Author’s Accepted Manuscript

oscillations in the Human brain during walkingexecution, imagination and observation

C. Cevallos, D. Zarka, T. Hoellinger, A. Leroy, B.Dan, G. Cheron

PII: S0028-3932(15)30079-8DOI: http://dx.doi.org/10.1016/j.neuropsychologia.2015.06.039Reference: NSY5658

To appear in: Neuropsychologia

Received date: 9 February 2015Revised date: 19 June 2015Accepted date: 23 June 2015

Cite this article as: C. Cevallos, D. Zarka, T. Hoellinger, A. Leroy, B. Dan andG. Cheron, oscillations in the Human brain during walking execution,imagination and observation, Neuropsychologia,http://dx.doi.org/10.1016/j.neuropsychologia.2015.06.039

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Oscillations in the human brain during walking execution,

imagination and observation

Cevallos C1, Zarka D1, Hoellinger T1, Leroy, A1, 3, Dan B1,2, Cheron G1,4*.

1Laboratory of Neurophysiology and Movement Biomechanics, ULB Neuroscience Institut,

Université Libre de Bruxelles, Brussels, Belgium

2Department of Neurology, Hopital Universitaire des Enfants reine Fabiola, Université Libre

de Bruxelles, Belgium

3 Haute Ecole Condorcet, Charleroi, Belgium

4Laboratory of Electrophysiology, Université de Mons-Hainaut, Belgium

*Correspondence: Prof. Guy CHERON, Laboratory of Neurophysiology and Movement

Biomechanics, Université Libre de Bruxelles, CP 640, 50 Av. F. Roosevelt, 1050 Brussels,

Belgium. Email: gcheron@ulb.ac.be , Tel: +3225553403

Abstract

Gait is an essential human activity which organizes many functional and cognitive behaviors. The biomechanical constraints of bipedalism implicating a permanent control of balance during gait are taken into account by a complex dialogue between the cortical, subcortical and spinal networks. This networking is largely based on oscillatory coding, including changes in spectral power and phase-locking of ongoing neural activity in theta, alpha, beta and gamma frequency bands. This coding is specifically modulated in actual gait execution and representation, as well as in contexts of gait observation or imagination. A main challenge in integrative neuroscience oscillatory activity analysis is to disentangle the brain oscillations devoted to gait control. In addition to neuroimaging approaches, which have highlighted the structural components of an extended network, dynamic high-density EEG gives non-invasive access to functioning of this network. Here we revisit the neurophysiological foundations of behavior-related EEG in the light of current neuropsychological theoretic frameworks. We review different EEG rhythms emerging in the most informative paradigms relating to human gait and implications for rehabilitation strategies.

KEYWORDS: oscillations; EEG; fMRI; motor control; mental imagery; walking; review

1. Neurophysiological and cognitive perspectives on human gait

Gait (walking and running) is a central activity in human systemic organization, encompassing general

navigation and specific interactions with ecological and social environment. In this review we shall

first highlight the basic imprint exerted by gait not only on the motor aspects of human health but

also by a more subtle way on cognitive function. Secondly, we shall review the neural networks

implicated in gait control and then discuss the different experiments performed in order to extract

the neuronal signals related to walking execution, imagination and observation.

1.1. Walking and creativity, ”un pas de deux “

From a cognitive point of view, walking represents a particular state of the global brain activity and

relies on the use of numerous cognitive resources, comprising, visuospatial abilities, and executive-

attentional functions. As for other motor behaviors, the cognition related to human gait concerns

two main aspects: (1) bottom-up processes that integrate information coming from the sensorimotor

system into the neural structures directly involved in gait control, and at the same time (2) top-down

processes that organize and focus this information according to other brain regions that are not

directly involved in gait control but are crucial for mental concepts, sense making and keeping of gait

goals.

When your feet touch the floor repeatedly you are not aware of the different sub-aspects of the

unfolding of the phenomenon and your brain may perform different mental and behavioral tasks

without the use of directed attention to gait. Yet, dual task experiments demonstrated that walking

cannot be fully automatic but requires internal and external judgment, motivation, attention and

executive function [1, 2], except in selected situations, such as somnambulism or epilepsy [3].

Dual task interferes with different gait parameters (alteration of speed, increased stride-length and

stride-time variability)[4], for a review. In such tasks, priority is generally given to motor control over

cognition and this has been interpreted as a strategy preventing falls [5, 6] [7]. However, other

prioritization strategies have been described such as the executive function to divide attention

during a cognitive task while walking or the prioritization of balance over the cognitive task in dual

task conditions when no specific instructions are given about task priorities [8, 9].

Yet, relationship between gait and cognitive functioning is not always competitive. For example, the

use of (high-groove, high beat salience that facilitate footsteps synchronization) music has been

shown to improve gait rehabilitation in individuals with Parkinson's disease [10] and in those with

stroke [11]. This supports positive interference between rhythmical sensory contingencies in the

brain and gait behavior. Furthermore, walking might by itself facilitate mental operations and

creativity. Brain creativity was reported by Heisenberg when he solved hard matrix calculus of

uncertainty principle during swimming in a lake (reported by [12]). More recently, it was also

demonstrated that outdoor walking among other behaviors (sitting and rolling outside in a

wheelchair) produced the highest creativity scores on Guilford’s alternate uses test [13].

The reciprocal interferences between gait and cognition might be supported by oscillatory properties

of the brain [14, 15]. Namely, it was demonstrated that the power of EEG alpha oscillation increased

during the early and late phases of creative ideas generation [16]. Alpha band oscillations play an

active role in attention and working memory [17, 18]. Recent studies using treadmill workstations

have demonstrated benefits of walking on performance and cognitive abilities that are necessary for

tasks requiring attention and memory [19, 20].

2. Neurophysiology of walking network, the central pattern generator and supraspinal

control

2.1. The central pattern generator

Neurophysiological studies in human have identified a complex mode of control integrating voluntary

command and feedback regulation into a spinal cord network termed central pattern generators

(CPG) [21-23]. However, most of our comprehension of walking neurophysiology comes from animals

studies. Although, evidence is still indirect, it is widely accepted that automatic basic motor pattern

of stepping is generated by the CPG. This network produces rhythmic movements involving synergy

of a large number of muscles (e.g. walking, swimming, flying) without voluntary effort [24]. Evidence

demonstrates that human CPG is genetically determined and develops during childhood. For

instance, infants show a stepping pattern before birth and stepping is a primitive reflex exhibited in

early month of life [25, 26]. There are alternative hypothesis about the development of newborn

motor patterns and stepping reflex evolution. It has been suggested that the inactive period of the

stepping reflex in newborns might be due to excitability changes in the original central network when

descending locomotor driving systems develop and establish contact. It has also been hypothesized

that human locomotor control relies on a hierarchical system similar to that of quadrupeds, but with

additional neural mechanisms that transform the original pattern into upright bipedal control [27].

The spinal CPG is modulated by proprioceptive and sensitive feedback from muscle and skin [28]. In

addition, CPG receives feedforward commands mostly originating in supraspinal structures including,

cerebellum, basal ganglia and various cerebral cortex areas [29].

2.2. The supraspinal control of the CPG

CPG is activated by midbrain locomotor region (MLR) and modulated by pedunculopontine

tegmental nucleus (PPN) via brainstem. MLR and PPN are midbrain structures involved in control

postural muscle tone. MLR is responsible of excitatory muscle tone whereas PPN is responsible of

inhibitory muscle tone. Mutual inhibitory between excitatory and inhibitory system in brainstem and

spinal cord adjust muscle tone and facilitated locomotion [30]. MLR and brainstem receives

rhythmical input from cerebellar locomotor region which regulates speed, while midline cerebellar

regions (vermis and paravermis) control body balance [31, 32]. Basal ganglia control activities of

brainstem and contribute with limbic system to emotional behavioral locomotor expression or

automatic behavior such as fight reactions [30, 33]. Finally, in non-modulatory steady state, a

corticospinal system (from primary motor cortex directly to CPG) would control limb-trunk

movements [30, 32].

Although the isolated spinal cord CPG and brainstem locomotor regions may elicit rhythmic

movement of the legs in some circumstances, [34, 35], it is clinically well recognized that they must

be initially activated by cortical commands [36, 37]. This is why humans with severe spinal lesions but

intact brain have paraplegia and spinal stepping is only possible when the body is unloaded in this

situation [38, 39]. Numerous evidences demonstrate the importance of the cortical areas in the

control of human locomotion. Among these, the supplementary motor area (SMA) is implicated in

initiation and termination of gait [40-42]. Lesion of this cortical area results in gait apraxia [43].

Other premotor (PM) regions play a role for navigation in narrow passages [44] and formed a

complex network revealed by neuroimaging studies involving the primary motor cortex, the primary

somatosensory cortex, the SMA, the parahippocampal and fusiform gyri [45], subcortical regions

involved in locomotor control, including basal ganglia, thalamus, cerebellum, and spinal cord [46-49].

Visual feedback guides motor planning via posterior parietal cortex [50, 51]. These processes

generate muscular pattern separately from that of locomotion. The coordination of locomotion with

voluntary task would be accomplished through a superposition of motor programs [52]. Cerebellum

and proprioceptive feedback assists processes to control timing and balance [53]. A locomotion-

inducing site has been found on the midline of the cerebellar white matter close to the most rostral

pole of the fastigial nucleus [54], a region that was also implicated during walking imagery [55].

3. EEG during walking execution

Gait is classically studied in terms of kinematics, described by a juxtaposition of several gait cycles. A

gait cycle is defined as the movement performed between two successive contacts of the same heel

on the ground (Fig.1a). For each side, each cycle consists of a stance phase and a swing phase. It

engages almost all muscles of the body with coordination [56-59] such that the plane of the gaze,

named Frankfort plane, is kept close to the horizontal [60].

Figure 1: A, Figurines representing the gait cycle. B,C, Event-related spectral perturbation (ERSP) during walking

cycle recorded in C3 and C4 electrodes for one subject. The stripped lines indicate the right heel strike event

A

B

C

upon which the averaging was triggered. The power increase is represented in red color and the power

decrease in blue color. (Modified from [15] Cheron et al., 2012, with permission)

The analysis of the EEG oscillation during walking execution necessitated synchronization between

kinematics data and EEG signals. Optoelectronic systems allow reconstructing the elevation angles of

both feet as a function of time. Then a peak-detection algorithm is used to precisely localize the

successive heel-strike and push-off events. EEG signals are processed by different EEG-specific

toolboxes, for example: the EEGLAB toolbox [61], which includes artifact rejection, high-pass filtering

(above 1Hz), and independent component analysis (ICA) for extracting the component related to eye

movement.

In accordance with different studies ([14, 62-65] the analysis of the event related spectral

perturbation (ERSP) during walking shows specific power increases (interpreted as an event related

synchronization, ERS) or decreases (even related desynchronization, ERD).

Figure 1 illustrates such type of results recorded from C3 and C4 electrodes which are anatomically

placed over the left and right sensorimotor areas corresponding to the left and right hand region,

respectively, during 50 walking cycles. In this case the averaging was triggered when the heel of the

leading foot (right side) was touching the ground (0%, dotted line) and the trailing foot was pushing

off (green line). Just after the heel strike of the right foot an alpha (9-12Hz) –beta (15-20Hz) ERS was

recorded in C3 and not in C4, a reverse situation was later recorded after the heel strike of the left

foot. Given the fact that walking execution involves a whole-body experience, this activation pattern

might be related to discrete elements in this experience, e.g. arm swing during gait, which could

correspond to synchronization and/or a change in the frequency of activities within a group of

neurons. These should make it possible to use real-time EEG signals for piloting prosthesis or

exoskeleton [15, 66, 67].

3.1. Walking movement artifacts

One of the major problems not yet resolved concerns the presence of multiple types of artifacts.

Indeed, we have recently demonstrated [68] that harmonics of the fundamental stepping frequency

recorded by accelerometer placed on the top of the head were found in the EEG signals spectrum

(Fig. 2 C,D) corresponding to the fundamental stepping frequency of the subject ranging from 0.6 Hz

at 1.5 km/h to about 1 Hz at 4.5 km/h. Figure 2 shows that harmonics are present up to 15 Hz and 30

Hz in accelerometer and EEG signals, respectively. In addition, ERS (red surfaces) and ERD (blue

surfaces) appear during each heel strike and swing phase, respectively and that for a large frequency

band ranging from low-delta to high-gamma (150 Hz) in accelerometer and EEG signals. The fact that

artifact pollution of EEG signals is dependent on the electrode location on the scalp and because

different quantities are measured by accelerometers and EEG electrodes, the gait related artifact

render artifact cleaning more complex than applying a general band-pass filter, ICA or PCA

mathematical procedures. In this context, a recent study of Kline et al. (2015) paves the way for

future development of hardware artifact detecting system. The idea is to isolate and quantify

movement artifact by means of a silicone swim cap placed between the AgCl EEG electrodes and the

scalp. This montage allows to block all physiological signals (EEG, ocular, muscular, etc.) from the

recording electrode. The placement of a wig coated with conductive gel between the recording

electrodes and the swim cap allows the simulation of the conductive medium found in normal EEG

recording conditions. By this montage, an artifact only signal was recorded with the AgCl electrodes

[69] allowing future development of a cap containing double type of electrodes, one for classical EEG

+ movement artifacts and one with only movement-related artifacts. Thanks to this hardware system

adequate interpolative subtraction could suppress movement artifacts at the level of each electrode

couple and that in real time.

Figure 2. Harmonics of walking present in the EEG electrode (Cz) and measured by an accelerometer placed on

the top of head cap (B). ERSP of EEG recorded in Cz (C), Oz (D) and of accelerometer signal (E) during a walking

speed of 1.5 km/h on a treadmill. The color scale is in dB. Right heel strike (RHS). Left toe off (LTO) (Modified

from [68] Castermans et al., 2014).

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Figure 3. Walking imagery: Illustration of the “forward step- imagery action- backward step” paradigm. In the

upper part, the foot elevation angles of both feet are superimposed (right foot in blue, left foot in orange). In

the lower part, the ERSP recorded by a frontal (FCz) electrode and triggered by the first right toe-off event.

Note the presence of three ERS burst (red) in the alpha frequency range (9-12 Hz) during the forward walking

period and the presence of an ERS in the beta (15-20 Hz) during walking imagination.

4. EEG during walking imagery

The recording of EEG recording during walking execution is made difficult by the serious problem of

artifacts. Therefore, many researchers have turned their attention to the study of walking brain

dynamics when the descending motor commands are blocked. This occurs during observation or

imagery of walking. The visual information memorized in the visual cortical network is reactivating

during the latter situation. EEG dynamics offers the possibility to follow for each frequency band of

interest the ERS/ERD sequence. For alpha and beta oscillations, an ERD can be interpreted as an

index of cortical activation while an ERS may be associated to an inhibitory activity.

The application of EEG dynamics method requires the repetition of experimental trials for obtaining

ERSP data during walking imagery. It is also important to precisely index the onset and ending of the

subject’s imagery performance and record their actual accomplishment of imagery. The introduction

of any type of sensory events given to the subject for initiating or ending their imagery sequence

might interfere with the self-paced imagery process. For example a short beta ERD due to visually

orienting reflex recorded in the cue-paced motor imagery used for Brain-Computer Interface [70]

may complicate the recording of neural oscillation purely related to imagery. It is therefore

important to develop paradigms in which imagery is self-paced rather than triggered by an external

cue. For example, the participant may be asked to perform a single step cycle directly followed by an

imagery action remembering the previous walking step. When the imagery sequence is ended the

participant is asked to make one step cycle backward before doing the sequence again (forward step

- imagery action - backward step). In this paradigm, the leg movement kinematics is used to

synchronize the ERSP analysis and without any external cues. Figure 3 illustrates in parallel the

kinematics (Fig. 3A) and the ERSP (Fig. 3B) recorded during this experimental paradigm in one

representative participant. When right heel-off events (n=50) are taken as trigger for ERSP

presentation a series of ERS and ERD sequences emerge during the forward step-imagery action and

backward step, summarized as follow: (1) a theta ERS occurs before the initiation of the step cycle,

(2) it is followed by a theta ERD during the step cycle concomitant to 3 bursts of alpha (10 Hz) ERS,

then (3) at the end of the movement a clear frequency shift toward beta ERS (15-20 Hz) concomitant

to ERD in the upper frequency range accompanies the imagery action. Thereafter, the backward step

is initiated.

The presence of alpha ERS during walking may be interpreted as reflecting global inhibition of the

cortex, improving behavioral performance by facilitation of the cognitive control [71-75]. This

suggests that the presence of alpha ERS burst may represent a ‘windshield wiper’ [76] effect through

pulsed inhibition in order to update incoming information during walking. The rhythmic shift toward

beta range during the walking imagery period can be discussed in relation to the fact that motor and

somatosensory cortical areas are known to generate beta oscillation [77, 78] and to modulate it in

relation to motor execution, motor imagery and somatosensory stimulation [79-82]. It was reported

that movement execution and imagination are followed by beta power rebound [83]. Such type of

ERS rebound may be confused with the present ERS occurring after the end of the forward step

sequence. However, in 4 of 7 participants of the Pfurtscheller et al’s study [83] investigating foot

movements, a beta ERS also occurred during the imagery sequence and thus before the beta

rebound (Fig. 1 ). The distinction between beta ERS occurring during imagery and those related to

beta rebound will require more experiments.

A large body of evidence demonstrate that actual movement and motor imagery implicate a same

neuronal network comprising the primary motor cortex [84] SMA, PM, cingulate and parietal cortex

[85, 86] [87] [88-91]. Similar conclusion has been reached for actual and walking imagery [45, 49, 55,

92], revealing activation of a complex motor network [45, 93, 94]. In this context, in order to

facilitate the walking imagery performance realistic visual feedback has been provided to the

participant by virtual reality (VR) environment [95-98]. The fMRI study of Iseki [99] demonstrated

that the SMA and the dorsal part of the PM, are activated during both observation (third-person

perspective) and imagination (first person perspective) of walking in VR environment. Interestingly,

local field potentials in the alpha band have been recorded in the penduculopontine nucleus (PPN) of

Parkinsonian patients during unconstrained walking [100] and imagined gait [101]. These alpha

oscillations correlate with gait speed and with alpha EEG and are attenuated during gait freezing.

5. EEG during walking observation

It is widely accepted that numerous visual areas functionally specialized and hierarchically organized

give rise to a conscious perception of the different attributes of the visual scene [102]. The neuronal

activity follows a ventral stream (the ‘What’ pathway) supporting object vision and a dorsal stream

(the ‘Where’ pathway). The latter divides into three sub-pathways projecting on to the premotor

(supporting visually-guided actions), the prefrontal and the medial temporal lobes (supporting spatial

working memory) both directly and through the posterior cingulate and retro-splenial areas

(supporting navigation) [103]. The discovery of the phase-locking mechanism at the level of the

cortical neurons producing gamma oscillation [104] constitutes a strong scientific foundation for the

binding by synchrony hypothesis [105, 106] even though gamma rhythms in signal processing raise

several signal-processing issues [107].

5.1. Walking observation and the mirror neuron system

The motor theory of perception and the discovery of the mirror neuron system constitute the

theoretical and experimental foundations for approaching a theory that constitutes the basis of

walking observation. The theoretical grounding of such studies is supported by the fact that

movement perception is influenced by implicit knowledge about the working principles of the motor

control system [108, 109]. Discovery of mirror neurons in the monkey [110] has motivated numerous

human studies of visual processes involved in recognition [111-113], and prediction of others'

movements [114, 115]. These approaches were also extended to social cognition [116-119]. Several

technological of approaches have been used in this respect, particularly fMRI and EEG. This has

resulted in much convergence in results but also some divergent evidence within this

literature. Neurophysiological, neuroimaging and behavioral data have demonstrated a high

sensitivity to kinematics of human movement [120, 121] including walking [122, 123] as in a self-

image mirror walking or virtual environment [63], reference frame [122, 124-126]. It is well known

that shape and motion information are treated separately by ventral and dorsal visual streams, and

converge to the posterior portion of superior temporal sulcus [111, 127, 128]. In this context, the

motor theory of perception gives a critical place to ventral premotor cortex in biological motion

perception processes [129].

5.2. VR walking mannequin: normal, upside-down and uncoordinated animation

In the perspective of using the enhancement of brain signals for walking rehabilitation, we have

studied the event-related potential (ERP) and dynamics of theta, alpha, beta and gamma oscillations

induced by the observation of an animated VR walking mannequin. We hypothesized that physical

plausibility of the spatial-kinematic of human locomotion plays a major role in different modes of

neural processing (bottom-up and top-down) implicated in locomotion recognition: we expect that

these processes will be reflected in different contributions of rhythmic power and phase-locked

perturbation in different frequency bands and cortical areas. To address this question, we have

recently used an animation representing a human mannequin during walking action performed in

normal, upside-down and uncoordinated conditions (Fig. 4) [122]. When the heel strike of the right

leg was used for triggering the ERSP and inter trial coherence (ITC)analysis we observed that

observation of the normal walking animation was accompanied by alpha-beta and theta ERS followed

by a long lasting alpha ERD (Fig 4 B, E). The ITC showed a theta phase-locked peaked at about 200ms.

For upside down and uncoordinated condition we found a decreased of the alpha ERS and theta

phase-locking. The suppression of the early alpha ERS in upside-down situation indicates that the

inversion of the body presentation rapidly affect the early visual process. Alpha-beta ERD is in line

with previous research showing decrease of alpha band power during perception of human motion

[130, 131]. This was generally related to the desynchronization of mirror neurons activity studied

with EEG and fMRI combination [132]. Relative to this, amplification of alpha-beta ERD in Upside-

down and uncoordinated condition [122] would indicate a recruitment of mirror neurons system.

One possible interpretation of this data might be that mirror neurons are involved in transformation

in reference frame and in reconstruction of coherence motion in order to recognize or predicted

observed motion. We may speculate that the enhancement of the alpha ERD in upside-down and

uncoordinated condition could facilitate a dynamical process throughout the neural network

involved in alpha-beta rhythm generation evoked by the normal walking mannequin.

5.3. Theta phase-locking and emergence of gamma oscillation in walking perception

The ability of the human cortex to produce theta oscillation is now well recognized. Namely, it was

related to sensorimotor integration [133], navigation [134], memory load [135] and working memory

[136-138]. Interestingly, all the different phases of virtual movement during a navigation game

induced an increase of 4-8 Hz oscillation in both hippocampus and neocortex in human [139].

However, the theta oscillations recorded during observation of human locomotion as described

above cannot be specifically ascribed to locomotion per se.

Faster oscillation, in the gamma range (30-100 Hz) must also be considered given the central position

it has acquired in cognitive neuroscience [140]. We have recorded the emergence of gamma ERS at

the occipito-parietal regions (left side) when participants observed the walking mannequin in upside-

down animation (Fig. 4 A,D) and a gamma ERD during the uncoordinated animation (Fig. 4 C,F). This

gamma ERS may be related to a non-phase–locked gamma ERS (60 Hz) occurring at the same latency

when the recognition of an illusory Kanizsa triangle required additional mental reconstruction

compared to an explicit triangle [141]. These results are also in accordance with previous

magnetoencephalography study showing gamma enhancements 100 ms after upright and inverted

point-light walking observation [125]. In line with the global workspace theory, serial and parallel

processes are involved from the widespread treatment of unconscious information to the emergence

of consciousness [142] [143-145]. Additional implicit recognition [146, 147] of upside-down walking

may explain the emergence of gamma ERS.

In contrast, both theta and gamma frequency ranges have not been specifically been demonstrated

to play a specific role in gait to date.

This is intriguing, as theta oscillations are now considered as a basic physiological element involved in

global oscillatory synchronization processes linking multiple brain regions [148, 149]. For example,

the multiplicity of functional roles for theta oscillation was demonstrated by the fact that the

amplitude of theta power recorded in temporal and frontal cortex predicted the behavioral

performance of the subject [150]. Closer to the gait observation task, theta oscillations are related to

the perception of color shape of object and visual attention [151]. It is also involved in different

sensory modalities to provide meaningful chunks of neuronal signals allowing subsequent decoding

for enhanced perception.

Furthermore, in the context of the binding theory, gamma oscillation are seen to emerge from the

synchronous activity of a large ensembles of firing neurons [152-154] and combine different features

of the visual scene to form a coherent percept [105]. High density electrocorticography recording

performed in the macaque [155] showed the emergence of robust gamma oscillation (50-80 Hz)

during natural viewing over most of the recorded visual cortex including V1 and V4. It is the spike-

field coherence in the gamma-band frequency that explains the gamma rhythm enhancement [149,

151, 156-158] assuming neuronal synchronization in this frequency range when visual stimuli are

moving smoothly [159]. The disruption of smooth walking sequence in the uncoordinated condition

may explain the gamma ERD recorded during the latter condition as also well illustrated in the

primary visual cortex of the cat [160]. These authors demonstrated that a smooth movement of the

visual field evoked gamma but in contrast, when the smooth movement was disturbed the gamma

oscillations disappeared.

Figure 4. Kinematics representation of the gait in the three conditions. Upside-down (A) and normal (B)

conditions present the same coherent kinematic sequence; in contrast, uncoordinated condition (C) shows an

incoherent kinematic sequence. ERSP and ITC from O1 electrode. The upper panel (D,E,F) shows the ERSP and

ITC in each three conditions. The lower panel shows difference between upside-down and normal (G), and

between uncoordinated and normal (H) for ERSP and ITC. Areas of statistical significances (p < 0.001) are

indicated by white squares. (Modified from [122] Zarka et al. 2014)

6. Conclusion and perspectives

The study of oscillatory activities in the human brain related to walking has emerged as a promising

field in current neuroscience. The vexed question of rhythmic movement artifacts associated with

gait remains an important issue and has prompted authors to design novel study paradigms that do

not involve actual participant’s movement. Many protocols have thus been developed in order to

avoid or rule out artifacts and get the more comprehensive, reliable information from the execution

as well as walking imagery. This should be done with much caution, as paradigms that do not involve

actual movement may introduce other confounds, hence the need to disentangle walking from

D E F

G H

UPSIDE-DOWN-NORMAL UNCOORDINATED-NORMAL

UPSIDE-DOWN NORMAL UNCOORDINATED

processes such as spatial reorientation in virtual environments. Resolving these confounds is one of

the most important challenges for this field.

In addition, studies of walking observation gives access to changes in theta, alpha, beta and gamma

oscillations related to the perception of natural or unnatural observed movement, providing

arguments to test the eventual modality-specificity of such changes. Current and future studies

concentrating on the implication of these findings for rehabilitation include brain-machine interface,

the development of walking exoskeletons for patients with paraplegia, stroke, Parkinson’s disease,

cerebral palsy or other gait disorders.

Conflict of Interest Statement

The authors declare that the research was conducted in the absence of any commercial or financial

relationships that could be construed as a potential conflict of interest.

Acknowledgments

We thank M. Dufief, E. Toussaint, T. D’Angelo, E. Hortmanns, and M. Petieau, for expert technical

assistance. This work was funded by the Belgian Federal Science Policy Office, the European Space

Agency (AO-2004,118), the Belgian National Fund for Scientific Research (FNRS), the research funds

of the Université Libre de Bruxelles and of the Université de Mons (Belgium), the FEDER support

(BIOFACT), the MINDWALKER project (FP7–2007–2013) supported by the European Commission, the

Secretaria Nacional de Ciencia y Tecnologia (SENESCYT, Ecuador), the Fonds G.Leibu and the

NeuroAtt BIOWIN project supported Walloon Country. The scientific responsibility rests with its

author(s).

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Highlights:

EEG dynamics may help to understand walking execution, observation and

imagination.

Movement artifact remains problematic but hardware methods are emerging.

Brain oscillations related to walking are promising for technological rehabilitation.