3. Degeneración en el lóbulo frontotemporal

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Fear conditioning in frontotemporal lobardegeneration and Alzheimer’s disease

M. Hoefer,1,2 S. C. Allison,1,2 G. F. Schauer,1,2 J. M. Neuhaus,3 J. Hall,1,2 J. N. Dang,4 M. W. Weiner,1,5,6

B. L. Miller1,2 and H. J. Rosen1,2

1University of California at San Francisco Department of Neurology, 2USCF Memory and Aging Center, 3UCSF Department

of Epidemiology and Biostatistics, 4UCSF School of Pharmacy, 5San Francisco Veterans Affairs Hospital Magnetic Resonance

Imaging Unit and 6UCSF Department of Radiology, San Francisco, CA, USA

Correspondence to: Howard J. Rosen, UCSF Department of Neurology, Memory and Aging Center, 350 Parnassus Ave.,

Box 1207, Suite 706, San Francisco, CA 94143-1207, USA

E-mail: [email protected]

Emotional blunting and abnormal processing of rewards and punishments represent early features of fronto-

temporal lobar degeneration (FTLD). Better understanding of the physiological underpinnings of these

emotional changes can be facilitated by the use of classical psychology approaches. Fear conditioning (FC) isan extensively used paradigm for studying emotional processing that has rarely been applied to the study of

dementia.We studied FC in controls (n= 25), Alzheimer’s disease (n= 25) and FTLD (n= 25). A neutral stimulus

(coloured square on a computer screen) was repeatedly paired with a 1s burst of 100 db white noise. Change in

skin conductance response to the neutral stimulus was used to measure conditioning. Physiological^anatomical

correlations were examined using voxel-based morphometry (VBM). Both patient groups showed impaired

acquisition of conditioned responses. However, the basis for this deficit appeared to differ between groups.

In Alzheimer’s disease, impaired FC occurred despite normal electrodermal responses to the aversive stimulus.

In contrast, FTLD patients showed reduced skin conductance responses to the aversive stimulus, which contrib-

uted significantly to their FC deficit. VBM identified correlations with physiological reactivity in the amygdala,

anterior cingulate cortex, orbitofrontal cortex and insula. These data indicate that Alzheimer’s disease and

FTLD both show abnormalities in emotional learning, but they suggest that in FTLD this is associated with a

deficit in basic electrodermal response to aversive stimuli, consistent with the emotional blunting described

with this disorder. Deficits in responses to aversive stimuli could contribute to both the behavioural and cognitivefeatures of FTLD and Alzheimer’s disease. Further study of FC in humans and animal models of dementia could

provide a valuable window into these symptoms.

Keywords: frontotemporal lobar degeneration; Alzheimer’s disease; emotion; fear conditioning

Abbreviations: ACC = anterior cingulate cortex; CS = conditioned stimulus; FC = fear conditioning; FTD = frontotemporal

dementia; F TLD= frontotemporal lobar degeneration; GDS= Geriatric Depression Scale; OFC = orbitofrontal cortex;

ROI = regions of interest; SCL = skin conductance level; SCR = skin conductance response; SD= semantic dementia;

US = unconditioned stimulus; VBM = voxel-based morphometry

Received September 22, 2007. Revised March 4, 2008. Accepted April 11, 2008. Advance Access publication May 20, 2008

Introduction

Emotional problems are common in neurodegenerative

disease, with symptoms ranging from depression, apathy

and emotional blunting to anxiety, irritability and agitation

(Cummings, 1997). In some disorders, such as frontotem-

poral dementia (FTD), social and emotional problems repre-

sent early signs and core features of the illness for diagnosis

(Neary et al ., 1998; McKhann et al ., 2001). The diagnostic

implications of emotional problems in neurodegenerative

disease and their contribution to morbidity underscore the

need for a deeper understanding of their origins.Improved understanding of emotional dysfunction in

dementia may come from the study of processes whose

neurophysiological substrates are well-understood in ani-

mals, such as simple conditioning paradigms. The advan-

tages of conditioning are two-fold. Unlike verbally mediated

doi:10.1093/brain/awn082 Brain (2008), 131, 1646 ^1657

The Author (2008).Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: [email protected]



neuropsychological testing, conditioning can be easily applied to animal models of dementia. Second, if abnormalin humans, conditioning paradigms can be studied andunderstood in animals at a physiological and molecular level.

Fear conditioning (FC) is one of the most extensively used models for studying emotional processing in animals.

This paradigm, in which neutral stimuli are made to elicitfear responses through repetitive pairing with inherently aversive stimuli, represents an elemental process by whichthe brain’s emotional systems learn to anticipate threats inthe environment. Successful FC is dependent on a discreteset of frontal and temporal regions, including the amygdala,insula and ventromedial pre-frontal cortex, and diencepha-lic and brainstem structures that mediate physiological andbehavioural responses (LeDoux, 1992). Several fMRI andlesion studies have demonstrated that FC in humans isdependent on these same structures (Bechara et al ., 1995,1999; LaBar et al ., 1995, 1998; Buchel and Dolan, 2000;Phelps et al ., 2004). Although FC has been proposed as a

model for understanding primary psychiatric disorders,particularly anxiety (Phillips et al ., 2003b; Rauch et al .,2006), it has received little attention as means of studyingdementia. Yet, the key FC structures are commonly affectedin neurodegenerative disease. Frontotemporal lobar degen-eration (FTLD) is associated with amygdala, insula andorbitofrontal tissue loss (Rosen et al ., 2002; Liu et al ., 2004;Boccardi et al ., 2005). In Alzheimer’s disease, the amygdalais also a site of early involvement after the hippocampusand entorhinal cortex (Braak and Braak, 1991) andamygdala volumes are accordingly reduced (Barnes et al .,2006; Basso et al ., 2006; Markesbery et al ., 2006).

FTLD and Alzheimer’s disease differ clinically, withemotional blunting, loss of empathy, impaired socialinteractions and compulsive behaviours being early featuresin FTLD, while interpersonal behaviour is relatively wellpreserved in Alzheimer’s disease, although irritability andagitation often develop (Cummings, 1997; Liu et al ., 2004).These clinical differences suggest different abnormalities inthe emotional system, which might be revealed throughdirect assessment of emotional processing.

FC depends on a number of component processes,including auditory and visual processing of incomingstimuli, and basic physiological reactivity to aversivestimuli-functions known to be altered in aging (Labar

et al ., 2004). One prior study indicated that FC is impairedin Alzheimer’s disease patients who had no deficit inelectrodermal response to aversive sounds (Hamann et al .,2002), but no studies have examined conditioning in FTLD.The emotional blunting in FTLD suggests that physiologicalreactivity to aversive stimuli might be altered in thesepatients. This would impact FC, and could also haveimplications for emotional processing in general becausealtered processing of aversive stimuli may change one’sbehaviour towards them. The goal of the current study wasto compare the effects of FTLD and Alzheimer’s disease onFC, taking into account the basic processing underlying FC.

Two variants of FTLD were included: FTD and semanticdementia (SD). Both of these variants are associated withsignificant behavioural abnormalities and tissue loss in

orbitofrontal cortex (OFC), cingulate and insular cortex (Bozeat et al ., 2000; Snowden et al ., 2001; Liu et al ., 2004;

Rosen et al ., 2006).

MethodsParticipantsSeventy-five consecutively recruited individuals, including 25

patients with probable Alzheimer’s disease [13 men, 12 women,

mean age= 61.8 years (range = 50–77)], 25 with FTLD [17 men,

8 women, mean age = 63 years (range= 49–83)] and 25 healthy

older individuals [normal controls, 10 men, 15 women, mean

age = 66.8 years (range= 51–79)] participated. There were no

significant differences across groups for age or sex (Table 1).

Patients were diagnosed using published criteria (McKhann

et al ., 1984; Neary et al ., 1998) after a comprehensive evaluation at

the UCSF Memory and Aging Center including neurological

history and examination, nursing evaluation, laboratory evaluation

and neuropsychological assessment of memory, executive function,

language and mood (see subsequently). Twenty-one of the normal

controls underwent the same evaluation, and the other five were

spouses of patients or other individuals who did not undergo

formal evaluation but had no cognitive complaints and no history

of neurological or psychiatric disease.

FTLD is comprised of three clinical syndromes: FTD, SD and

progressive non-fluent aphasia (Neary et al ., 1998). For this ex-

periment, patients with FTD (n = 15) and SD (n = 10) were included

because they also share many social/emotional behavioural abnorm-

alities (Bozeat et al ., 2000; Snowden et al ., 2001; Liu et al ., 2004)

whereas progressive non-fluent aphasia patients show a less

prominent behavioural disturbance (Rosen et al ., 2006).

Briefly, the neuropsychological evaluation consists of the Mini-

Mental State Examination (Folstein et al ., 1975), and tests of

working memory (digit span backwards), verbal episodic memory

[California Verbal Learning Test (Delis et al ., 2000)], visual

episodic memory (memory for details of a modified Rey-

Osterrieth figure), visual-spatial function (copy of a modified

Rey-Osterrieth figure), confrontational naming [15 items from the

Boston Naming Test (Kaplan et al ., 1983)], phonemic (words

beginning with the letter ‘D’), semantic (animals) and non-verbal

fluency [novel designs (Delis et al ., 2001)] and visual-motor

sequencing [a modified version of the ‘Trails B’ test (Reitan,

1958)]. Other variables of interest collected at our clinical visits

were the Clinical Dementia Rating Scale score (Morris, 1997) that

measures functional impairment and is often used as a surrogateof disease severity, the Geriatric Depression Scale [GDS (Yesavage

et al ., 1983)] and the Neuropsychiatric Inventory, which assesses

behavioural dysfunction (Cummings, 1997).

The research protocol was approved by the UCSF committee on

human research and all subjects gave informed consent before

participating.

Psychophysiologic testing

OverviewDuring the FC paradigm, two alternating neutral stimuli (coloured

squares on a computer monitor) were repetitively presented every

Conditioning in FTLD and Alzheimer’s disease Brain (2008), 131, 1646^1657 1647



16s over an 15-min experiment. The experiment proceeded in

three phases: habituation, where each of the stimuli were initially

presented four times, acquisition, where one of the neutral stimuli

(the conditioned stimulus, or CS+), was immediately followed by

an aversive sound presented through headphones (the uncondi-

tioned stimulus, or US) and the other (the CS) was not and

extinction, where the CS+ and CS were again repetitively

presented unaccompanied by the US. Figure 1 illustrates the

organization of the experiment and the creation of variables for

analysis.

StimuliThe CS+ and CS were usually blue and orange rectangles,

of equal luminance that occupied the entire computer screen

for 2 s. For a few subjects, green and red stimuli were used because

these subjects were also participating in a related experiment.

The colours used for the CS+ and CS were counterbalan-

ced across participants (within diagnostic group). The USwas a 1-s burst of 100 db white noise presented through

headphones.

Fig. 1 Graphic illustration of the experiment and creation of physiological variables. SCRdiff hab, SCRdiff ecq and SCRdiff ext are graphed inFig. 2. Note that no trials with a US are used to examine conditioning. Responses to trials containing a US are analysed separately andgraphed in Fig. 3 (for each presentation prior to and during the experiment) and Fig. 4 (averaged across the experiment).

Table 1 Demographics and neuropsychological test results in controls, Alzheimer’s disease, FTD and SD

Overall ANOVA Controls Mean (SD) AD Mean (SD) FTD Mean (SD) SD Mean (SD)

Age F (3, 73) = 1.51 66.7 (8.6) 62.0 (9.2) 62.3 (8.7) 64.6 (7.9)Males/females NS (2) 10/15 13/12 11/4 6/4Clinical Dementia Rating Scale (sum of boxes) F (3, 56) = 23.2 0.04 (0.1) 6.9 (3.0) ¥ 7.7 (3.9) ¥ 4.9 (1.8) ¥

Mini-Mental State Examination (max= 30) F (3, 73) = 11.1 29.7 (0.5) 21.4 (6.4) ¥ 20.3 (9.6) ¥ 22.1 (6.0) ¥

CVLT 100 free recall (max= 9) F (3, 43) = 11.6 7.3 (1.0) 0.8 (1.2) ¥ ,‰ 3.5 (2.8) ¥ 2.0 (2.9) ¥

Mod. Rey-O Delay (max = 17) F (3, 52) = 13.1 13.0(3.1) 3.0 (4.2) ¥ 7.5 (5.9) ¥ 6.2 (6.2) ¥

Digit span backwards F (3, 56) = 5.6

5.2 (1.5) 3.0 (1.3)

¥

3.9 (2.2) 4.3 (1.4)Modified trails #lines/min F (3, 50)=4.25 28.8 (7.8) 9.5 (14.8) ¥ 16.6 (19.7) 18.2 (11.5)Stroop # correct/min F (3, 44) = 14.9 48.2 (16.3) 12.6 (11.2) ¥ ,‰ 32.9 (16.4) 30.0 (15.4) ¥

Phonemic fluency F (3, 54) = 19.4 16.6 (3.2) 8.1 (5.0) ¥ 7.2 (3.6) ¥ 4.8 (4.2) ¥

Semantic fluency F (3, 54) = 47.8 24.1 (5.7) 7.2 (3.6) ¥ 11.0 (5.8) ¥ 4.3 (4.0) ¥ ,‰

Abbreviated BNT (max = 15) F (3, 54) = 23.0 14.5 (3.2) 11.9 (3.6) 10.0 (5.0) ¥ 3.0 (2.4) ¥ ,y,‰

Mod. Rey-O copy (max = 17) F (3, 54) = 8.4 16.1(1.3) 9.6 (6.6) ¥ ,‰ 13.8 (3.5) 15.8 (0.9)y

Calculations (max = 5) F (3, 56) = 5.4 4.6 (0.6) 2.7 (0.8) ¥ 3.5 (1.5) 3.8 (1.5)GDS (max = 30, lower better) F (3, 48)=2.9 3.3 (2.9) 6.1 (4.8) 3.1 (2.7) 6.9 (4.3)

SD= standard deviation, NS= not signficant. P50.05 across groups (ANOVA). ¥ P50.05 versus Controls (post hoc usingTukey HSD). yP50.05versus Alzheimer’s disease (post hoc using Tukey HSD). ‰P50.05 versus FvFTD (post hoc using Tukey HSD).

1648 Brain (2008), 131, 1646 ^1657 M. Hoefer et al.



ApparatusVisual stimuli were presented on a 17in. CRT computer monitor

attached to a custom-built PC running the STIM software package

(James Long Co., Caroga Lake, NY, www.jameslong.com).

Acoustic stimuli were presented via Telephonics high-impedance

headphones (Farmingdale, NY).

Skin conductance level (SCL) was measured in microSiemens(mS) by attaching two 1081 FG-DIN Ag/AgCl sensors prepared

with Biogel electrode gel (UFI inc., Morro Bay, CA) to the ventral

surface of the middle phalanges on the middle and index fingers

of the participant’s non-dominant hand. The sensors were

connected to an SAI bioamplifier (0.5V constant voltage with a

sensitivity of 600 pS, SAI Inc., Hauppauge, NY), which fed the

signal to a DI-720-P data acquisition unit (DataQ, Akron, OH),

and the digitized data were transmitted to a laptop computer

running Snapmaster software (version 3.5.8, HEM Data

Corporation, Southfield, MI). The physiological software acquired

skin conductance data on two channels: one with the SCL and the

other with SCR. SCL is derived by applying excitation voltage to

the sensors attached to the hand. The resultant current flow is

presented, after root-mean square conversion and signal con-

ditioning, as a DC conductance level. SCL bandpass is 10 Hz, and

range is 0–25 mS. SCR is derived by sampling the SCL channel and

directing it through high gain signal conditioning circuits, which

also remove the DC signal, resulting in a magnified display of skin

conductance change. The bandpass is 0.01–10 Hz, and the range

was 2.5 to +2.5 mS.

Experimental procedureAfter consent, subjects washed their hands and had the sensors

attached. They were then seated about 50 cm from the computer

monitor and instructed to breathe normally and to refrain from

moving or talking while a 60 s baseline reading of SCL/SCR was

taken.Participants were then presented with the conditioned stimuli

and asked to name the colours, as a test of whether they could

appreciate differences between them. Headphones were then

placed over the subject’s ears and a hearing test was administered

using a series of 1 and 2 kHz tones. Participants were asked to

indicate the onset and offset of the tones by raising and lowering

their hands. The hearing screening revealed several patients (two

controls, three FTLD and one Alzheimer’s disease) with some

hearing difficulties (unilateral hearing loss or bilateral high

frequency hearing loss). Inspection of the data in these patients

did not suggest that the hearing problems impacted their

reactivity, and all patients reported hearing the aversive sound

loudly and clearly. Hearing problems are a normal accompani-

ment of aging, and not specifically associated with any of the

disorders studied here. Thus, in order to increase the general-

izeability of the results, these subjects were included in our

analyses, with the presence of these abnormalities entered as a

covariate.

Next, the subject was given a warned presentation of the US

without concomitant presentation of the CS+ in order to acquaint

them with the stimulus. After this presentation, the subject was

given an opportunity to discontinue the experiment if the US was

deemed too aversive (no participants discontinued at this point).

Participants were then informed that they would see a series of

colours and occasionally hear the loud sound. They were

instructed to press a button each time they saw a colour (this

was done to ensure that they were attending to the stimulus).

During the conditioning paradigm, stimuli were presented in

pseudorandom order to diminish anticipatory confounds. During

inter-trial intervals the computer screen was dark. During

habituation, the subject was presented with four CS+ trials and

four CS trials without presentation of the US. Acquisition was

broken into two parts: (i) constant acquisition, where the subject

was presented with four CS+ trials each paired with the US and

four CS trials and (ii) variable acquisition, where the subject was

presented with 6 CS+/US trials, 16 CS trials and 8 CS+ trials

without a paired US. The variable acquisition phase allowed us to

measure the SCR to the CS+ after learning, but without the

confounding effect of the US being presented immediately after

the CS+ and in a phase where the US/CS+ association was still

being intermittently reinforced. During extinction the subject was

presented with 16 unpaired CS+ and 16 CS trials.

At the end of the experiment, a second 1 min 60 s assessment of

resting SCL/SCR was taken.

Image acquisitionT1-weighted images were available in 53 of the 75 subjects

(17 controls, 21 FTLD, 16 Alzheimer’s disease). Structural MR

imaging was accomplished using a 1.5-T Magnetom VISION

system (Siemens Inc., Iselin, NJ), a standard quadrature head coil

and previously described sequences (Rosen et al ., 2002) to obtain

(i) scout views of the brain for positioning subsequent MRI slices,

(ii) proton density and T2-weighted MRIs and (iii) T1-weighted

(MP-RAGE) images of the entire brain. MP-RAGE images were

used for analysis.

AnalysisFor all analyses except baseline assessment of reactivity (see

subsequently), we used the maximum SCR during the period

running from 0.5 s to 4.5 s after stimulus offset.

Conditioning and extinctionConditioning was represented as the change in maximum SCR to

the CS+, as compared with the CS, after acquisition. Relative

response to the CS+ was measured by taking the mean maximum

SCR to the CS for all trials representing each phase and

subtracting this from the mean maximum SCR to the CS+ across

targeted trials for the same phase. If conditioning occurs, this

difference (SCRdiff) should be zero for habituation, but positive

after acquisition. In order to create one number representing

conditioning, this SCRdiff in habituation was subtracted from the

SCRdiff after acquisition. Target trials were as follows: all trialsduring habituation, and those trials occurring in the latter half of

acquisition that were not followed by the US (variable acquisition

phase). A single value for extinction was also created by

subtracting the SCRdiff in the latter half of extinction from the

SCRdiff in the latter half of acquisition.

Physiological response to USThe SCR response to the US was examined for each of the 10

times it was presented during acquisition. We used the average

response across all these trials as a covariate for some statistical

analysis.




Baseline assessment of reactivityVarious factors, including skin thickness, aging and medications

might affect the ability to measure electrodermal reactivity. To assess

this, we examined the maximum SCR during the 60 s rest periods

that occurred at the beginning or end of the session. During these

rest periods, the experimenter monitored participants’ activity and

noted excessive subject movement or talking. Problems with theinitial rest period were noted in 6 of the 75 subjects (four FTLD, two

Alzheimer’s disease). In three of these, the rest period at the end of

the experiment was considered valid, and was used instead. In the

other three (two FTLD and one Alzheimer’s disease), both rest

periods had problems. For these subjects, the first rest period was

used. Baseline reactivity in Alzheimer’s disease appeared to be higher

than in controls and FTLD, which had similar baseline reactivity, but

the difference was not significant across groups [one way ANOVA;

F (2, 72) = 1.28, P = 0.29]. Baseline SCL also did not differ across

groups. Baseline reactivity (SCR) was included as a covariate in all

statistical analyses.

MedicationsSCR is a sympathetic response mediated by cholinergic fibres in

the periphery. While there is not extensive data examining the

effects of medications on FC, the bulk of the available literature

indicates that agents with substantial anticholinergic effects can

alter FC, but there is little evidence that agents with effects on the

sympathetic nervous system have much impact (Fryer and Lukas,

1999; Mueck-Weymann et al ., 2001; Grillon et al ., 2004; Siepmann

et al ., 2004; Praharaj and Arora, 2006). To address this issue, we

reviewed participants’ medication lists and identified agents likely

to have effects on SCR or conditioning. Targets included

antipsychotics (both first and second generation), selective

serotonin reuptake inhibitors (including fluoxetine, paroxitine,

citalopram and escitalopram, sertraline, duloxetine), other anti-

depressants (tricyclics, trazadone, venlafaxine), antihistamines andbenzodiazepines [which have been shown to affect FC (Brignell

and Curran, 2006)]. Most patients were on one of these agents.

A few were on two or three. Patients were coded dichotomously as

to whether they were, or were not on these agents.

Cholinesterase inhibitors are a standard of care for patients with

Alzheimer’s disease and are sometimes prescribed in other

dementia syndromes. Because they enhance cholinergic function,

they could conceivably enhance SCRs. Thus, we also coded each

patient according to whether they were on such agents. The

presence or absence of anticholinergic medications and cholines-

terase inhibitors were included in all statistical analyses.

Correlations between physiology and other clinicalfeaturesAbnormalities in conditioning or physiologic responding could be

mediated by other cognitive or clinical factors, including severity

of disease. To explore this, we conducted bivariate regression

analyses between physiological variables and the Clinical Dementia

Rating Scale, Neuropsychiatric Inventory and GDS, and all the

neuropsychological variables described earlier.

Voxel-based morphometry (VBM)VBM is a technique that allows voxel-wise analysis of the

relationship between changes in brain tissue content and

independent variables of interest (Ashburner and Friston, 2000).

A detailed description of the VBM pre-processing and analysis

steps used in this study has been published (Rosen et al ., 2005).

Briefly, our approach included the use of a study specific template

composed of the average of all study participants (Good et al .,

2001; Testa et al ., 2004), optimized spatial normalization of grey

matter images (Good et al ., 2002) and multiplication of the gray

matter images by the Jacobian determinants used in normalization

to preserve the original volume. Normalized gray matter images

were smoothed using a 12mm full width at half-maximum

isotropic Gaussian kernel.

VBM analyses were constructed to compare tissue content

across groups before examining the correlates of the physiological

variables. Physiological correlates were examined by entering the

physiological variables into ‘covariates only’ design matrices to

examine their anatomical correlates. The data were then

reanalysed using ‘conditions and covariates’ matrices to look for

group-specific effects. Age, sex and total intracranial volume,

calculated as the sum of the modulated gray, white and CSF

volumes, used to control for head size) were always used as

covariates.Statistical significance was evaluated at P 50.05 corrected for

multiple comparisons using family-wise error correction (Friston

et al ., 1996). The human and animal literature indicates that

particular aspects of FC are linked to specific brain regions,

providing a basis for selection of regions of interest (ROI) to limit

the number of multiple comparisons. Acquisition is most closely

associated with the amygdala (Bechara et al ., 1995, 1999; LaBar

et al ., 1995, 1998; Buchel and Dolan, 2000). Extinction is

associated with ventromedial frontal cortex (Phelps et al ., 2004;

Milad et al ., 2005; Quirk and Beer, 2006) and related processes of

reversal learning with posterior OFC (Kringelbach and Rolls,

2004). More generally, emotional processing is linked with a

diverse set of frontal and temporal regions including the anterior

and mid-cingulate regions, medial superior frontal gyrus, ventro-medial frontal and OFC and amygdala (Phan et al ., 2002; Phillips

et al ., 2003a). These regions were used as the ROI for reactivity to

the US, as the literature does not provide a basis for constraining

the ROI further. ROIs were constructed using WFU Pickatlas

software (version 2.0 for Linux, Wake Forest University, Raleigh,

NC), (Maldjian et al ., 2003) and the AAL brain atlas (Tzourio-

Mazoyer et al ., 2002). For each physiological function, potential

effects within the appropriate ROI were explored down to a voxel-

level P -value of 0.01. All VBM statistical analyses were conducted

using SPM (version 2, University College, London, UK) operating in

a MATLAB environment (version 7.1, Mathworks, Inc.,Natick, MA).

Statistical analysesOur chief aim was to see how FC is affected in each of the clinical

dementia syndromes. We examined this with regression analysis

using our conditioning variable (see Conditioning and extinction

in the analysis section above) as the dependent variable and

diagnosis (control, Alzheimer’s disease or FTLD) and other

covariates as independent variables. Regressions were conducted

in two blocks, with all covariates entered in the first block and

diagnosis in the second block. If the contribution of diagnosis was

significant, as indicated by a P 50.05 for the R2 after adding

diagnosis into the model, differences between each patient group

and controls were evaluated at P 50.05 threshold using a Fischer’s

least significant difference approach (Miller, 1981).




We also compared the basic reactivity to the US across groups.

Because the US was delivered 10 times during the experiment,

each subject contributes multiple SCR measurements representing

reactivity to the US. We analysed these repeated measures using

linear mixed effects models (McCulloch and Searle, 2001).

Examination of the correlations between individual US responses

across time did not suggest that these responses departed from the

assumption of compound symmetry.

Because of the known effects of age on FC (Labar et al ., 2004),

age was included in all of the analyses in addition to baseline

physiological reactivity, medication use and the presence or

absence of mild hearing impairment. Statistical analyses were

performed using SPSS version 14 (SPSS inc., http://www.

spss.com).

ResultsFC

Figure 2 shows that the SCRdiff for CS+ versus CSincreased for controls in the acquisition phase, consistent

with conditioning. In contrast, there is no evidence of learning in FTLD or Alzheimer’s disease. The overall effect

for diagnosis was significant (P = 0.01), and pairwisecomparisons were significant for FTLD versus controls

(B =0.042, P 50.01) and for Alzheimer’s disease versuscontrols (B =0.049, P 50.01).

Reactivity to the US

We examined the response to the US across the experimentto assess whether this might be abnormal in either patient

group. Linear mixed effects analysis revealed a significanteffect for group overall (P 50.04). Pairwise comparisons

were significant for FTLD versus control (mean difference0.09 mS, 95% CI 0.02–0.16, P 50.02) but not for Alzheimer’sdisease versus controls (mean difference 0.06mS, 95%CI 0.13 to 0.12, P 50.45). The difference between

FTLD and Alzheimer’s disease approached significance

(mean difference 0.09 mS, 95% CI 0.01 to 0.13, P 50.09).Response to the US is depicted in Fig. 3, which

also includes the first presentation of the US priorto the experiment. This first response was higher

than subsequent responses in all groups, but still lowest

in FTLD.We also analysed the reactivity to the US in terms of how

many participants had significant SCRs in response to theUS. Participants were scored as having a significant SCR if any of their responses were 40.5mS, a commonly used

threshold for SCRs (Ohman et al ., 2000). Using thisthreshold, 40% of the controls and 48% of the Alzheimer’s

disease patients had significant SCRs in response to the US,

but only 12% of the FTLD subjects had significant SCRs(2 P 50.05 overall, and for FTLD versus controls andFTLD versus Alzheimer’s disease).

The FTLD group was composed of two syndromes: FTD

and SD. To explore whether either of these groups was

disproportionately showing reduced reactivity, we examined

the response to the US averaged across all 10 learning trialsseparately for FTD and SD. As shown in Fig. 4, the USresponse was low in both SD and FTD, compared with theother groups. A post hoc statistical comparison confirmedthat there was no significant difference in average responseto the US between SD and FTD (two-sample t -test,P = 0.326).

Fig. 3 Magnitude of SCR after each of the 11 presentations of the100 db US, once prior to the experiment and 10 times during theexperiment. Means for controls, FTLD and Alzheimer’s disease.

Fig. 2 Difference in SCR for CS+ versus CS in each group ineach phase of the experiment.


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Reactivity to the US and conditioning

The low reactivity to the US in FTLD suggested that this

may be an important factor determining their apparent lack

of conditioning. Thus, the contribution of the US response

to conditioning was assessed by repeating the original

regression model with conditioning as the dependent

variable and US response as an additional independent

variable. For this analysis, response to the US was averaged

across all 10 presentations to create a single covariate.

With this change, the overall effect of adding diagnosis

to the model was still significant (P 50.04). However, the

difference between FTLD and controls for conditioning wasreduced and was only marginally significant (B =0.028,P = 0.067), while the impairment in Alzheimer’s disease

remained significant (B = 0.041, P 50.01).

Neuropsychological and behavioural data and

clinical-physiology correlationsTables 1 and 2 summarize the neuropsychological and

behavioural findings in controls and in the three patient

groups: Alzheimer’s disease, FTD and SD. There were no

differences in age or sex distribution across groups. All

patient groups showed increased Clinical Dementia Rating

Scales and decreased Mini-Mental State Examinations

compared with controls, but there were no differences

across patient groups. As would be expected, Alzheimer’s

disease patients showed the worst performance in memory

and figure copying, and they also showed poor calculation

abilities and low performance on many measures sensitive

to frontal lobe disease. SD patients showed the worst

picture naming. In the behavioural domain (Table 2), both

FTD and SD showed high levels of apathy, disinhibition

and eating disorders, none of which were significantly

different between FTD and SD, consistent with prior

reports demonstrating behavioural overlap between FTD

and SD (Liu et al ., 2004).Bivariate correlation analyses were performed examining

the relationship between the degree of conditioning,

reactivity to the US and all the variables listed in

Tables 1 and 2 across patients. GDS score was correlatedwith reactivity to the US (r = 0.383, P 50.02, uncorrected

for multiple comparisons). This analysis was repeated as a

partial correlation, factoring out diagnosis and the relation-

ship was still significant. No other variables were correlatedwith the physiology data.

VBMFTLD and Alzheimer’s disease both showed regions of

significant volume loss (P 50.05, corrected for multiplecomparisons) compared with controls (Fig. 5). In FTLD,

these regions included the left posterior orbitofrontal

region, extending into the left insula, and the right insula.In Alzheimer’s disease, the regions were in the tempor-

oparietal cortex bilaterally.Anatomical correlates of physiological variables are

summarized in Table 3 and illustrated in Fig. 6.

Conditioning was examined using reactivity to the US as

a covariate, in addition to age, sex and total intracranial

volume. No regions correlated with conditioning wereidentified across the experimental group at a whole-brain

corrected level of significance, or within the amygdala to a

level of P 50.01. However, in FTLD, conditioning was

correlated with tissue content in the right amygdala (voxel-level P = 0.004, P = 0.062 corrected for volume of the

bilateral amygdala ROI). No effects could be found in

controls or Alzheimer’s disease.

Table 2 Neuropsychiatric Inventory frequency severityproduct (and per cent with that feature) across diagnosticgroups

Feature Controls Alzheimer’sdisease

FTD SD

Delusions 0 0.6 (29) 0.8 (18) 0 (0)Hallucinations 0 0.3 (24) 0.4 (16) 0.2 (10)Agitation 0 1.2 (29) 2.8 (50) 2.9 (60)Depression 0 2.2 (52) 1.7 (17) 1.0 (40)Anxiety 0 2.0 (52) 2.6 (50) 1.8 (40)Elation 0 0.4 (10) 0.8 (33) 1.3 (30)Apathy 0 3.8 (57) 6.3 (92) ¥ 4.9 (70)Disinhibition 0 0.8 (38) 4.1 (67) ¥ ,y 5.1 (80) ¥ ,y

Irritability 0 0.8 (43) 1.4 (33) 2.6 (40)Aberrant motorBehaviour

0 2.0 (33) 3.8 (58) 2.8 (50)

Sleep Disorders 0 1.1 (38) 2.3 (50) 0.8 (30)Eating Disorders 0 1.6 (33) 5.9 (75) ¥ ,y 4.7 (80) ¥

P50.05 across groups (ANOVA for frequency severity

product).

¥

P5

0.05 versus Controls (post hoc using Tukey HSD).yP50.05 versus Alzheimer’s disease (post hoc usingTukey HSD).

Fig. 4 Magnitude of the SCR averaged in each subject across all10 presentations of the US during the experiment. Means forcontrols, FTD, SD and Alzheimer’s disease.




Reactivity to the US (average across the 10 presentations)

was correlated with volume in dorsal anterior cingulate

cortex (ACC) region (voxel-level P = 0.01) and left insula

across the entire group (voxel-level P = 0.001) but these

effects were not significant after multiple comparison

correction. However, in controls, US reactivity was more

significantly correlated with dorsal ACC volume (voxel-levelP 50.001, P = 0.028 after multiple comparisons correction

within the frontal-temporal ROI). In FTLD, reactivity to

the US appeared to be correlated with volume in the left

insula (voxel-level P = 0.004, not significant after multiple

comparisons correction). No correlations were detected in

Alzheimer’s disease.

Extinction was examined using the magnitude of

conditioning as a covariate, and was correlated with

volume in the posterior OFC, with a more significant

effect on the right (voxel-level P 50.001, P = 0.03 after

Fig. 6 Regions where gray matter content was correlated with physiological responses in specific groups. T -maps overlayed onstudy-specific template.

Table 3 Regions of correlation between gray matter volume and physiological variables

Variable Conditioning US reactivity Extinction

ROI B/L amygdala B/L ACC/OFC/amygdala B/L posterior OFCCoordinatea Regionb Uncorrected/

correctedP-value

Coordinatea Regionb Uncorrected/correctedP-value

Coordinatea Regionb Uncorrected/correctedP-value

Across Groups ç ç ç 4,19, 31 LdACC 0.01/40.1 18, 10, 20 ROFC 50.001/0.0337,11, 12 Linsula 0.001/40.1

Normal Control ç ç ç 4, 8, 36 LdACC 50.001/0028 18,16, 24 ROFC 0.003/40.1FTLD 26, 2, 24 Ramygdala 0.004/0.062 37, 3, 3 Linsula 0.004/40.1 ç ç ç Alzheimer’sdisease

ç ç ç ç ç ç 13, 23, 11 ROFC 0.01/40.1

ROI = Region of interest used for small volume correction for this correlation, B/L = bilateral, dACC= dorsal anterior cingulate cortex,OFC = orbitofrontal cortex. aCoordinate in the standardized space based on the Montreal Neurological Institute (Evans et al., 1994) brain.bAnatomical region of the coordinate, based on overlaying statistical map on the study specific template. L= left, R = right.

Fig. 5 Regions of gray matter tissue loss in FTLD and Alzheimer’sdisease versus controls. T -maps overlayed on study-specific

template.




multiple comparisons correction within the posterior OFCbilaterally) The same region appeared to be correlated with

extinction in controls (voxel-level P = 0.003, not significantafter multiple comparisons correction), and at a lesssignificant level in Alzheimer’s disease (voxel-levelP = 0.01, not significant after multiple comparisons correc-

tion). No effects with a P -value 50.01 were seen in thisregion in FTLD.

Discussion

Our study suggests that both Alzheimer’s disease and FTLD

are associated with abnormalities emotional reactivity in aclassical fear FC paradigm, but that the nature of the deficitdiffers between the two disorders. In Alzheimer’s disease,the deficit is isolated to conditioning, with normal reactivity to an inherently aversive stimulus, a replication of a priorfinding in Alzheimer’s disease (Hamann et al ., 2002). In

FTLD, the deficit appears to be different, with reduced

physiological reactivity to an aversive stimulus. Physiologi-cal deficits were not accounted for by medication use orhearing deficits, and the deficit in reactivity to the US was

present in both SD and FTD—two variants of FTLD thatshow a large degree of behavioural overlap (Bozeat et al .,2000; Snowden et al ., 2001; Liu et al ., 2004; Rosen et al .,2006), again seen in this study. Physiological reactivity did

not correlate with any neuropsychological variables, indi-cating that these deficits were not mediated by cognitiveimpairment. Thus, this FC paradigm appears to pinpointfunctional deficits in FTLD and Alzheimer’s disease that arenot addressed by traditional neuropsychological testing anddo not correlate with any particular cognitive test. While

the numbers in this study are relatively small for this typeof paradigm and the findings for FTLD should bereplicated, the distinctive types of abnormalities in FTLDversus Alzheimer’s disease suggested here offer new insights

into the emotional and cognitive abnormalities seen inthese two disorders.

Our findings highlight the contribution of several corticalregions to emotional learning. The amygdala, which is theprimary site for the establishment of CS–US association

(LeDoux, 1992), is strongly interconnected with theanterior cingulate, insula and OFC (Amaral and Price,1984). These paralimbic regions function as transition zones

between evolutionarily older limbic cortex and newerneocortical structures subserving higher-level multimodalprocessing, providing a link between visceral processing and

other sensory information (Mesulam and Mufson, 1982a, b;Mufson and Mesulam, 1982). Prior studies have shown thatinjury to some of these regions, including the ventromedialfrontal cortex and ACC, as well as right parietal regions,

causes reduced electrodermal reactivity to aversive stimulisimilar to those used in our study (Tranel and Damasio,1994). FTLD consistently affects these paralimbic regions(Rosen et al ., 2002; Diehl et al ., 2004; Ibach et al ., 2004;

Liu et al ., 2004; Boccardi et al ., 2005), which was

highlighted by our VBM data showing bilateral insulaand left OFC tissue loss in FTLD. Thus, we propose thatinjury to the OFC and/or insula causes reduced reactivity to the US in FTLD. The VBM analysis suggested that insula,in particular, may account for this deficit in FTLD,although the statistical significance of this association

was low, possibly because FTLD patients were uniformly low in both insular tissue content and US reactivity,limiting the variance needed to estimate the relationship.The insula is well-established as a site of visceral processing(Cechetto and Saper, 1987; King et al ., 1999). Insularactivation correlates with SCR magnitude in fMRI studies(Critchley et al ., 2000), and the insula has been proposedas one route for transmission of aversive stimulusinformation to the amygdala in FC paradigms (Shi andDavis, 1999).

The VBM analysis also highlighted a relationship betweencerebral changes in normal aging and physiologicalreactivity. Normal aging is known to be associated with

reductions in reactivity to USs (Labar et al ., 2004) and thiswas correlated with tissue loss in the ACC in our analysis.This association was statistically significant, after correctionusing a large ROI encompassing the amygdala andparalimbic regions mentioned earlier. Notably, this associa-tion was not detected in Alzheimer’s disease, suggesting thatother factors may affect US reactivity in this group.

Although electrodermal activity was reduced in FTLD,many normal controls had low electrodermal activity usingthis method as well, as has been shown in previous work (Labar et al ., 2004). Thus, electrodermal responses to thisspecific stimulus are not a sensitive diagnostic markerof FTLD, but they do suggest that other measures probingthe emotional reactivity system in the brain, such as fMRI,may provide sensitive measures of disease. In addition,although electrodermal activity did not correlate with spe-cific behaviours on the Neuropsychiatric Inventory, reducedphysiological reactivity has potential implications forbehaviour in FTLD. Our image analysis and prior studiesreferenced above suggest that electrodermal reactivity toaversive stimuli depends on the integrity of severalstructures, including the ACC and VMPC/insula, whichare important structures for emotional processing. Reducedphysiological responsiveness to aversive stimuli may be amarker of underactivation of these structures in response to

punishments, which may cause events that would beconsidered aversive to normal individuals be consideredless fearsome by FTLD patients. If this were the case, FTLDpatients may be less likely to alter their choices based onthe fear that their actions could generate potentially aversive consequences. In support of the idea that FTLDpatients are less sensitive to aversive consequences, previousstudies have indicated that FTLD patients have reducedsensitivity to pain (Snowden et al ., 2001). The specificphysical sensations associated with physiological activationhave also been hypothesized to play an important role incognitive and social decision making (Bechara et al ., 2000),




an idea sometimes referred to as the somatic markerhypothesis (Damasio, 1996). Based on this hypothesis theabsence of the visceral sensations associated with peripheralphysiological activation itself may be a factor contributingto a change in behaviour in FTLD, such that thesesensations deprives FTLD patients of important informa-

tion for cognitive and social decision making. Whether thedeficit in sensory input due to impaired physiologicalactivation could be, in and of itself, an importantcontributor to abnormal behaviour in FTLD, as opposedto altered physiology just being a marker of altered corticalprocessing, is unclear, and cannot be resolved from ourdata. Because some normal older individuals showed low physiological reactivity, but this was more prevalent inFTLD, we would favour the idea that our findings representa marker of more pervasive impairment in activation of cortical emotional processing systems.

Even after correction for reactivity to the US, the FCimpairment in FTLD was marginally significant, suggesting

a true conditioning deficit in addition to their deficit inreactivity. The residual FC ability was correlated withamygdala volume. This is consistent with studies demon-strating FC impairment due to amygdala damage (Becharaet al ., 1995; LaBar et al ., 1995), and with prior studiesshowing volumetric changes in the amygdala in FTLD(Chan et al ., 2001; Liu et al ., 2004). Whereas reducedelectrodermal reactivity appeared to be characteristic of FTLD, conditioning may have occurred in patients withrelatively little amygdala loss.

Abnormal electrodermal responding in FTLD does notnecessarily imply that all emotional reactivity is impaired.A recent study of emotional reactivity in FTLD demon-strated impaired activation of self-conscious emotions, butfound that basic reactivity to a startle stimulus was intact(Sturm et al ., 2006). The stimulus used in that study was presented without warning and was three times louder(115 db) than the stimulus used in this study, which doesnot typically elicit a full defensive startle response. Thepreservation of the defensive response to the more powerfulstartle stimulus suggests that the basic physiologicalmechanisms for autonomic and behavioural responding,generated in the brainstem, hypothalamus and spinal cord,remain intact in FTLD. It is notable that FTLD patients inthe current study appeared to show short-term habituation,

decreasing their reactivity to the US after the first exposureprior to the experiment. Short-term habituation of theacoustic startle reflex has been demonstrated in decerebraterats, indicating that it can occur purely through brainstemmechanisms (Leaton et al ., 1985). This further supports theidea that basic subcortical mechanisms of behavioural andphysiological responding to aversive stimuli are intact inFTLD. What the current study suggests is that corticalinfluences on these basic reactions are altered, so thatresponses to less dramatic stimuli can be impaired.

Our data also demonstrated impaired FC in Alzheimer’sdisease, where the electrodermal response to the US

was normal. These data confirm a previous study (Hamann

et al ., 2002) that demonstrated impaired FC in Alzheimer’s

disease. Although this abnormality could relate to amygdala

damage, we could not identify this relationship with VBM,

even after placing a ROI in the amygdala. This relationship

may emerge with a larger sample, or the deficit may be

determined by functional changes in the amygdala that are notcorrelated with volume loss. The behavioural implications of

the FC deficit in Alzheimer’s disease are not established. One

potential effect is an impact on episodic memory, because of

the known effects of emotional processing in enhancing

episodic memory (Cahill and McGaugh, 1998). A previous

study demonstrated a blunted impact of emotional processing

on memory in Alzheimer’s disease (Hamann et al ., 2000).

There may also be effects in the emotional realm. Alzheimer’s

disease frequently causes behavioural abnormalities including

apathy, irritability and agitation (Cummings, 1997). If deficits

in emotional learning prevent learning new associations

between neutral events and aversive outcomes, patients couldbecome confused about what is threatening in their environ-

ment, leading to irritability and agitation. It is also notable

that reactivity to the US was correlated across all patients with

the GDS score, indicating this type of physiological reactivity

may influence mood, both in Alzheimer’s disease and FTLD.We also found that right OFC volume is associated with

extinction. Although this finding was significant across the

whole group of subjects (after multiple comparison

correction for an OFC ROI), the data looking at this

relationship in individual groups suggested that most of the

effect was driven by the normal control subjects, who were

able to generate conditioned responses. This finding is

consistent with previous studies relating posterior OFC toextinction in FC paradigms, and more generally to

modification of previously established cue-reward associa-

tions (Kringelbach and Rolls, 2004; Phelps et al ., 2004;

Milad et al ., 2005; Quirk and Beer, 2006).The finding of abnormal FC in dementia may have broad

implications. FC is a unique behavioural probe for studying

neurodegenerative disease. Although it represents a very

low-level emotional response that cannot easily be linked to

more complex behaviour, this paradigm has several

attractive features. The behavioural component is simple,

and requires relatively little comprehension, allowing

patients of varying severity to be studied. It does not

seem to correlate with standard measures of cognitive

function, suggesting that it provides a novel window into

brain function relative to these measures. In addition, our

data suggest that these processes are disrupted early in

neurodegenerative disease. Most importantly, FC has been

extensively studied in humans and animals, and appears to

depend on the same brain structures across species,

allowing parallel studies in humans and animals to be

designed. These features suggest that FC can be a powerful

tool for linking molecular changes in neurodegenerative

disease with human behaviour.




AcknowledgementsThis work was supported by the State of California

Department of Health Services (DHS) grant 04-35516NIA,

State of California DHS Alzheimer’s Disease Research

Center of California (ARCC) grant 01-154-20, NIH grants

1K08AG020760-01, AG10129, P50-AG05142 and AG16570,

NINDS grant NS050915, grant number M01 RR00079(UCSF General Clinical Research Center) and the Hillblom

Network.

References

Amaral DG, Price JL. Amygdalo-cortical projections in the monkey

(Macaca fascicularis). J Comp Neurol 1984; 230: 465–96.

Ashburner J, Friston KJ. Voxel-based morphometry–the methods.

Neuroimage 2000; 11: 805–21.

Barnes J, Whitwell JL, Frost C, Josephs KA, Rossor M, Fox NC.

Measurements of the amygdala and hippocampus in pathologically

confirmed Alzheimer disease and frontotemporal lobar degeneration.

Arch Neurol 2006; 63: 1434–9.

Basso M, Yang J, Warren L, MacAvoy MG, Varma P, Bronen RA, et al.Volumetry of amygdala and hippocampus and memory performance in

Alzheimer’s disease. Psychiatry Res 2006; 146: 251–61.

Bechara A, Damasio H, Damasio AR. Emotion, decision making and the

orbitofrontal cortex. Cereb Cortex 2000; 10: 295–307.

Bechara A, Damasio H, Damasio AR, Lee GP. Different contributions of

the human amygdala and ventromedial prefrontal cortex to decision-

making. J Neurosci 1999; 19: 5473–81.

Bechara A, Tranel D, Damasio H, Adolphs R, Rockland C, Damasio AR.

Double dissociation of conditioning and declarative knowledge relative

to the amygdala and hippocampus in humans. Science 1995; 269:

1115–8.

Boccardi M, Sabattoli F, Laakso MP, Testa C, Rossi R, Beltramello A, et al.

Frontotemporal dementia as a neural system disease. Neurobiol Aging

2005; 26: 37–44.

Bozeat S, Gregory CA, Ralph MA, Hodges JR. Which neuropsychiatric andbehavioural features distinguish frontal and temporal variants of

frontotemporal dementia from Alzheimer’s disease? J Neurol

Neurosurg Psychiatry 2000; 69: 178–86.

Braak H, Braak E. Neuropathological stageing of Alzheimer-related

changes. Acta Neuropathol 1991; 82: 239–59.

Brignell CM, Curran HV. Drugs, sweat, and fears: a comparison of the

effects of diazepam and methylphenidate on fear conditioning.

Psychopharmacology (Berl) 2006; 186: 504–16.

Buchel C, Dolan RJ. Classical fear conditioning in functional neuroima-

ging. Curr Opin Neurobiol 2000; 10: 219–23.

Cahill L, McGaugh JL. Mechanisms of emotional arousal and lasting

declarative memory. Trends Neurosci 1998; 21: 294–9.

Cechetto DF, Saper CB. Evidence for a viscerotopic sensory representation

in the cortex and thalamus in the rat. J Comp Neurol 1987; 262: 27–45.

Chan D, Fox NC, Scahill RI, Crum WR, Whitwell JL, Leschziner G, et al.Patterns of temporal lobe atrophy in semantic dementia and Alzheimer’s

disease. Ann Neurol 2001; 49: 433–42.

Critchley HD, Elliott R, Mathias CJ, Dolan RJ. Neural activity relating to

generation and representation of galvanic skin conductance responses:

a functional magnetic resonance imaging study. J Neurosci 2000; 20:

3033–40.

Cummings JL. The Neuropsychiatric Inventory: assessing psychopathology

in dementia patients. Neurology 1997; 48: S10–6.

Damasio AR. The somatic marker hypothesis and the possible functions of

the prefrontal cortex. Philos Trans R Soc Lond B Biol Sci 1996; 351:

1413–20.

Delis D, Kaplan EB, Kramer J. The Delis-Kaplan executive function system.

San Antonio: TX, US: The Psychological Corporation; 2001.

Delis DC, Kramer JH, Kaplan E, Ober BA. California Verbal Learning

Test, 2nd edn. San Antonio: TX, US: The Psychological Corporation;

2001.

Diehl J, Grimmer T, Drzezga A, Riemenschneider M, Forstl H, Kurz A.

Cerebral metabolic patterns at early stages of frontotemporal dementia

and semantic dementia. A PET study. Neurobiol Aging 2004; 25:

1051–6.

Evans AC, Kamber M, Collins DL, Macdonald D. An MRI-basedprobabilistic atlas of neuroanatomy. In: Shorvon S, Fish D,

Andermann F, Bydder GM, Stefan H, editors. Magnetic resonance

scanning and epilepsy. Vol. 264. Plenum Press; 1994. p. 263–74.

Folstein MF, Folstein SE, McHugh PR. ‘Mini-mental state’. A practical

method for grading the mental state of patients for the clinician.

J Psychiatr Res 1975; 12: 189–98.

Friston KJ, Holmes A, Poline JB, Price CJ, Frith CD. Detecting activations

in PET and fMRI: levels of inference and power. Neuroimage 1996; 4:

223–35.

Fryer JD, Lukas RJ. Antidepressants noncompetitively inhibit nicotinic

acetylcholine receptor function. J Neurochem 1999; 72: 1117–24.

Good CD, Johnsrude IS, Ashburner J, Henson RN, Friston KJ,

Frackowiak RS. A voxel-based morphometric study of ageing in 465

normal adult human brains. Neuroimage 2001; 14: 21–36.

Good CD, Scahill RI, Fox NC, Ashburner J, Friston KJ, Chan D, et al.

Automatic differentiation of anatomical patterns in the human brain:

validation with studies of degenerative dementias. Neuroimage 2002; 17:

29–46.

Grillon C, Cordova J, Morgan CA, Charney DS, Davis M. Effects of the

beta-blocker propranolol on cued and contextual fear conditioning in

humans. Psychopharmacology (Berl) 2004; 175: 342–52.

Hamann S, Monarch ES, Goldstein FC. Impaired fear conditioning in

Alzheimer’s disease. Neuropsychologia 2002; 40: 1187–95.

Hamann SB, Monarch ES, Goldstein FC. Memory enhancement for

emotional stimuli is impaired in early Alzheimer’s disease.

Neuropsychology 2000; 14: 82–92.

Ibach B, Poljansky S, Marienhagen J, Sommer M, Manner P, Hajak G.

Contrasting metabolic impairment in frontotemporal degeneration and

early onset Alzheimer’s disease. Neuroimage 2004; 23: 739–43.

Kaplan E, Goodglass H, Wintraub S. The Boston Naming Test.

Philadelphia: Lea and Febiger; 1983.King AB, Menon RS, Hachinski V, Cechetto DF. Human forebrain

activation by visceral stimuli. J Comp Neurol 1999; 413: 572–82.

Kringelbach ML, Rolls ET. The functional neuroanatomy of the human

orbitofrontal cortex: evidence from neuroimaging and neuropsychology.

Prog Neurobiol 2004; 72: 341–72.

Labar KS, Cook CA, Torpey DC, Welsh-Bohmer KA. Impact of healthy

aging on awareness and fear conditioning. Behav Neurosci 2004; 118:

905–15.

LaBar KS, Gatenby JC, Gore JC, LeDoux JE, Phelps EA. Human amygdala

activation during conditioned fear acquisition and extinction: a mixed-

trial fMRI study. Neuron 1998; 20: 937–45.

LaBar KS, LeDoux JE, Spencer DD, Phelps EA. Impaired fear conditioning

following unilateral temporal lobectomy in humans. J Neurosci 1995;

15: 6846–55.

Leaton RN, Cassella JV, Borszcz GS. Short-term and long-term habituationof the acoustic startle response in chronic decerebrate rats. Behav

Neurosci 1985; 99: 901–12.

LeDoux JE. Brain mechanisms of emotion and emotional learning. Curr

Opin Neurobiol 1992; 2: 191–7.

Liu W, Miller BL, Kramer JH, Rankin K, Wyss-Coray C, Gearhart R, et al.

Behavioral disorders in the frontal and temporal variants of fronto-

temporal dementia. Neurology 2004; 62: 742–8.

Maldjian JA, Laurienti PJ, Kraft RA, Burdette JH. An automated method

for neuroanatomic and cytoarchitectonic atlas-based interrogation of

fMRI data sets. Neuroimage 2003; 19: 1233–9.

Markesbery WR, Schmitt FA, Kryscio RJ, Davis DG, Smith CD,

Wekstein DR. Neuropathologic substrate of mild cognitive impairment.

Arch Neurol 2006; 63: 38–46.




McCulloch CE, Searle SR. Generalized, linear, and mixed models.

New York: John Wiley and Sons; 2001.

McKhann G, Drachman D, Folstein M, Katzman R, Price D, Stadlan EM.

Clinical diagnosis of Alzheimer’s disease: report of the NINCDS-

ADRDA work group under the auspices of Department of Health and

Human Services Task Force on Alzheimer’s disease. Neurology 1984; 34:

939–44.

McKhann GM, Albert MS, Grossman M, Miller B, Dickson D,Trojanowski JQ. Clinical and pathological diagnosis of frontotemporal

dementia: report of the work group on frontotemporal dementia and

Pick’s disease. Arch Neurol 2001; 58: 1803–9.

Mesulam MM, Mufson EJ. Insula of the old world monkey. I.

Architectonics in the insulo-orbito-temporal component of the para-

limbic brain. J Comp Neurol 1982a; 212: 1–22.

Mesulam MM, Mufson EJ. Insula of the old world monkey. III: efferent

cortical output and comments on function. J Comp Neurol 1982b; 212:

38–52.

Milad MR, Quinn BT, Pitman RK, Orr SP, Fischl B, Rauch SL. Thickness

of ventromedial prefrontal cortex in humans is correlated with

extinction memory. Proc Natl Acad Sci USA 2005; 102: 10706–11.

Miller RG. Simultaneous statistical inference. New York: Springer-Verlag;

1981.

Morris JC. Clinical dementia rating: a reliable and valid diagnostic and

staging measure for dementia of the Alzheimer type. Int Psychogeriatr

1997; 9: 173–6discussion 177–8.

Mueck-Weymann M, Acker J, Agelink MW. Autonomic responses of

blood vessels and sweat glands in patients with schizophrenia treated

with olanzapine or clozapine. Psychopharmacology (Berl) 2001; 157:

368–72.

Mufson EJ, Mesulam MM. Insula of the old world monkey. II: afferent

cortical input and comments on the claustrum. J Comp Neurol 1982;

212: 23–37.

Neary D, Snowden JS, Gustafson L, Passant U, Stuss D, Black S, et al.

Frontotemporal lobar degeneration: a consensus on clinical diagnostic

criteria. Neurology 1998; 51: 1546–54.

Ohman A, Hamm A, Hugdahl K. Cognition and the autonomic nervous

system: orienting, anticipation, and conditioning. In: Cacioppo JT,

Tassinary LG, Berntson GG, editors. Handbook of psychophysiology.

New York: Cambridge University Press; 2000.Phan KL, Wager T, Taylor SF, Liberzon I. Functional neuroanatomy of

emotion: a meta-analysis of emotion activation studies in PET and

fMRI. Neuroimage 2002; 16: 331–48.

Phelps EA, Delgado MR, Nearing KI, LeDoux JE. Extinction learning in

humans: role of the amygdala and vmPFC. Neuron 2004; 43: 897–905.

Phillips ML, Drevets WC, Rauch SL, Lane R. Neurobiology of emotion

perception I: the neural basis of normal emotion perception. Biol

Psychiatry 2003a; 54: 504–14.

Phillips ML, Drevets WC, Rauch SL, Lane R. Neurobiology of emotion

perception II: implications for major psychiatric disorders. Biol

Psychiatry 2003b; 54: 515–28.

Praharaj SK, Arora M. Paroxetine useful for palmar-plantar hyperhidrosis.

Ann Pharmacother 2006; 40: 1884–6.

Quirk GJ, Beer JS. Prefrontal involvement in the regulation of emotion:

convergence of rat and human studies. Curr Opin Neurobiol 2006; 16:

723–7.Rauch SL, Shin LM, Phelps EA. Neurocircuitry models of posttraumatic

stress disorder and extinction: human neuroimaging research–past,

present, and future. Biol Psychiatry 2006; 60: 376–82.

Reitan RM. Validity of the Trailmaking Test as an indication of organic

brain damage. Percept Mot Skills 1958; 8: 271–6.

Rosen HJ, Allison SC, Ogar JM, Amici S, Rose K, Dronkers N, et al.

Behavioral features in semantic dementia vs other forms of progressive

aphasias. Neurology 2006; 67: 1752–6.

Rosen HJ, Allison SC, Schauer GF, Gorno-Tempini ML, Weiner MW,

Miller BL. Neuroanatomical correlates of behavioural disorders in

dementia. Brain 2005; 128: 2612–25.

Rosen HJ, Gorno-Tempini ML, Goldman WP, Perry RJ, Schuff N,

Weiner M, et al. Patterns of brain atrophy in frontotemporal dementia

and semantic dementia. Neurology 2002; 58: 198–208.

Shi C, Davis M. Pain pathways involved in fear conditioning measured

with fear-potentiated startle: lesion studies. J Neurosci 1999; 19: 420–30.

Siepmann M, Kirch W, Krause S, Joraschky P, Mueck-Weymann M. The

effects of St. John’s wort extract and amitriptyline on autonomic

responses of blood vessels and sweat glands in healthy volunteers. J Clin

Psychopharmacol 2004; 24: 79–82.

Snowden JS, Bathgate D, Varma A, Blackshaw A, Gibbons ZC, Neary D.

Distinct behavioural profiles in frontotemporal dementia and semantic

dementia. J Neurol Neurosurg Psychiatry 2001; 70: 323–32.

Sturm VE, Rosen HJ, Allison S, Miller BL, Levenson RW. Self-conscious

emotion deficits in frontotemporal lobar degeneration. Brain 2006; 129:

2508–16.

Testa C, Laakso MP, Sabattoli F, Rossi R, Beltramello A, Soininen H, et al.

A comparison between the accuracy of voxel-based morphometry and

hippocampal volumetry in Alzheimer’s disease. J Magn Reson Imaging

2004; 19: 274–82.

Tranel D, Damasio H. Neuroanatomical correlates of electrodermal skinconductance responses. Psychophysiology 1994; 31: 427–38.

Tzourio-Mazoyer N, Landeau B, Papathanassiou D, Crivello F, Etard O,

Delcroix N, et al. Automated anatomical labeling of activations in SPM

using a macroscopic anatomical parcellation of the MNI MRI single-

subject brain. Neuroimage 2002; 15: 273–89.

Yesavage JA, Brink TL, Rolse TL, Lum O, Huang V, Adey M, et al.

Development and validity of a Geriatric Depression Scale: a preliminary

report. J Psychiatr Res 1983; 17: 37–49.


3. Degeneración en el lóbulo frontotemporal

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