetitive practice tasks(training) leads to permanent improvement ofvision in patients suffering from visual fielddefects. Poggel et al. (2004) combined standardVRT in hemianopics with an attentional cueing

task focusing attention to ARVs and found thisto enhance the restoration level of VRT (Fig. 10).Also, the Jung et al. (2008) study, where trainingof the intact region of the visual field in patientswith anterior ischemic optic neuropathy improvedfunction, was taken to conclude that this “mayreflect diffusely increased visual attention (neuro-nal activation), or improvement of an underlyingsubclinical abnormality in the seeing visual field”(p. 145). The Poggel study supports the hypothesisthat both ARVs normally receive insufficientattentional resources; the intact visual field sectorsimply captures all of the attention in everyday life,at the expense of the partially damaged areas byinhibiting them (excitatory/inhibitor dysbalance).In summary, attention plays a key role in the plas-ticity of partially damaged areas of V1 at a net-work level, even in the presumably intact visualfield sector.

The residual vision activation theory

Only partially damaged brain systems have apotential for restoration of vision. Clearly, if thereis no structure (e.g., complete eye damage), thereis no chance for recovery. Rather, recovery or res-toration of function requires someminimal amountof tissue that is (or becomes) dedicated to this task.One of us has earlier postulated the “hypothesis ofminimal residual structures” (Sabel, 1997). It isremarkable how much a relatively small numberof cells can accomplish. Rats with mild optic nerveinjury with only 10–20% of the RGCs survival(Sautter and Sabel, 1993) recovered their abilityto perform visual tasks again in about 2–3 weeks.The recovery was not complete and also not allanimals recovered to the same extent. Yet, visualperformance improved from complete visual dys-function to about 70–80% performance. Thisrather remarkable and unexpected observationsuggests that a small percentage of neurons andtheir intact axons are sufficient to allow consider-able recovery.

249

The behavioral tasks we used to test our ratsemployed rather simple brightness discriminationor pattern discrimination tasks. We do not knowif perhaps some more complex functions such asambient stimulus perception, fast or complextasks might remain deficient. Nevertheless, thesefindings clearly attest to a considerable post-lesion plasticity potential after partial visual sys-tem damage which opens new possibilities to takeadvantage of this restoration potential by devel-oping new therapeuties.

Our own research and that of others have con-firmed the restoration potential of residual vision.There are many publications on the subject ofvision restoration and plasticity by now from dif-ferent fields of study (Table 1). With this review,we have attempted to arrange these many puzzlepieces to a coherent picture. Based on severaldecades of research by us and others since the1970s, we now propose the residual vision activa-tion theory as follows:

Damage to visual structures is usually not com-plete but some structures survive the damage.Together with structures of the intact hemi-sphere, they provide residual capacities to sup-port vision restoration.Residual structures include (i) partially damagedtissue that sustains “areas of residual vision”(ARV) at the visual field border, (ii) “islands ofresidual vision” inside the blind field, (iii) alter-nate visual pathways unaffected by the damage(sustaining “blindsight”), and (iv) down-stream,higher-level neuronal networks. Because patientswith retina or brain damage tend to focus theirattention on the “intact” visual field sectors ineveryday life, a result of a hyperactivation of theintact hemisphere, residual structures lack suffi-cient attentional resources, reducing their activa-tion state and impairing physiological activationand synchronization. Residual structures thus suf-fer a triple handicap: (i) they have fewer neurons,(ii) they are disturbed in their excitation/inhibi-tion balance and temporal processing, and (iii)they lack sufficient attentional activation. ARVs

are therefore down-regulated, unable to contrib-ute much to every-day vision. “Non-use” thenimpairs their synaptic strength even further.Residual structures can be (re-)activated/restoredby engaging them in repetitive activation andstimulation. This repetitive activation of residualvision can be achieved by different means suchas (i) visual experience, (ii) visual training, or(iii) noninvasive electrical current brain stimula-tion. This may lead to reorganization by thestrengthening of synaptic transmission of the par-tially damaged structures themselves (“within-systems plasticity”) and of downstream neuronalnetworks (“network plasticity”) in cortical or sub-cortical areas of the damaged and the intacthemisphere. This leads to improved synchroniza-tion of neuronal firing in the brain network.Cellular mechanisms of vision restoration are simi-lar to, if not identical with those involved in normalperceptual learning (such as long-term potentia-tion) which is why long-lasting reorganization andre-synchronization of synaptic plasticity can sustainlong term activation of residual structures. Visionrestoration should therefore not be regarded as apathology-specific phenomenon but an expressionof normal learning which explains that it can beinduced at any time after the lesion, at all ages andinmost, if not all, visual field impairments (scotoma,tunnel vision, hemianopia, acuity loss), irrespectiveof their etiology (e.g. stroke, neurotrauma,glaucoma, amblyopia, AMD).However, vision restoration is rarely completeand does not take place in all patients. If and towhat extent restoration can be achieved is a func-tion of the precise nature and extent of residualstructures and their activation state. In addition,the extent of restoration depends on the properactivation methodology and appropriateparameters, and it requires the allocation of suffi-cient attentional resources directed toward theresidual structures.Thus, themoreARVare available, the greater is therestoration potential. Whereas the acute activationof residual vision leads to only temporary functional

250

improvements, permanent improvements requirerepetitive stimulation for many days, weeks ormonths (depending on the stimulation method).By becoming again engaged in every day vision,(re-) activation and synchronization of ARVoutlasts the stimulation period, leading to long-termimprovements in vision and quality of life.

Considering the large body of evidence, wenow have many reasons to be more optimisticabout the fate of partial blindness. The visual sys-tem has an excellent potential for plasticity andself-repair, much more than previously thoughtwhich is a paradigm shift. If in doubt, considerthe following quote by perhaps the most promi-nent visual system scientist, Torsten N. Wiesel,who received the Nobel Prize for his work onvisual system specificity and RF organization. Ina lecture held at the symposium “Restoration ofvision after brain damage” during the “VISION2005” meeting (organized by B. A. S. and T.Wiesel; Royal National Institute of the Blind,London) he emphasized the value of vision resto-ration research:

Restoration of vision after damage is an issue I amvery interested in and I think that there is prog-ress; to find different means of restoring visualfunctions is very interesting and encouraging. . .(My experiments on receptive field enlargements)are hard evidence that it is possible to restore(visual) function through time. In this case wedid not make any special effort by stimulatingthe eyes,. . . trying to restore visual functions. . .but this kind of experiment gives you hope thatthere is more to learn from this kind ofexperiments and also from the clinical work thatit should be possible to have patients restore visionin spite of initially apparent lack of vision. . .

Time will tell if the proposed residual visionactivation theory is a paradigm shift (Kuhn,1962) in the fields of low vision, neuro-ophthal-mology, and restorative neurology. In any event,

we hope the theory will stimulate others to getengaged in further discussion and experimentalverification. We do not expect that each individ-ual aspect of the proposed theory will hold for-ever. But it is a start to better understand thecomplex mechanisms of how the brain may over-come visual impairments. For sure, new aspectswill have to be added to the proposed theory.But nevertheless, it provides a heuristic basis forfurther studies in the field of vision restoration,a rather complex issue in restorative neurosci-ence. Hopefully, the theory will inspire others tocarry out new experiments and develop newtreatment options. Perhaps the current theory willbe modified or extended at some point. In thismanner, vision restoration may mature to becomea more widely accepted subject. The theoryshould lead our way to go beyond the widelyaccepted notion that (partial) blindness after reti-nal and cerebral damage is forever and unchange-able. Rather than turning a “blind eye” on visionrestoration as a real possibility, we shall recognizethat the theory is a basis for a more hopeful atti-tude: that vision restoration is possible and thatnew and innovative solutions may be found thatreduce the impact of visual impairments. Futureresearch and development will help improvevisual impairments, extending far beyond the con-ceptual borders that currently limit our view. Weare at the dawn of a better medical care forpatients that greatly suffer from partial blindnesswhich is inflicted by retinal and cerebral visualinjury.

Acknowledgments

We thank Steffi Matzke and Sylvia Prilloff fortheir excellent help preparing the chapter, andspecial thanks to W. Waleszczyk (Nencki Instituteof Experimental Biology, Warsaw, Poland) forinsightful comments on a previous version of thechapter.

251

References

Aiello, L. P. (2008). Targeting intraocular neovascularizationand edema—One drop at a time. The New England Journalof Medicine, 359, 967–969.

Antal, A., Artl, S., Nitsche, M. A., Chadaide, Z., & Paulus, W.(2006). Higher variability of phosphene thresholds inmigraineurs than in controls: A consecutive transcranialmagnetic stimulation study. Cephalalgia, 26, 865–870.

Antal, A., Boros, K., Poreisz, C., Chaieb, L., Terney, D., &Paulus, W. (2008). Comparatively weak after-effects oftranscranial alternating current stimulation (tACS) on corti-cal excitability in humans. Brain Stimulation, 1, 97–105.

Antal, A., Kincses, T. Z., Nitsche, M. A., & Paulus, W. (2003).Modulation of moving phosphene thresholds by transcranialdirect current stimulation of V1 in human. Neuropsychologia,41, 1802–1807.

Aoyagi, A., Saito, H., Abe, K., & Nishiyama, N. (1998). Earlyimpairment and late recovery of synaptic transmission in therat dentate gyrus following transient forebrain ischemiain vivo. Brain Research, 799, 130–137.

Azzopardi, P., & Cowey, A. (2001). Motion discrimination incortically blind patients. Brain, 24, 30–46.

Bahrami, B., Lavie, N., & Rees, G. (2007). Attentional loadmodulates responses of human primary visual cortex toinvisible stimuli. Current Biology, 17, 509–513.

Bak, M., Girvin, J. P., Hambrecht, F. T., Kufta, C. V.,Loeb, G. E., & Schmidt, E. M. (1990). Visual sensationsproduced by intracortical microstimulation of the humanoccipital cortex. Medical & Biological Engineering &Computing, 28, 257–259.

Baker, C. I., Dilks, D. D., Peli, E., & Kanwisher, N. G. (2008).Reorganization of visual processing in macular degenera-tion: Replication and clues about the role of foveal loss.Vision Research, 48, 1910–1919.

Baker, C. I., Peli, E., Knouf, N., & Kanwisher, N. G. (2005).Reorganization of visual processing in macular degenera-tion. The Journal of Neuroscience, 25, 614–618.

Balliett, R., Blood, K. M., & Bach-y-Rita, P. (1985).Visual field rehabilitation in the cortically blind? Journalof Neurology, Neurosurgery and Psychiatry, 48, 1113–1124.

Barbur, J. L., Watson, J. D. G., Frackowiak, R. S. J., &Zeki, S. (1993). Conscious visual perception without V1.Brain, 116, 1293–1302.

Bartley, S. H., & Ball, R. J. (1969). Effects of intermittentphotic input on brightness, hue, saturation, visual acuity,and stereopsis. American Journal of Optometry and Archivesof American Academy of Optometry, 46, 315–318.

Baumann, T. P., & Spear, P. D. (1977). Role of supersylvianvisual area in behavioral recovery from effects of visualcortex damage in cats. Brain Research, 138, 445–468.

Baumgarten, P. (1878). Hemiopie nach Erkrankung deroccipitalen Hirnrinde. Centralblatt für die MedicinischenWissenschaften, 16, 369–371.

Beard, B. L., Levi, D. M., & Reich, L. N. (1995). Perceptuallearning in parafoveal vision. Vision Research, 27, 953–965.

Bechtereva, N. P., Bondartchuk, A. N., Gretchin, V. B.,Iliukhina, V. A., Kambarova, D. K., Matveev, Y. K., et al.(1972). Structural–functional organization of the humanbrain and the pathophysiology of the Parkinsonian typehyperkineses. Confinia Neurologica, 34, 14–17.

Bechtereva, N. P., Shandurina, A. N., Khilko, V. A.,Lyskov, E. B., Matveev, Y. K., Panin, A. V., et al. (1985).Clinical and physiological basis for a new method underly-ing rehabilitation of the damaged visual nerve function bydirect electric stimulation. International Journal of Psycho-physiology, 2, 257–272.

Benowitz, L. I., & Yin, Y. (2007). Combinatorial treatments forpromoting axon regeneration in the CNS: Strategiesforovercoming inhibitory signals andactivatingneurons’ intrin-sic growth state.Developmental Neurobiology, 67, 1148–1165.

Benowitz, L., & Yin, Y. (2008). Rewiring the injured CNS:Lessons from the optic nerve. Experimental Neurology,209, 389–398.

Benson, P. J., Guo, K., & Blakemore, C. (1998). Direction dis-crimination of moving gratings and plaids and coherence indot displays without primary visual cortex (V1). The Euro-pean Journal of Neuroscience, 10, 3767–3772.

Bergsma, D. P., & Van der Wildt, G. J. (2008). Properties ofthe regained visual field after visual detection training ofhemianopsia patients. Restorative Neurology and Neurosci-ence, 26, 365–375.

Bergsma, D. P., & van der Wildt, G. (2010). Visual training ofcerebral blindness patients gradually enlarges the visualfield. The British Journal of Ophthalmology, 94, 88–96.

Bliss, T. V., & Lomo, T. (1973). Long-lasting potentiation ofsynaptic transmission in the dentate area of theanaesthetized rabbit following stimulation of the perforantpath. The Journal of Physiology, 232, 331–356.

Bouwmeester, L., Heutnik, J., & Lucas, C. (2007). The effectof visual training for patients with visual field defects dueto brain damage: A systematic review. Journal of Neurology,Neurosurgery and Psychiatry, 78, 555–564.

Brindley, G. S., Donaldson, P. E. K., Falconer, M. A., &Rushton, D. N. (1972). The extent of the region of occipitalcortex that when stimulated gives phosphenes fixed inthe visual field. Journal of Physiology, London, 225, 57P–58P.

Brindley, G. S., & Lewin, W. S. (1968). The sensations pro-duced by electrical stimulation of the visual cortex. TheJournal of Physiology, 96, 479–493.

Brindley, G. S., & Rushton, D. N. (1977). Observations on therepresentation of the visual field on the human occipital cor-tex. In F. T. Hambrecht & J. B. Reswick (Eds.), Functionalelectrical stimulation: Applications in neural prostheses(pp. 261–276). New York: Marcel Dekker.

Brodtmann,A., Puce, A., Darby, D., &Donnan,G. (2009). Serialfunctional imaging poststroke reveals visual cortex reorganiza-tion.Neurorehabilitation and Neural Repair, 23, 150–159.

252

Calford, M. B., Chino, Y. M., Das, A., Eysel, U. T.,Gilbert, C. D., Heinen, S. J., et al. (2005). Neuroscience:Rewiring the adult brain. Nature, 438, E3–E4.

Calford, M. B., Wang, C., Taglianetti, V., Waleszczyk, W. J.,Burke, W., & Dreher, B. (2000). Plasticity in adult cat visualcortex (area 17) following circumscribed monocular lesionsof all retinal layers. Journal of Physiology, London, 524,587–602.

Calford, M. B., Wright, L. L., Metha, A. B., & Taglianetti, V.(2003). Topographic plasticity in primary visual cortex ismediated by local corticocortical connections. The Journalof Neuroscience, 23, 6434–6442.

Chaieb, L., Antal, A., & Paulus, W. (2008). Gender-specificmodulation of short-term neuroplasticity in the visual cortexinduced by transcranial direct current stimulation. VisualNeuroscience, 25, 77–81.

Center for Disease Control and Prevention, Aging Trends,No. 2, March 2004.

Chibisova, A. N., Fedorov, A. B., & Fedorov, N. A. (2001).Neurophysiological characteristics of compensation-recov-ery processes in the brain during rehabilitation of the neuro-sensory impairment of the visual and acoustic systems.Fiziologiia Cheloveka, 27, 14–21.

Chino, Y. M., Smith, E. G., Kaas, J. H., Sasaki, Y., &Cheng, H. (1995). Receptive field properties of deafferentedvisual cortical neurons after topographic map reorganizationin adult cats. The Journal of Neuroscience, 15, 2417–2433.

Chokron, S., Perez, C., Obadia, M., Gaudry, I., Laloum, L., &Gout, O. (2008). From blindsight to sight: Cognitive rehabil-itation of visual field defects. Restorative Neurology andNeuroscience, 26, 305–320.

Chow, K. L. (1968). Visual discrimination after extensive abla-tion of optic tract and visual cortex in cats. Brain Research,9, 363–366.

Chow, K. L., & Stewart, D. L. (1972). Reversal of structuraland functional effects of long-term visual deprivation in cats.Experimental Neurology, 34, 409–433.

Cohen, S. Y., Lamarque, F., Saucet, J. C., Provent, P.,Langram, C., & LeGargasson, J. F. (2003). Filling-in phe-nomenon in patients with age-related macular degeneration:Differences regarding uni- or bilaterality of central scotoma.Graefe's Archive for Clinical and Experimental Ophthalmol-ogy, 241, 785–791.

Cole, S. R., Beck, R. W., Moke, P. S., Gal, R. L., &Long, D. T. (2000). The National Eye Institute Visual Func-tion Questionnaire: Experience of the ONTT. InvestigativeOphthalmology & Visual Science, 41, 1017–1021.

Cooke, S. F., & Bear, M. F. (2010). Visual experience induceslong-term potentiation in the primary visual cortex. TheJournal of Neuroscience, 30, 16304–16313.

Corbetta, M., Kincade, M. J., Lewis, C., Snyder, A. Z., &Sapir, A. (2005). Neural basis and recovery of spatial atten-tion deficits in spatial neglect. Nature Neuroscience, 8,1603–1610.

Cowey, A. (1967). Perimetric study of field defects in monkeysafter cortical and retinal ablations. The Quarterly Journal ofExperimental Psychology, 19, 232–245.

Cowey, A., & Stoerig, P. (1991). The neurobiology ofblindsight. Trends in Neurosciences, 14, 140–145.

Cowey, A., & Stoerig, P. (1995). Blindsight in monkeys.Nature, 373, 247–249.

Darian-Smith, C., & Gilbert, C. D. (1994). Axonal sproutingaccompanies functional reorganization in adult cat striatecortex. Nature, 368, 737–740.

Darian-Smith, C., &Gilbert, C.D. (1995). Topographic reorgani-zation in the striate cortex of the adult cat andmonkey is corti-cally mediated. The Journal of Neuroscience, 15, 1631–1647.

Das, A., & Gilbert, C. D. (1995). Long-range horizontalconnections and their role in cortical reorganization rev-ealed by optical recording of cat primary visual cortex.Nature, 375, 780–784.

Das, A., & Huxlin, K. R. (2010). New approaches to visualrehabilitation for cortical blindness: Outcomes and putativemechanisms. The Neuroscientist, 16, 374–387.

De Weerd, P., Sprague, J. M., Raiguel, S., Vandenbussche, E.,& Orban, G. A. (1993). Effects of visual cortex lesions onorientation discrimination of illusory contours in the cat.The European Journal of Neuroscience, 5, 1695–1710.

De Weerd, P., Sprague, J. M., Vandenbussche, E., &Orban, G. A. (1994). Two stages in visual texture segrega-tion: A lesion study in the cat. The Journal of Neuroscience,14, 929–948.

Di Stefano, M., & Gargini, C. (1995). Recovery of the nasalfield loss in esotropic cats after section of the optic chiasm.Neuroreport, 6, 1341–1346.

Dilks, D. D., Baker, C. I., Peli, E., & Kanwisher, N. (2009).Reorganization of visual processing in macular degenerationis not specific to the “preferred retinal locus” The Journal ofNeuroscience, 29, 2768–2773.

Dilks, D. D., Serences, J. T., Rosenau, B. J., Yantis, S., &McCloskey, M. (2007). Human adult cortical reorganizationand consequent visual distortion. The Journal of Neurosci-ence, 27, 9585–9594.

Dobelle, W. H., Mladejovsky, M. G., Evans, J. R., Roberts, T. S.,& Girvin, J. P. (1976). 'Braille' reading by a blind volunteer byvisual cortex stimulation. Nature, 259, 111–112.

Dobelle, W. H., Mladejovsky, M. G., &Girvin, J. P. (1974). Arti-ficial vision for the blind: Electrical stimulation of visual cortexoffers hope for a functional prosthesis. Science, 183, 440–444.

Dohle, C. I., Eysel, U. T., &Mittmann, T. (2009). Spatial distribu-tion of long-term potentiation in the surround of visual cortexlesions in vitro. Experimental Brain Research, 199, 423–433.

Dreher, B., Burke, W., & Calford, M. B. (2001). Cortical plas-ticity revealed by circumscribed retinal lesions or artificialscotomas. Progress in Brain Research, 134, 217–246.

Dürsteler, M. R., Wurtz, R. H., & Newsome, W. T. (1987).Directional pursuit deficits following lesions of the fovealrepresentations within the superior temporal sulcus of the

253

macaque monkey. Journal of Neurophysiology, 57,1262–1287.

Duvdevani, R., Rosner, M., Belkin, M., Sautter, J.,Sabel, B. A., & Schwartz, M. (1990). Graded crush of thetat optic nerve as a brain injury model: Combining electro-physiological and behavioral outcome. Restorative Neurol-ogy and Neuroscience, 2, 31–38.

El Mallah, M. K., Chakravarthy, U., & Hart, P. M. (2000).Amblyopia: Is visual loss permanent? The British Journalof Ophthalmology, 84, 952–956.

Eriksen, C. W., & Rohrbaugh, J. W. (1970). Some factorsdetermining efficiency of selective attention. The AmericanJournal of Psychology, 83, 330–342.

Eysel, U. T. (1997). Perilesional cortical dysfunction and reorga-nization. In H.-J. Freund, B. A. Sabel & O. W. Witte (Eds.),Brain plasticity. Advances in Neurology, 73, pp. (195–206).

Eysel, U. T., & Grüsser, O.-J. (1978). Increased transneuronalexcitation of the cat lateral geniculate nucleus after acutedeafferentation. Brain Research, 158, 107–128.

Eysel, U. T., Schweigart, G., Mittmann, T., Eyding, D., Qu, Y.,Vandesande, F., et al. (1999). Reorganization in the visualcortex after retinal and cortical damage. Restorative Neurol-ogy and Neuroscience, 15, 153–164.

Fabre-Thorpe, M., Levesque, F., & Buser, P. (1994). Preserva-tion of pointing accuracy toward moving targets after exten-sive visual cortical ablations in cats. Cortex, 30, 585–601.

Fahle, M. (2002). Perceptual learning: Gain without pain?Nature Neuroscience, 5, 923–924.

Fahle, M. (2005). Perceptual learning: Specificity versus gener-alization. Current Opinion in Neurobiology, 15, 154–160.

Fahle, M., & Poggio, T. (2002). Perceptual learning.Cambridge, MA: MIT Press.

Fahle, M., & Skrandies, W. (1994). An electrophysiologicalcorrelate of learning in motion perception. German Journalof Ophthalmology, 3, 427–432.

Fedorov, A. B., Chibisova, A. M., & Tchibissova, J. M. (2005).Impulse modulating therapeutic electrical stimulation(IMTES) increases visual field size in patients withoptic nerve lesions. International Congress Series, 1282,525–529.

Fedorov, A. B., Jobke, S., Chibisova, A. N., Chibisova, J. M.,Gall, C., & Sabel, B. A. (2010). Restoration of vision: non-invasive current stimulation enhances brain synchronizationafter optic nerve damage - a retrospective observationalstudy with 446 patients. World Ophthalmology Congress,Berlin, Germany, June, 5–9.

Felleman, D. J., & Van Essen, D. C. (1991). Distributed hier-archical processing in the primate cerebral cortex. CerebralCortex, 1, 1–47.

Fendrich, R., Wessinger, C. M., & Gazzaniga, M. S. (1992).Residual vision in a scotoma: Implications for blindsight.Science, 258, 27.

Fendrich, R., Wessinger, C. M., & Gazzaniga, M. S. (1993).Sources of blindsight (technical comment). Science, 261,494–495.

Fiorentini, A., & Berardi, N. (1980). Perceptual learning specificfor orientation and spatial frequency. Nature, 287, 43–44.

Fischman, M.W., &Meikle, T. H. Jr. (1965). Visual intensity dis-crimination in cats after serial tectal and cortical lesions. Jour-nal of Comparative andPhysiological Psychology, 59, 193–201.

Foerster, O. (1929). Beitrage zur Pathophysiologie derSehbahn und der Sehsphare. Journal für Psychologie undNeurologie, 39, 435–463.

Franke, G. H., & Gall, C. (2008). Quality of life—Methodol-ogy and clinical practice aspects with a focus on ocular med-icine. Ophthalmologe, 105, 727–734.

Fronius, M., Cirina, L., Cordey, A., & Ohrloff, C. (2005).Visual improvement during psychophysical training in anadult amblyopic eye following visual loss in the contralateraleye. Graefe's Archive for Clinical and Experimental Oph-thalmology, 243, 278–280.

Fronius, M., Cirina, L., Kuhli, C., Cordey, A., & Ohrloff, C.(2006). Training the adult amblyopic eye with ‘perceptuallearning’ after vision loss in the non-amblyopic eye. Strabis-mus, 14, 75–79.

Fujikado, T., Morimoto, T., Matsushita, K., Shimojo, H.,Okawa, Y., & Tano, Y. (2006). Effect of transcorneal elec-trical stimulation in patients with nonarteritic ischemic opticneuropathy or traumatic optic neuropathy. Japanese Journalof Ophthalmology, 50, 266–273.

Galambos, R., Norton, T. T., & Frommer, G. P. (1967). Optictract lesions sparing pattern vision in cats. ExperimentalNeurology, 18, 8–25.

Gall, C., Franke, G. H., & Sabel, B. A. (2010a). Vision-relatedquality of life in first stroke patients with homonymous visualfield defects. Health and Quality of Life Outcomes, 88, 33.

Gall, C., Fedorov, A. B., Ernst, L., Borrmann, A., &Sabel, B. A. (2010b). Repetitive transorbital alternating cur-rent stimulation (rtACS) in optic neuropathy—Single casestudy. NeuroRehabilitation, 27, 335–341.

Gall, C., Wagenbreth, C., Sgorzaly, S., & Sabel, B. A. (2010c).Parafoveal vision impairments and their influence onreading performance and self-evaluated reading abilities.Graefe's Archive for Clinical and Experimental Ophthalmol-ogy, 248, 863–875.

Gall, C., Lucklum, J., Sabel, B. A., & Franke, G. H. (2009).Vision- and health-related quality of life in patients withvisual field loss after postchiasmatic lesions. InvestigativeOphthalmology & Visual Science, 50, 2765–2776.

Gall, C., Mueller, I., Kaufmann, C., Franke, G. H., &Sabel, B. A. (2008). Visual field defects after cerebrallesions from the subject's perspective: Health- and vision-related quality of life assessed by SF-36 and NEI-VFQ.Der Nervenarzt, 79, 185–194.

Gall, C., Schmidt, S., Brandt, S., Fedorov, A. B., &Sabel, B. A. (2011). Non-invasive alternating current stimu-lation impoves subjective visual functioning in optic neurop-athy. Neuroscience, Washington, 12.11.–16.11.2011.

Ganz, L., & Fitch, M. (1968). The effect of visual deprivation onperceptual behavior. Experimental Neurology, 22, 638–660.

254

Giannikopoulos, D. V., & Eysel, U. T. (2006). Dynamics andspecificity of cortical map reorganization after retinallesions. Proceedings of the National Academy of Sciencesof the United States of America, 103, 10805–10810.

Gibson, E. (1969). Principles of perceptual learning and devel-opment. New York: Appleton-Century-Crofts.

Gilbert, C. D. (1998). Adult cortical dynamics. PhysiologicalReviews, 78, 467–485.

Gilbert, C. D., Sigman, M., & Crist, R. E. (2001). The neuralbasis of perceptual learning. Neuron, 31, 681–697.

Gilbert, C. D., & Wiesel, T. N. (1992). Receptive field dynam-ics in adult primary visual cortex. Nature, 356, 150–152.

Gothe, J., Brandt, S. A., Irlbacher, K., Röricht, S.,Sabel, B. A., & Meyer, B. U. (2002). Changes in visualcortex excitability in blind subjects as demonstrated bytranscranial magnetic stimulation. Brain, 125, 479–490.

Greenstein, V. C., Santos, R. A., Tsang, S. H., Smith, R. T.,Barile, G. R., & Seiple, W. (2008a). Preferred retinal locusin macular disease: Characteristics and clinical implications.Retina, 28, 1234–1240.

Greenwald, M. J., & Parks, M. M. (1999). Treatment of ambly-opia. In: T. Duane (Ed.), Clinical ophthalmology, (Vol. 1.Hagerstown: Harper and Row.

Gudlin, J. (2008) Objective and subjective effects of systematicvisual stimulation in glaucoma patients. Zugl.: MagdeburgUniv., Fak. für Naturwiss., Dissertation, 2008.

Gudlin, J., Mueller, I., Thanos, S., & Sabel, B. A. (2008).Computer based vision restoration therapy in glaucomapatients: A small open pilot study. Restorative Neurologyand Neuroscience, 26, 403–412.

Guenther, T., Mueller, I., Preuss, M., Kruse, R., & Sabel, B. A.(2009). Treatment outcome prediction model of visual fieldrecovery using Self-Organizing-Maps. IEEE Transactionson Biomedical Engineering, 56, 572–581.

He, Z. J., & Loop, M. S. (1991). Luminance sensitivityrecovers quickly in monocularly deprived cats. VisionResearch, 31, 1633–1637.

Heiduschka, P., & Thanos, S. (2000). Restoration of the ret-inofugal pathway. Progress in Retinal and Eye Research,19, 577–606.

Heinen, S. J., & Skavenski, A. A. (1991). Recovery of visualresponses in foveal V1 neurons following bilateral foveallesions in adult monkey. Experimental Brain Research, 83,670–674.

Held, R., & Hein, A. (1963). Movement-produced stimulationin the development of visually guided behaviour. Journal ofComparative and Physiological Psychology, 56, 872–876.

Henrich-Noack, P., Gorkin, A. G., Krautwald, K., Pforte, C.,Schröder, U. H., & Reymann, K. G. (2005). Tetanus-induced re-activation of evoked spiking in the post-ischemicdentate gyrus. Neuroscience, 133, 571–581.

Henriksson, L., Raninen, A., Näsänen, R., Hyvärinen, L., &Vanni, S. (2007). Training-induced cortical representation

of a hemianopic hemifield. Journal of Neurology, Neurosur-gery and Psychiatry, 78, 74–81.

Hess, R. F., Field, D., & Watt, R. J. (1990). The puzzle ofamblyopia. In C. Blakemore (Ed.), Vision: Coding andefficiency. Cambridge: Cambridge University Press.

Hirsch, J. A., & Gilbert, C. D. (1991). Synaptic physiology ofhorizontal connections in the cat's visual cortex. The Journalof Neuroscience, 11, 1800–1809.

Ho, Y. C., Cheze, A., Sitoh, Y. Y., Petersen, E. T., Goh, K. Y.,Gjedde, A., et al. (2009). Residual neurovascular functionand retinotopy in a case of hemianopia. Annals of theAcademy of Medicine, Singapore, 38, 827–831.

Holmes, G. (1918). Disturbances of visual orientation. TheBritish Journal of Ophthalmology, 2, 449–506.

Hubel, D. H., & Wiesel, T. N. (1970). The period of suscepti-bility to the physiological effects of unilateral eye closure inkittens. The Journal of Physiology, 206, 419–436.

Huemmeke, M., Eysel, U. T., & Mittmann, T. (2004). Lesion-induced enhancement of LTP in rat visual cortex is medi-ated by NMDA receptors containing the NR2B subunit.The Journal of Physiology, 559, 875–882.

Humphrey, N. K. (1970). What the frog's eye tells themonkey's brain. Brain, Behavior and Evolution, 3, 324–337.

Humphrey, N. K. (1974). Vision in a monkey without striatecortex: A case study. Perception, 3, 241–255.

Huxlin, K. R. (2008). Perceptual plasticity in damaged adultvisual systems. Vision Research, 48, 2154–2166.

Huxlin, K. R., Martin, T., Kelly, K., Riley, M., Friedman, D. I.,Burgin, W. S., et al. (2009). Perceptual relearning of com-plex visual motion after V1 damage in humans. The Journalof Neuroscience, 29, 3981–3991.

Huxlin, K. R., & Pasternak, T. (2004). Training-induced recov-ery of visual motion perception after extrastriate corticaldamage in the adult cat. Cerebral Cortex, 14, 81–90.

Hyvärinen, L., Raninen, A. N., & Näsänen, R. E. (2002).Vision rehabilitation in homonymous hemianopia. Neuro-Ophthalmology, 27, 97–102.

Imbrosci, B., Eysel, U. T., & Mittmann, T. (2010).Metaplasticity of horizontal connections in the vicinity oflaser lesions in rat visual cortex. The Journal of Physiology,588, 4695–4703.

Inomata, K., Shinoda, K., Ohde, H., Tsunoda, K.,Hanazono, G., Kimura, I., et al. (2007). Transcorneal electri-cal stimulation of retina to treat longstanding retinal arteryocclusion. Graefe's Archive for Clinical and ExperimentalOphthalmology, 245, 1773–1780.

Ito, M., & Gilbert, C. D. (1999). Attention modulates contex-tual influences in the primary visual cortex of alert monkeys.Neuron, 22, 593–604.

Jacobson, S. G., Eames, R. A., & McDonald, W. I. (1979).Optic nerve fibre lesions in adult cats: Pattern ofrecovery of spatial vision. Experimental Brain Research, 36,491–508.

255

Jacobson, S. G., McDonald, W. I., & Perry, P. A. (1977). Patternof recovery of spatial vision after pre-geniculate nerve fibrelesions in adults cats.The Journal of Physiology, 269, 25P–26P.

Jobke, S., Kasten, E., & Sabel, B. A. (2009). Vision restorationthrough extrastriate stimulation in patients with visual fielddefects—A double-blind and randomized experimentalstudy. Neurorehabilitation and Neural Repair, 23, 246–555.

Julkunen, L., Tenovuo, O., Jääskeläinen, S. K., &Hämäläinen, H. (2003). Rehabilitation of chronic post-strokevisual field defect with computer-assisted training: A clinicaland neurophysiological study. Restorative Neurology andNeuroscience, 21, 19–28.

Julkunen, L., Tenovuo, O., Vorobyev, V., Hiltunen, J.,Teräs, M., Jääskeläinen, S. K., et al. (2006). Functional brainimaging, clinical and neurophysiological outcome of visualrehabilitation in a chronic stroke patient. RestorativeNeurology and Neuroscience, 24, 123–132.

Jung, C. S., Bruce, B., Newman, N. J., & Biousse, V. (2008).Visual function in anterior ischemic optic neuropathy: Effectof Vision Restoration Therapy—A pilot study. Journal ofthe Neurological Sciences, 268, 145–149.

Kaas, J. H., Krubitzer, L. A., Chino, Y. M., Langston, A. L.,Polley, E. H., & Blair, N. (1990). Reorganization ofretinotopic cortical maps in adult mammals after lesions ofthe retina. Science, 248, 229–231.

Karmarker, U. R., & Dan, Y. (2006). Experience-dependentplasticity in adult visual cortex. Neuron, 52, 577–585.

Karni, A., & Sagi, D. (1991). Where practice makes perfect intexture discrimination: Evidence for primary visual cortexplasticity. Proceedings of the National Academy of Sciencesof the United States of America, 88, 4966–4970.

Kasten, E., Bunzenthal, U., Müller-Oehring, E. M., Mueller, I.,& Sabel, B. A. (2007). Vision restoration does not benefitfrom costimulation: A pilot study. Journal of Clinical andExperimental Neuropsychology, 29, 569–584.

Kasten, E., Bunzenthal, U., & Sabel, B. A. (2006). Visual fieldrecovery after vision restoration therapy (VRT) is indepen-dent of eye movements: An eye tracker study. BehaviouralBrain Research, 175, 18–26.

Kasten, E., Guenther, T., & Sabel, B. A. (2008). Inversestimuli in perimetric performance reveal larger visual fielddefects: Implications for vision restoration. RestorativeNeurology and Neuroscience, 26, 355–364.

Kasten, E., Müller-Oehring, E., & Sabel, B. A. (2001). Stabil-ity of visual field enlargements following computer-basedrestitution training—Results of a follow-up. Journal ofClinical and Experimental Neuropsychology, 23, 297–305.

Kasten, E., & Sabel, B. A. (1995). Visual field enlargementafter computer training in brain-damaged patients withhomonymous deficits: An open pilot trial. Restorative Neu-rology and Neuroscience, 8, 113–127.

Kasten, E., Wuest, S., & Sabel, B. A. (1998a). Variability ofstimulus detection, form discrimination, and color

recognition with suprathreshold campimetry in brain dam-aged patients. Neuroophthalmology, 20, 161–176.

Kasten, E., Wüst, S., Behrens-Baumann, W., & Sabel, B. A.(1998b). Computer-based training for the treatment of par-tial blindness. Natural Medicines, 4, 1083–1087.

Kasten, E., Wüst, S., & Sabel, B. A. (1998c). Residual vision intransition zones in patients with cerebral blindness. Journalof Clinical and Experimental Neuropsychology, 20, 581–598.

Keck, T., Mrsic-Flogel, T. D., Vaz Afonso, M., Eysel, U. T.,Bonhoeffer, T., & Hübener, M. (2008). Massive restructuringof neuronal circuits during functional reorganization of adultvisual cortex. Nature Neuroscience, 11, 1162–1167.

Keller, J., Strasburger, H., Cerutti, D. T., & Sabel, B. A.(2000). Automated assessment of the visual contrast sensi-tivity in the hooded rat. Journal of Neuroscience Methods,97, 103–110.

Kerkhoff, G., Münßinger, U., Eberle-Strauss, G., &Stögerer, E. (1992a). Rehabilitation of hemianopic alexiain patients with postgeniculate visual field disorders. Neuro-psychological Rehabilitation, 2, 21–42.

Kerkhoff, G., Münßinger, U., Haaf, E., Eberle-Strauss, G., &Stögerer, E. (1992b). Rehabilitation of homonymousscotomata in patients with postgeniculate damage of thevisual system: Saccadic compensation training. RestorativeNeurology and Neuroscience, 4, 245–254.

Kerkhoff, G., Münßinger, U., & Meier, E. K. (1994).Neurovisual rehabilitation in cerebral blindness. Archivesof Neurology, 51, 474–481.

Kerkhoff, G., & Schindler, I. (2000). Möglichkeiten undGrenzen restorativer Trainingsmethoden bei prä- undpostchiasmatischen Skotomen. Zeitschrift fürNeuropsychologie, 11, 82–85.

Kolarow, R., Brigadski, T., & Lessmann, V. (2007). Postsynap-tic secretion of BDNF and NT-3 from hippocampal neuronsdepends on calcium calmodulin kinase II signaling and pro-ceeds via delayed fusion pore opening. The Journal of Neu-roscience, 27, 10350–10364.

Kölmel, H. W. (1985). Complex visual hallucinations in thehemianopic field. Journal of Neurology, Neurosurgery andPsychiatry, 48, 29–38.

Kölmel, H. W. (1993). Visual illusions and hallucinations.Baillere‘s Clinical Neurology, 2, 243–264.

Korsholm, K., Madsen, K. H., Frederiksen, J. L., Rowe, J. B., &Lund, T. E. (2008). Cortical neuroplasticity in patientsrecovering from acute optic neuritis.Neuroimage, 42, 836–844.

Korsholm, K., Madsen, K. H., Frederiksen, J. L.,Skimminge, A., & Lund, T. E. (2007). Recovery from opticneuritis: An ROI-based analysis of LGN and visual corticalareas. Brain, 130, 1244–1253.

Kreutz, M. R., Böckers, T. M., Bockmann, J.,Seidenbecher, C., Kracht, B., Vorwerk, C. K., et al. (1998).Splicing of the retinal NR1 receptor is altered after opticnerve injury: The preferential expression of the NR1-b

256

isoforms is crucial for retinal ganglion cell survival. TheJournal of Neuroscience, 18, 8278–8291.

Kuhn, R. (1962). The speed of cerebral circulation. The NewEngland Journal of Medicine, 267, 689–695.

Lane, A. R., Smith, D. T., Ellison, A., & Schenk, T. (2010).Visual exploration training is no better than attentiontraining for treating hemianopia. Brain, 133, 1717–1728.

Lashley, K. (1939). The mechanisms of vision XVI. The func-tion of small remnants of the visual cortex. The Journal ofComparative Neurology, 70, 45–67.

Levi, D. M., & Carkeet, A. (1993). Amblyopia: A consequenceof abnormal visual development. In K. Simons (Ed.), Earlyvisual development, normal and abnormal (pp. 391–407).Oxford, NY: Oxford University Press.

Levi, D. M., & Polat, U. (1996). Neural plasticity in adults withamblyopia. Proceedings of the National Academy of Sciencesof the United States of America, 93, 6830–6834.

Levi, D. M., Polat, U., & Hu, Y. S. (1997). Improvement inVernier acuity in adults with amblyopia. Practice makes bet-ter. Investigative Ophthalmology & Visual Science, 38,1493–1510.

Levin, N., Orloy, T., Dotan, S., & Zohary, E. (2006). Normal andabnormal fMRI activation patterns in the visual cortex afterrecovery from optic neuritis.Neuroimage, 33, 1161–1168.

Li, W., Piech, V., & Gilbert, C. D. (2004). Perceptual learningand top-down influences in primary visual cortex. NatureNeuroscience, 7, 651–657.

Li, R. W., Young, K. G., Hoenig, P., & Levi, D. M. (2005).Perceptual learning improves visual performance in juvenileamblyopia. Investigative Ophthalmology & Visual Science,46, 3161–3168.

Liu, T., Cheung, S. H., Schuchard, R., Glielmi, C., Hu, X.,He, S., et al. (2010). Incomplete cortical reorganization inmacular degeneration. Investigative Ophthalmology &Visual Science, 51, 6826–6834.

Lorber, B., Berry, M., & Logan, A. (2008). Different factorspromote axonal regeneration of adult rat retinal ganglioncells after lens injury and intravitreal peripheral nervegrafting. Journal of Neuroscience Research, 86, 894–903.

Maire-Lepoivre, E., Przybyskawski, J., & Gary-Bobo, E. (1988).Visual field in dark-reared cats after an extended periodof recovery. Behavioural Brain Research, 28, 245–251.

Malis, L. I., & Kruger, L. (1956). Multiple response and excit-ability of cat's visual cortex. Journal of Neurophysiology, 19,172–186.

Mangun, G. R., & Hillyard, S. A. (1987). The spatial allocationof visual attention as indexed by event-related brainpotentials. Human Factors, 29, 195–211.

Marshall, R. S., Ferrera, J. J., Barnes, A., Xian, Z.,O'Brian, K. A., Chmayssani, M., et al. (2008). Brain activityassociated with stimulation therapy of the visual borderzonein hemianopic stroke patients. Neurorehabilitation and Neu-ral Repair, 22, 136–144.

Marshall, R. S., Chmayssani, M., O’Brian, K. A., Handy, C. &Greenstein, V. C. (2010) Visual field expansion after visualrestoration therapy. Clin Rehabil, 24, 1027–1035.

Martinez, A., Anllo-Vento, L., Sereno, M. I., Frank, L. R.,Buxton, R. B., Dubowitz, D. J., et al. (1999). Involvementof striate and extrastriate visual cortical areas in spatialattention. Nature Neuroscience, 2, 364–369.

McManus, J. N., Ullman, S., & Gilbert, C. D. (2008). Acomputational model of perceptual fill-in following retinaldegeneration. Journal of Neurophysiology, 99, 2086–2100.

Mendola, J. D., Conner, I. P., Sharma, S., Bahekar, A., &Lemieux, S. (2006). fMRI measures of perceptual filling-inin the human visual cortex. Journal of Cognitive Neurosci-ence, 18, 363–375.

Milleret, C., & Buser, P. (1984). Receptive field sizes andresponsiveness to light in area 18 of the adult cat afterchiasmotomy. Postoperative evolution; role of visual experi-ence. Experimental Brain Research, 57, 73–81.

Mitchell, D. E., Murphy, K. M., & Kaye, M. G. (1984). Thepermanence of the visual recovery that follows reverseocclusion of monocularly deprived kittens. InvestigativeOphthalmology & Visual Science, 25, 908–917.

Mizobe, K., Polat, U., Pettet, M. W., & Kasamatsu, T. (2001).Facilitation and suppression of single striate-cell activity byspatially discrete pattern stimuli presented beyond thereceptive field. Visual Neuroscience, 18, 377–391.

Mohler, C. W., & Wurtz, R. H. (1977). Role of striate cortexand superior colliculus in visual guidance of saccadic eyemovements in monkeys. Journal of Neurophysiology, 40,74–94.

Moore, T., Rodman, H. R., Repp, A. B., Gross, C. G., &Mezrich, R. S. (1996). Greater residual vision in monkeysafter striate cortex damage in infancy. Journal of Neuro-physiology, 76, 3928–3933.

Mueller, I., Gall, C., Kasten, E., & Sabel, B. A. (2008). Long-term learning of visual functions in patients after braindamage. Behavioural Brain Research, 191, 32–42.

Mueller, I., Mast, H., & Sabel, B. A. (2007). Recovery of visualfunction after brain injury: A large-sample study usingVision Restoration Therapy. Restorative Neurology andNeuroscience, 25, 563–572.

Mueller, I., Poggel, D. A., Kenkel, S., Kasten, E., &Sabel, B. A. (2003). Vision Restoration Therapy (VRT)after brain damage: Subjective improvements of activitiesof daily life and their relationship to visual fieldenlargements. Visual Impairment Research, 5, 157–178.

Mueller, I., Sabel, B. A., & Kasten, E. (2006). Comparison ofearly and late rehabilitation of stroke and cerebral traumapatients with visual field defects. Der Nervenarzt, 77,694–701.

Murakami, I., Komatsu, H., & Kinoshita, M. (1997). Percep-tual filling-in at the scotoma following a monocular retinallesion in the monkey. Visual Neuroscience, 14, 89–101.

257

Nakayama, K., & Mackeben, M. (1989). Sustained and tran-sient components of focal visual attention. Vision Research,29, 1631–1647.

Nelles, G., de Greiff, A., Pscherer, A., Forsting, M.,Gerhard, H., Esser, J., et al. (2007). Cortical activation inhemianopia after stroke. Neuroscience Letters, 426, 34–38.

Nelles, G., Pscherer, A., de Greiff, A., Gerhard, H.,Forsting, M., Esser, J., et al. (2010). Eye-movement train-ing-induced changes of visual field representation in patientswith post-stroke hemianopia. Journal of Neurology, 257,1832–1840.

Nelles, G., Widman, G., de Greiff, A., Meistrowitz, A.,Dimitrova, A., Weber, J., et al. (2002). Brain representationof hemifield stimulation in poststroke visual field defects.Stroke, 33, 1286–1293.

Newsome, W. T., Wurtz, R. H., Dürsteler, M. R., &Mikami, A. (1985). Punctate chemical lesions of striate cor-tex in macaque monkeys: Effects on visually guidedsaccades. Experimental Brain Research, 58, 392–399.

Nilsson, U. L., Frennesson, C., & Nilsson, S. E. (1998). Loca-tion and stability of a newly established eccentric retinallocus suitable for reading, achieved through training ofpatients with a dense central scotoma. Optometry and VisionScience, 75, 873–878.

Nilsson, U. L., Frennesson, C., & Nilsson, S. E. (2003).Patients with AMD and a large absolute central scotomacan be trained successfully to use eccentric viewing, asdemonstrated in a scanning laser ophthalmoscope. VisionResearch, 43, 1777–1787.

Noppeney, U. (2007). The effects of visual deprivation onfunctional and structural organization of the human brain.Neuroscience and Biobehavioral Reviews, 31, 1169–1180.

Ostrovsky, Y., Andalman, A., & Sinha, P. (2006). Visionfollowing extended congenital blindness. PsychologicalScience, 17, 1009–1014.

Ostrovsky, Y., Meyers, E., Ganesh, S., Mathur, U., & Sinha, P.(2009). Visual parsing after recovery from blindness. Psy-chological Science, 20, 1484–1491.

Palagina, G., Eysel, U. T., & Jancke, D. (2009). Strengtheningof lateral activation in adult rat visual cortex after retinallesions captured with voltage-sensitive dye imaging in vivo.Proceedings of the National Academy of Sciences of theUnited States of America, 106, 8743–8747.

Pambakian, A. L., Currie, J., & Kennard, C. (2005). Rehabili-tation strategies for patients with homonymous visual fielddefects. Journal of Neuroophthalmology, 25, 136–142.

Pambakian, A. L., & Kennard, C. (1997). Can visual functionbe restored in patients with homonymous hemianopia?The British Journal of Ophthalmology, 81, 324–328.

Papageorgiou, E., Hardiess, G., Schaeffel, F., Wiethoelter, H.,Karnath, H. O., Mallot, H., et al. (2007). Assessment ofvision-related quality of life in subjects with homonymous

visual field defects. Graefe's Archive for Clinical and Exper-imental Ophthalmology, 245, 1749–1758.

Paramei, G. V., & Sabel, B. A. (2008). Contour integrationdeficits on the intact side of the visual field in hemianopicpatients. Behavioural Brain Research, 188, 109–124.

Park, H. J., Jeong, S. O., Kim, E. Y., Kim, J. I., Park, H.,Oh, M. K., et al. (2007). Reorganization of neural circuitsin the blind on diffusion direction analysis. Neuroreport,18, 1757–1760.

Pasik, T., & Pasik, P. (1973). Extrageniculostriate vision in themonkey. IV. Critical structures for light vs. no-light discrim-ination. Brain Research, 56, 165–182.

Pavlidis, M., Stupp, T., Naskar, R., Cengiz, C., & Thanos, S.(2003). Retinal ganglion cells resistant to advanced glau-coma: A post mortem study of human retinas with the car-bocyanine dye DiI. Investigative Ophthalmology & VisualScience, 44, 5196–5205.

Payne, B. R., Lomber, S. G., MacNeil, M. A., & Cornwell, P.(1996). Evidence for greater sight in blindsight followingdamage of primary visual cortex early in life.Neuropsychologia, 34, 741–774.

Poggel, D. A., Kasten, E., Müller-Oehring, E. M.,Bunzenthal, U., & Sabel, B. A. (2006). Improving residualvision by attentional cueing in patients with brain lesions.Brain Research, 1097, 142–148.

Poggel, D. A., Kasten, E., Müller-Oehring, E. M., Sabel, B. A.,& Brandt, S. A. (2001). Unusual spontaneous and traininginduced visual field recovery in a patient with a gunshotlesion. Journal of Neurology, Neurosurgery and Psychiatry,70, 236–239.

Poggel, D. A., Kasten, E., & Sabel, B. A. (2004). Attentionalcueing improves vision restoration therapy in patients withvisual field loss. Neurology, 63, 2069–2076.

Poggel, D. A., Mueller, I., Kasten, E., Bunzenthal, U., &Sabel, B. A. (2010). Subjective and objective outcomemeasures of computer-based vision restoration training.NeuroRehabilitation, 27, 173–187.

Poggel, D. A., Mueller, I., Kasten, E., & Sabel, B. A. (2008).Multifactorial predictors and outcome variables of vision res-toration training in patients with post-geniculate visual fieldloss. Restorative Neurology and Neuroscience, 26, 321–339.

Poggel, D. A., Müller-Oehring, E. M., Gothe, J., Kenkel, S.,Kasten, E., & Sabel, B. A. (2007). Visual hallucinations dur-ing spontaneous and training-induced visual field recovery.Neuropsychologia, 45, 2598–2607.

Polat, U. (1999). Functional architecture of long-range percep-tual interactions. Spatial Vision, 12, 143–162.

Polat, U. (2008). Restoration of underdeveloped corticalfunctions: Evidence from treatment of adult amblyopia.Restorative Neurology and Neuroscience, 26, 413–424.

Polat, U., Ma-Naim, T., Belkin, M., & Sagi, D. (2004). Improv-ing vision in adult amblyopia by perceptual learning.

258

Proceedings of the National Academy of Sciences of theUnited States of America, 101, 6692–6697.

Polat, U., Ma-Naim, T., & Spierer, A. (2009). Treatment ofchildren with amblyopia by perceptual learning. VisionResearch, 49, 2599–2603.

Polat, U., & Sagi, D. (1994). Spatial interactions in humanvision: From near to far via experience-dependent cascadesof connections. Proceedings of the National Academy ofSciences of the United States of America, 91, 1206–1209.

Polat, U., & Sagi, D. (2006). Temporal asymmetry of collinearlateral interactions. Vision Research, 46, 953–960.

Polat, U., Sagi, D., & Norcia, A. M. (1997). Abnormal long-range spatial interactions in amblyopia. Vision Research,37, 737–744.

Pollen, D. A. (1977). Responses of single neurons to electricalstimulation of the surface of the visual cortex. Brain, Behav-ior and Evolution, 14, 67–86.

Pöppel, E., Held, R., & Frost, D. (1973). Residual visual func-tion after brain wounds involving the central visualpathways in man. Nature, 243, 295–296.

Pöppel, E., & Richards, W. (1974). Light sensitivity in corticalscotomata contralateral to small islands of blindness. Exper-imental Brain Research, 21, 125–130.

Poppelreuter, W. (1917). Die psychischen Schädigungen durchKopfschuss im Kriege 1914–1916. Bd. I. Die Störungen derniederen und höheren Sehleistungen durch Verletzungen desOkzipitalhirns. Leipzig: L. Voss.

Posner, M. I. (1980). Orienting of attention. The QuarterlyJournal of Experimental Psychology, 32, 3–25.

Prieto-Diaz, J. S.-D. C. (2000). Strabismus (4th ed.). Boston:Butterworth-Heinemann.

Prilloff, S., Henrich-Noack, P., Kropf, S., & Sabel, B. A.(2010). Experience-dependent plasticity and vision restora-tion in rats after optic nerve crush. Journal of Neurotrauma,27, 2295–2307.

Prilloff, S., Noblejas, M. I., Chedhomme, V., & Sabel, B. A.(2007). Two faces of calcium activation after optic nervetrauma: Life or death of retinal ganglion cells in vivodepends on calcium dynamics. The European Journal ofNeuroscience, 25, 3339–3346.

Ptito, M., Fumal, A., de Noordhout, A. M., Schoenen, J.,Gjedde, A., & Kupers, R. (2008). TMS of the occipital cor-tex induces tactile sensations in the fingers of blind Braillereaders. Experimental Brain Research, 184, 193–200.

Ptito, M., & Kupers, R. (2005). Cross-modal plasticity in earlyblindness. Journal of Integrative Neuroscience, 4, 479–488.

Radvay, X., Duhoux, S., Koenig-Supiot, F., & Vital-Durand, F.(2007). Balance training and visual rehabilitation of age-related macular degeneration patients. Journal of VestibularResearch, 17, 183–193.

Raemaekers, M., Bergsma, D. P., van Wezel, R. J., van derWildt, G. J., & van den Berg, A. V. (2011). Effects of visionrestoration training on early visual cortex in patients with

cerebral blindness investigated with functional magnetic res-onance imaging. Journal of Neurophysiology, 105, 872–882.

Ramrattan, R. S., Wolfs, R. C. W., Panda-Jonas, S.,Jonas, J. B., Bakker, D., Pols, H. A., et al. (2001). Preva-lence and causes of visual field loss in the elderly andassociations with impairment in daily functioning. Archivesof Ophthalmology, 119, 1788–1794.

Raninen, A., Vanni, S., Hyvärinen, L., & Näsänen, R. (2007).Temporal sensitivity in a hemianopic visual field can beimproved by long-term training using flicker stimulation. Jour-nal of Neurology, Neurosurgery and Psychiatry, 78, 66–73.

Rausch, M., Widdig, W., Eysel, U. T., Penner, I. K., &Tegenthoff, M. (2000). Enhanced responsiveness of humanextra visual areas to photic stimulation in patients with severelyreduced vision.Experimental Brain Research, 135, 34–40.

Reinhard, J., Schreiber, A., Schiefer, U., Kasten, E.,Sabel, B. A., Kenkel, S., et al. (2005). Does visual restitutiontraining change absolute homonymous visual field defects?A fundus controlled study. The British Journal of Ophthal-mology, 89, 30–35.

Riddoch, G. (1917). Dissociation of visual perceptions due tooccipital injuries with special reference to appreciation ofmovement. Brain, 40, 15–57.

Riesen, A. H. (1961). Excessive arousal effects of stimulationafter early sensory deprivation. In P. Solomon, P. E.Kubzansky, P. H. Leiderman, J. Mendalson & D. Wexler(Eds.), Sensory deprivation (pp. 34–40). Cambridge, MA:Harvard University Press.

Romano, J. G., Schulz, P., Kenkel, S., & Todd, D. P. (2008).Visual field changes after a rehabilitation intervention:Vision restoration therapy. Journal of the NeurologicalSciences, 273, 70–74.

Romei, V., Brodbeck, V., Michel, C., Amedi, A., Pascual-Leone, A., & Thut, G. (2008a). Spontaneous fluctuationsin posterior alpha-band EEG activity reflect variability inexcitability of human visual areas. Cerebral Cortex, 18,2010–2018.

Romei, V., Rihs, T., Brodbeck, V., & Thut, G. (2008b). Rest-ing electroencephalogram alpha-power over posterior sitesindexes baseline visual cortex excitability. Neuroreport, 19,203–208.

Roth, T., Sokolov, A. N., Messias, A., Roth, P., Weller, M., &Trauzettel-Klosinski, S. (2009). Comparing explorativesaccade and flicker training in hemianopia: A randomizedcontrolled study. Neurology, 72, 324–331.

Rousseau, V., Engelmann, R., & Sabel, B. A. (1999). Restora-tion of vision III: Soma swelling dynamics predicts neuronaldeath or survival after optic nerve crush in vivo.Neuroreport, 10, 3387–3391.

Rousseau, V., & Sabel, B. A. (2001). Restoration of vision IV:Compensatory soma size increase of retinal ganglion cellspredicts recovery of vision after partial optic nerve crush.Restorative Neurology and Neuroscience, 18, 177–189.

259

Russ, M. O., Cleff, U., Lanfermann, H., Schalnus, R.,Enzensberger, W., & Kleinschmidt, A. (2002). Functionalmagnetic resonance imaging in acute unilateral opticneuritis. Journal of Neuroimaging, 12, 339–350.

Sabel, B. A. (1997). Unrecognized potential of survivingneurons: Within-systems plasticity, recovery of functionand the hypothesis of the minimal residual structure. TheNeuroscientist, 3, 366–370.

Sabel, B. A. (1999). Restoration of vision I: Neurobiologicalmechanisms of restoration and plasticity after brain damage—Areview.RestorativeNeurologyandNeuroscience,15, 177–200.

Sabel, B. A., Fedorov, A. B., Hermann, C., & Gall, C. (2010).Restoration of vision. Non-invasive current stimulation forthe treatment of visual field defects in optic neuropathy -a single–center prospective trial, World OphthalmologyCongress, Berlin, Germany. June 5–9.

Sabel, B. A., & Kasten, E. (2000). Restoration of vision bytraining of residual functions. Current Opinion in Ophthal-mology, 11, 430–436.

Sabel, B. A., Kasten, E., & Kreutz, M. R. (1997). Recovery ofvision after partial visual system injury as a model of post-lesion neuroplasticity. Advances in Neurology, 73, 251–276.

Sabel, B. A., Kenkel, S., & Kasten, E. (2004). Vision restora-tion therapy (VRT) efficacy as assessed by comparative per-imetric analysis and subjective questionnaires. RestorativeNeurology and Neuroscience, 22, 399–420.

Sabel, B. A., Sautter, J., Stoehr, T., & Siliprandi, R. A. (1995).A behavioural model of excitotoxicity: Retinal degenera-tion, loss of vision, and subsequent recovery after intraocu-lar NMDA administration in adult rats. ExperimentalBrain Research, 106, 93–105.

Sabel, B. A., & Trauzettel-Klosinski, S. (2005). Improvingvision in a patient with homonymous hemianopia. Journalof Neuroophthalmology, 25, 143–149.

Sadato, N. (2005). How the blind “see” Braille: Lessons fromfunctional magnetic resonance imaging. The Neuroscientist,11, 577–582.

Sahraie, A., MacLeod, M. J., Trevethan, C. T., Robson, S. E.,Olson, J. A., Callaghan, P., et al. (2010). Improved detectionfollowing Neuro-Eye Therapy in patients with post-genicu-late brain damage. Experimental Brain Research, 206, 25–34.

Sahraie, A., Trevethan, C. T., MacLeod, M. J., Murray, A. D.,Olson, J. A., & Weiskrantz, L. (2006). Increased sensitivityafter repeated stimulation of residual spatial channels inblindsight. Proceedings of the National Academy of Sciencesof the United States of America, 103, 14971–14976.

Sakaguchi, H., Fujikado, T., Kanda, H., Osanai, M.,Fang, X. Y., Nakauchi, K., et al. (2004). Electrical stimulationwith a needle type electrode placed into the optic nerve inrabbit eyes. Japanese Journal of Ophthalmology, 48, 552–557.

Sakaguchi, H., Kamei, M., Fujikado, T., Yonezawa, E.,Ozawa, M., Cecilia-Gonzalez, C., et al. (2009). Artificialvision by direct optic nerve electrode (AV-DONE)

implantation in a blind patient with retinitis pigmentosa.Journal of Artificial Organs, 12, 206–209.

Sale, A., De Pasquale, R., Bonaccorsi, J., Pietra, G., Oliveri, D.,Berardi, N., et al. (2010). Visual perceptual learning inducesLTP in the visual cortex. Neuroscience, 172, 219–225.

Sale, A., Maya Vetencourt, J. F., Medini, P., Cenni, M. C.,Baroncelli, L., De Pasquale, R., et al. (2007). Environmentalenrichment in adulthood promotes amblyopia recoverythrough a reduction of intracortical inhibition. NatureNeuroscience, 10, 679–681.

Sanders, M. D., Warrington, E. K., Marshall, J., &Weiskrantz, L. (1974). ‘Blindsight’: Vision in a field defect.Lancet, 1, 707–708.

Sautter, J., & Sabel, B. A. (1993). Recovery of brightness discrim-ination in adult rats despite progressive loss of retrogradelylabelled retinal ganglion cells after controlled optic nervecrush. The European Journal of Neuroscience, 5, 680–690.

Sautter, J., Schwartz, M., Duvdevani, R., & Sabel, B. A. (1991).GM1 ganglioside treatment reduces visual deficits after gradedcrush of the rat optic nerve. Brain Research, 565, 23–33.

Schadow, J., Dettler, N., Paramei, G. V., Lenz, D., Fründ, I.,Sabel, B. A., et al. (2009). Impairments of Gestalt perceptionin the intact hemifield of hemianopic patients are reflected ingamma-band EEG activity. Neuropsychologia, 47, 556–568.

Schendel, K., & Robertson, L. C. (2004). Reaching out to see:Arm position can attenuate human visual loss. Journal ofCognitive Neuroscience, 16, 935–943.

Schmidt, E. M., Bak, M. J., Hambrecht, F. T., Kufta, C. V.,Rourke, D. K. O., & Vallabhanath, P. (1996). Feasibility ofa visual prosthesis for the blind based on intracorticalmicrostimulation of the visual cortex. Brain, 119, 507–522.

Schmielau, F., & Wong, E. K. Jr. (2007). Recovery of visualfields in brain-lesioned patients by reaction perimetry treat-ment. Journal of Neuroengineering and Rehabilitation, 4, 31.

Schmitt,U.,&Sabel, B.A. (1996a). Basic fibroblast growth factortreatment protects from visual deficits but does not increaseretinal ganglion cell survival following controlled optic nervecrush. Restorative Neurology and Neuroscience, 10, 61–68.

Schmitt, U., & Sabel, B. A. (1996b). MK-801 increases retinalganglion cell death but reduces visual deficits after controlledoptic nerve crush. Journal of Neurotrauma, 13, 791–800.

Schmitt, U., Sabel, B. A., Cross, R., Samson, F. E., &Pazdernik, T. L. (1998). Recovery of metabolic activity inretinofugal targets after traumatic optic nerve injury is inde-pendent of retinofugal input. Restorative Neurology andNeuroscience, 13, 153–161.

Schneider, G. E. (1969). Two visual systems. Brainmechanisms for localization and discrimination are disso-ciated by tectal and cortical lesions. Science, 163, 895–902.

Schoenfeld, M. A., Noesselt, T., Poggel, D., Tempelmann, C.,Hopf, J.-M., Woldorff, M. G., et al. (2002). Analysis ofpathways mediating preserved vision after striate cortexlesions. Annals of Neurology, 52, 814–824.

260

Schuchard, R. A., & Fletcher, D. C. (1994). Preferred retinallocus. A review with applications in low vision rehabilita-tion. Ophthalmology Clinics of North America, 7, 243–256.

Schumacher, E. H., Jacko, J. A., Primo, S. A., Main, K. L.,Moloney, K. P., Kinzel, E. N., et al. (2008). Reorganizationof visual processing is related to eccentric viewing inpatients with macular degeneration. Restorative Neurologyand Neuroscience, 26, 391–402.

Segraves, M. A., Goldberg, M. E., Deng, S., Bruce, C. J.,Ungerleider, L. G., & Mishkin, M. (1987). The role of striatecortex in the guidance of eye movement in the monkey. TheJournal of Neuroscience, 7, 3040–3058.

Smirnakis, S. M., Brewer, A. A., Schmid, M. C., Tolias, A. S.,Schüz, A., Augath, M., et al. (2005). Lack of long-term cor-tical reorganization after macaque retinal lesions. Nature,435, 300–307.

Smith, D. C., & Holdefer, R. N. (1985). Binocular competitiveinteractions and recovery of visual acuity in long-term mon-ocularly deprived cats. Vision Research, 25, 1783–1794.

Sober, A. J., Stark, J. M., Yamasaki, D. S., & Lytton, W. W.(1997). Receptive field changes after strokelike corticalablation: A role for activation dynamics. Journal of Neuro-physiology, 78, 3438–3443.

Somers, D. C., Dale, A. M., Seiffert, A. E., & Tootell, R. B. H.(1999). Functional MRI reveals spatially specific attentionalmodulation in human primary visual cortex. Proceedings ofthe National Academy of Sciences of the United States ofAmerica, 96, 1663–1668.

Spear, P. D., & Barbas, H. (1975). Recovery of pattern dis-crimination ability in rats receiving serial or one-stage visualcortex lesions. Brain Research, 94, 337–346.

Spear, P. D., & Ganz, L. (1975). Effects of visual cortex lesionsfollowing recovery from monocular deprivation in the cat.Experimental Brain Research, 23, 181–201.

Sprague, J. M. (1966). Interaction of cortex and superiorcolliculus in mediation of visually guided behavior in thecat. Science, 153, 1544–1547.

Stein, D. G., & Weinberg, D. (1978). Impairment and recoveryof visual functions after bilateral lesions of superiorcolliculus. Physiology & Behavior, 20, 323–329.

Stoerig, P. (1993). Sources of blindsight. Science, 26, 493–494.Stoerig, P. (2006). Blindsight, conscious vision, and the role of pri-mary visual cortex. Progress in Brain Research, 155, 217–234.

Stoerig, P. (2008). Functional rehabilitation of partial corticalblindness? Restorative Neurology and Neuroscience, 26,291–303.

Stoerig, P., & Cowey, A. (1997). Blindsight in man and mon-key. Brain, 120, 535–559.

Tan, C. S., & Sabel, B. A. (2006). Dynamic changes in visualacuity as the pathophysiologic mechanism in Charles Bon-net syndrome (visual hallucinations). European Archives ofPsychiatry and Clinical Neuroscience, 256, 62–63.

Tan, C. S., Sabel, B. A., & Goh, K. Y. (2006). Visualhallucinations during visual recovery after central retinalartery occlusion. Archives of Neurology, 63, 598–600.

Teuber, H.-L. (1975). Effects of focal brain injury on humanbehavior. Nervous System, 2, 457–480.

Teuber, H.-L., Battersby, W. S., & Bender, M. B. (1960).Visual field defects after penetrating missile wounds of thebrain. Cambridge, MA: Harvard University Press.

Tieman, S. B., & Hirsch, H. V. (1983). Removal of the more-experienced eye decreases visual field deficits in cats rearedwith unequal alternative monocular exposure. BrainResearch, 271, 170–173.

Toosy, A. T., Hickman, S. J., Miszkiel, K. A., Jones, S. J.,Plant, G. T., Altmann, D. R., et al. (2005). Adaptive corticalplasticity in higher visual areas after acute optic neuritis.Annals of Neurology, 57, 622–633.

Toosy, A. T., Werring, D. J., Bullmore, E. T., Plant, G. T.,Barker, G. J., Miller, D. H., et al. (2002). Functional mag-netic resonance imaging of the cortical response to photicstimulation in humans following optic neuritis recovery.Neuroscience Letters, 330, 255–259.

Treisman, A., & Gelade, G. (1980). A feature-integration the-ory of attention. Cognitive Psychology, 12, 97–136.

Urbaitis, J. C., & Meikle, T. H., Jr., (1968). Relearning a dark-light discrimination by cats after cortical and collicularlesions. Experimental Neurology, 20, 295–311.

Van Essen, D. C., & Maunsell, J. H. R. (1980). Two-dimen-sional maps of the cerebral cortex. The Journal of Compar-ative Neurology, 191, 255–281.

Van Hoff-van Duin, J. (1976). Development of visuomotorbehavior in normal and dark-reared cats. Brain Research,104, 233–241.

Von Monakow, C. V. (1914). Die Lokalisation in derGroßhirnrinde und der Abbau der Funktion durch kortikaleHerde. Wiesbaden: J.F. Bergmann.

Von Noorden, G. K. (1981). New clinical aspects of stimulusdeprivation amblyopia. American Journal of Ophthalmol-ogy, 92, 416–421.

Voronin, L., Byzov, A., Kleschevnikov, A., Kozhemyakin, M.,Kuhnt, U., & Volgushev, M. (1995). Neurophysiologicalanalysis of long-term potentiation in mammalian brain.Behavioural Brain Research, 66, 45–52.

Waleszczyk, W. J., Wang, C., Young, J. M., Burke, W.,Calford, M. B., & Dreher, B. (2003). Laminar differencesin plasticity in area 17 following retinal lesions in kittens oradult cats. The European Journal of Neuroscience, 17,2351–2368.

Wallace, S. F., Rosenquist, A. C., & Sprague, J. M. (1989).Recovery from cortical blindness mediated by destructionof nontectal fibers in the commissure of the superiorcolliculus in the cat. The Journal of Comparative Neurology,284, 429–450.

261

Watson, G. R., Schuchard, R. A., De l`Aune, W. R., &Watkins, E. (2006). Effects of preferred retinal locus place-ment on text navigation and development of advantageoustrained retinal locus. Journal of Rehabilitation Researchand Development, 43, 761–770.

Weiskrantz, L. (1996). Blindsight revisited. Current Opinion inNeurobiology, 6, 215–220.

Weiskrantz, L. (2009). Is blindsight just degraded normalvision? Experimental Brain Research, 192, 413–416.

Weiskrantz, L., Warrington, E. K., Sanders, M. D., &Marshall, J. (1974). Visual capacity in the hemianopic fieldfollowing a restricted occipital ablation. Brain, 97, 709–728.

Werring, D. J., Bullmore, E. T., Toosy, A. T., Miller, D. H.,Barker, G. J., MacManus, D. G., et al. (2000). Recoveryfrom optic neuritis is associated with a change in the distri-bution of cerebral response to visual stimulation: A func-tional magnetic resonance imaging study. Journal ofNeurology, Neurosurgery and Psychiatry, 68, 441–449.

Werth, R. (2008). Cerebral blindness and plasticity of thevisual system in children. A review of visual capacities inpatients with occipital lesions, hemispherectomy orhydranencephaly. Restorative Neurology and Neuroscience,26, 377–389.

Werth, R., & Moehrenschlager, M. (1999). The developmentof visual functions in cerebrally blind children during a sys-tematic visual field training. Restorative Neurology and Neu-roscience, 15, 229–241.

Werth, R., & Seelos, K. (2005). Restitution of visual functionsin cerebrally blind children. Neuropsychologia, 43,2011–2023.

Wessinger, C. M., Fendrich, R., & Gazzaniga, M. S. (1997).Islands of residual vision in hemianopic patients. Journalof Cognitive Neuroscience, 9, 203–221.

Wick, B., Wingard, M., Cotter, S., & Scheiman, M. (1992).Anisometropic amblyopia: Is the patient ever too old totreat? Optometry and Vision Science, 69, 866–878.

Widdig, W., Pleger, B., Rommel, O., Malin, J. P., &Tegenthoff, M. (2003). Repetitive visual stimulation: A neu-ropsychological approach to the treatment of cortical blind-ness. NeuroRehabilitation, 18, 227–237.

Wiesel, T. N., & Hubel, D. H. (1965). Extent of recovery fromthe effects of visual deprivation in kittens. Journal of Neuro-physiology, 28, 1060–1072.

Wolford, G., Marchak, F., & Hughes, H. (1988). Practiceeffects in backward masking. Journal of Experimental Psy-chology. Human Perception and Performance, 14, 101–112.

Wood, C. C., Spear, P. D., & Braun, J. J. (1974). Effects ofsequential lesions of suprasylvian gyri and visual cortex onpattern discrimination in the cat. Brain Research, 66,443–466.

Wörgötter, F., Suder, K., Zhao, Y., Kerscher, N., Eysel, U. T.,& Funke, K. (1998). State-dependent receptive-fieldrestructuring in the visual cortex. Nature, 396, 165–168.

Wüst, S., Kasten, E., & Sabel, B. A. (2002). Blindsight afteroptic nerve injury indicates functionality of spared fibers.Journal of Cognitive Neuroscience, 14, 243–253.

Young, J. M., Waleszczyk, W. J., Burke, W., Calford, M. B., &Dreher, B. (2002). Topographic reorganization in area 18 ofadult cats following circumscribed monocular retinal lesionsin adolescence. Journal of Physiology, London, 541,601–612.

Young, J. M., Waleszczyk, W. J., Wang, C., Calford, M. B.,Dreher, B., & Obermayer, K. (2007). Cortical reorganiza-tion consistent with spike timing-but not correlation-depen-dent plasticity. Nature Neuroscience, 10, 887–895.

Zaehle, T., Rach, S., & Herrmann, C. S. (2010). Transcranialalternating current stimulation enhances individual alphaactivity in human EEG. PLoS ONE, 5, e13766.

Zee, D. S., Butler, P. H., Optican, L. M., Tusa, R. J., &Gücer, G. (1983). Effects of bilateral occipital lobectomieson eye movements in monkeys: Preliminary observations.In A. Roucoux & M. Crommelink (Eds.), Physiologicaland pathological aspects of eye movements (pp. 225–232).Boston: Junk.

Zeki, S., & Ffytche, D. H. (1998). The Riddoch syndrome:Insights into the neurobiology of conscious vision. Brain,121, 24–45.

Zhang, X., Kedar, S., Lynn, M. J., Newman, N. J., &Biousse, V. (2006). Natural history of homonymoushemianopia. Neurology, 66, 901–905.

Zihl, J., Pöppel, E., & von Cramon, D. (1977). Diurnal varia-tion of visual field size in patients with postretinal lesions.Experimental Brain Research, 27, 245–249.

Zihl, J., & von Cramon, D. (1979). Restitution of visual func-tion in patients with cerebral blindness. Journal of Neurol-ogy, Neurosurgery and Psychiatry, 42, 312–322.

Zihl, J., & von Cramon, D. (1985). Visual field recovery fromscotoma in patients with postgeniculate damage. A reviewof 55 cases. Brain, 108, 335–365.

Zur, D., & Ullman, S. (2003). Filling-in of retinal scotomas.Vision Research, 43, 971–982.

262

183_Sabel_2011

Documents

Transcript of 183_Sabel_2011