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Special issue: Research report

Time-course of motor inhibition during hypnotic paralysis:EEG topographical and source analysis

Yann Cojan a,b,c,*, Aurelie Archimi b,c, Nicole Cheseaux d, Lakshmi Waber e andPatrik Vuilleumier b,c

a Laboratorio de Neurociencia Integrativa, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, ArgentinabDepartment of Neuroscience, University Medical School, University of Geneva, Geneva, SwitzerlandcCenter for Neuroscience, University of Geneva, Geneva, SwitzerlanddDepartment of Anesthesiology, University Hospital Geneva, Geneva, SwitzerlandeDepartment of Psychiatry, University Hospital Geneva, Geneva, Switzerland

a r t i c l e i n f o

Article history:

Received 10 April 2012

Reviewed 1 July 2012

Revised 3 September 2012

Accepted 11 September 2012

Published online xxx

Keywords:

EEG

Paralysis

Hypnosis

Topography

Inhibition

* Corresponding author. Laboratorio de NeuUniversidad de Buenos Aires, Pabellon I, Ciu

E-mail addresses: [email protected], yan

Please cite this article in press as: Cojan Yand source analysis, Cortex (2012), http:/

0010-9452/$ e see front matter ª 2012 Elsevhttp://dx.doi.org/10.1016/j.cortex.2012.09.013

a b s t r a c t

Cognitive hypotheses of hypnotic phenomena have proposed that executive attentional

systems may be either inhibited or overactivated to produce a selective alteration or

disconnection of some mental operations. Recent brain imaging studies have reported

changes in activity in both medial (anterior cingulate) and lateral (inferior) prefrontal areas

during hypnotically induced paralysis, overlapping with areas associated with attentional

control as well as inhibitory processes. To compare motor inhibition mechanisms

responsible for paralysis during hypnosis and those recruited by voluntary inhibition, we

used electroencephalography (EEG) to record brain activity during a modified bimanual Go-

Nogo task, which was performed either in a normal baseline condition or during unilateral

paralysis caused by hypnotic suggestion or by simulation (in two groups of participants,

each tested once with both hands valid and once with unilateral paralysis). This paradigm

allowed us to identify patterns of neural activity specifically associated with hypnotically

induced paralysis, relative to voluntary inhibition during simulation or Nogo trials. We

used a topographical EEG analysis technique to investigate both the spatial organization

and the temporal sequence of neural processes activated in these different conditions, and

to localize the underlying anatomical generators through minimum-norm methods. We

found that preparatory activations were similar in all conditions, despite left hypnotic

paralysis, indicating preserved motor intentions. A large P3-like activity was generated by

voluntary inhibition during voluntary inhibition (Nogo), with neural sources in medial

prefrontal areas, while hypnotic paralysis was associated with a distinctive topography

activity during the same time-range and specific sources in right inferior frontal cortex.

These results add support to the view that hypnosis might act by enhancing executive

control systems mediated by right prefrontal areas, but does not produce paralysis via

direct motor inhibition processes normally used for the voluntary suppression of actions.

ª 2012 Elsevier Srl. All rights reserved.

rociencia Integrativa, Departamento de Fısica, Facultad de Ciencias Exactas y Naturales,dad Universitaria, (1428) Capital Federal, [email protected] (Y. Cojan).

, et al., Time-course of motor inhibition during hypnotic paralysis: EEG topographical/dx.doi.org/10.1016/j.cortex.2012.09.013

ier Srl. All rights reserved.

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c o r t e x x x x ( 2 0 1 2 ) 1e1 42

1. Introduction
Positivity (Pe) reflecting error evaluation or adjustment. Their
Hypnosis can induce striking changes in perception and

behaviour under the influence of specific suggestions, such as

being paralyzed, blind, or hearing sounds e yet the cognitive

and neural underpinnings of these phenomena are still poorly

understood. From the perspective of neuroscience, hypnosis

is generally defined as a modified state of consciousness

(Gruzelier, 2005), characterized by changes in attention and

reduced awareness to the peripheral world (Cojan et al., 2009;

Crawford, 1994; Raz and Shapiro, 2002; Spiegel and Spiegel,

1978). Because these effects imply a dissociation between

the phenomenal experience of the hypnotized subject and the

actual state or stimulation from the outside world, a better

understanding of hypnosis would provide invaluable insights

on the ways by which top-down mechanisms can affect

awareness and goal-directed behaviour (Egner and Raz, 2007).

In the current study, we specifically focussed on unilateral

hypnotic paralysis. We examined the neural substrates and

time-course ofmotor control processes underlyingmovement

inhibition during hypnotic paralysis, by recording event-

related potentials (ERPs) during a Go/Nogo motor paradigm

in conditions with and without hypnosis. Our aim was to test

for the similarity in neural activity and the possible temporal

overlap between inhibitory control mechanisms responsible

for hypnotically induced paralysis and those normally

recruited by voluntary suppression of motor action.

Several theoretical accounts of hypnotic phenomena have

invoked a crucial role of “cognitive control” and “supervisory

attentional systems” (Gruzelier, 1998; Hilgard, 1977; Oakley,

1999). However, these accounts diverge in terms of the exact

type of effects of hypnosis on attention, and even propose

changes in opposite directions. According to a first view,

hypnotic phenomena might result from a weakening of

attentional control, while lower-level automatic routines are

still operating freely without normal supervisory control

(Egner and Raz, 2007; Woody and Bowers, 1994; Woody and

Farvolden, 1998). For example, in a classic model proposed

by Gruzelier (1998), the influence of hypnosis on top-down

processes was divided into three distinct levels, correspond-

ing to a gradual inhibition of activity in frontal cortex during

the course of induction. While the first step of hypnotic

induction in this model may recruit executive control systems

in order to produce “sensory fixation”, the second step of

induction is thought to involve an activation of fronto-limbic

inhibitory systems under suggestions of relaxation and

tiredness, which will in turn inhibit more anterior frontal

executive functions in the critical third step. In this model,

therefore, the attenuation of frontal activity and reduced

attentional control constitute an essential component of

hypnotic phenomena, necessary for the subsequent effects of

suggestion.

Kaiser et al. (1997) specifically tested this hypothesis of

reduced executive functions by recording ERPs during a Stroop

task in subjects under hypnosis, without specific suggestion.

These authors hypothesized that an inhibition of frontal

functions should be reflected by a reduction of ERPs typically

elicited by error processing in Stroop tasks: the Error Nega-

tivity (Ne) reflecting error detection, and the Error-related late

Please cite this article in press as: Cojan Y, et al., Time-course of mand source analysis, Cortex (2012), http://dx.doi.org/10.1016/j.cor

results showed a significant reduction for the Pe, during

hypnosis relative to normal state, but no reduction for the Ne.

This was interpreted as a failure of controlled “context

updating” processes with a preservation of unconscious error

detection, and taken as evidence for an inhibition of frontal

executive functions during hypnosis (Kaiser et al., 1997).

However, it should be noted that this study did not use

a hypnotic suggestion concerning the task but rather investi-

gated the effect of hypnotic state per se. Changes in perfor-

mance and error processing in hypnotized (or highly

susceptible) subjects during a Stroop taskmight potentially be

related to several different processes, other than inhibition of

frontal monitoring functions, including a disconnection

between conflict-monitoring and executive control systems,

a failure in the maintenance of task sets, as well as an alter-

ation in motivational state (see Egner and Raz, 2007). There-

fore, the exact mechanisms responsible for the inhibition of

frontal lobe function by hypnosis were not directly tested in

this study.

In contrast, a second view of hypnotic phenomena is that

these imply an increase in executive control and frontal

activity, allowing greater focussing of attention and attenua-

tion of peripheral distractors. Thus, hypnotic suggestions

would modulate or override the activation of habitual

responses or behaviours through heightened cognitive control

(Cojan et al., 2009; Crawford, 1994; Oakley, 1999) e quite

contrary to popular beliefs that conceive hypnosis as a “loss of

control” leading to involuntary acts. In support of this view,

Egner et al. (2005) reported a distinctive pattern of frontal

activation during Stroop task performance (Egner et al., 2005).

Using functional magnetic resonance imaging (fMRI), these

authors found increased activation in anterior cingulate

cortex (ACC) during hypnosis in susceptible subjects as

compared with baseline, as well as with respect to subjects

with low susceptibility. No difference was observed in other

prefrontal areas. These findings were interpreted as reflecting

greater monitoring of interference-related information during

the Stroop task, mediated by ACC, but functional decoupling

with dorsolateral prefrontal cortex (DLPFC) areas normally

involved in selective attention. Again, however, this study

used no specific hypnotic suggestion. Different results

showing reduced ACC activation during a word-colour Stroop

task were obtained in another study where subjects received

a hypnotic suggestion that the words had lost their meaning

(Raz et al., 2005), such that the Stroop interference was actu-

ally abolished. Therefore, it remains unclear where changes in

ACC activity may reflect a cause or rather a consequence of

hypnotic induction. Increases or decreases in ACC are also

found to parallel changes in pain perception during hypnotic

suggestion of hyperalgesia or analgesia, respectively (Rainville

et al., 1997). This modulation might be driven by top-down

influences from other brain regions, but their neural sources

remain to be determined.

Along the same line, hypnotic suggestion of limb paralysis

has been explained by an active inhibition of motor processes

by executive control systems implemented by the frontal lobe

(Halligan et al., 2000; Oakley, 1999). Oakley (1999) suggested

that this active inhibitionmay act to suppress the initiation of

otor inhibition during hypnotic paralysis: EEG topographicaltex.2012.09.013



c o r t e x x x x ( 2 0 1 2 ) 1e1 4 3

voluntary movement or exclude the corresponding experi-

ence of volition from the field of conscious awareness. More-

over, two neuroimaging studies by Halligan et al. (Halligan

et al., 2000; Ward et al., 2003) reported that a hypnotically

induced paralysis of the leg was associated with increased

activation in ACC and right orbito frontal cortex (OFC) when

participants were asked to attempt a movement with their

paralyzed limb, concomitant with a lack of motor cortex

activation. The authors concluded that the activation in ACC

and OFC was probably responsible for an active inhibition of

the motor cortex during attempts to move, under the influ-

ence of hypnotic suggestion. However, such increases could

also reflect enhanced monitoring and conflict processing

given the simultaneous suggestion of paralysis. In an experi-

ment where subjects were instructed to imitate hand move-

ment shown on a screen, similar results were found:

increased activation in ACC, together with frontal gyrus and

insula (Burgmer et al., 2012). Interestingly, this effect did not

depend on the hand side, suggesting that these hyper-

activations might reflect attentionmiddle frontal gyrus (MFG),

conflict detection (ACC), and self-representation processes

(insula) during hypnotic paralysis rather than only motor

inhibition processes. However, no modulation of ACC was

found in another recent study on hypnotic paralysis (Cojan

et al., 2009).

A related hypothesis put forward that hypnotic paralysis

might arise through a modified representation of the self that

is characterized by (hypnotically) impaired motor abilities.

Two recent fMRI studies using a resting state approach have

provided some support to this idea. In a first study where high

and low susceptible subjects were compared after a hypnotic

induction, only the highs showed a reduction in anterior,

superior, medial frontal portion of the default mode networks

(McGeown et al., 2009). A second study on paralysis induction

revealed an increased connectivity of the precuneus with the

right DLPFC, angular gyrus, and a dorsal part of the precuneus,

all areas that could mediate a modified representation of the

self (Pyka et al., 2011).

Interestingly, Oakley (1999) proposed that limb paralysis

induced by hypnosis might be “the product of inhibition after

the intention to move has been generated within self-

awareness so that only the final stage of carrying out that

intention is missing”. Hence, in this view, the intention to

move and mental imagery of movement might still remain

intact despite hypnotic paralysis, again contrasting with the

popular view that the hypnotized subject lacks volition. This

would actually accord with neuroimaging data showing

preserved activation of primary motor cortex during mental

preparation of movement with a hypnotically paralyzed hand

(Cojan et al., 2009). Furthermore, Burgmer et al. (2012) did not

find any effect of hypnosis on brain activity duringmovement

observation, suggesting that early motor processes and motor

mirror systems are not altered by the hypnotic suggestion.

However, the neural mechanisms underlying the inhibi-

tion of motor execution by hypnotic suggestion are still

unclear, and their overlap with those responsible for inhibi-

tion of motor or cognitive responses in other tasks (outside

hypnotic situations) has not been systematically investigated.

In fact, ACC has only rarely been associated with inhibitory

control functions (Braver et al., 2001; Swick and Turken, 2002;


Wenderoth et al., 2005), whereas the voluntary suppression of

motor or cognitive responses has consistently been shown to

depend on the right inferior frontal gyrus (rIFG) and pre-SMA

across a range of different tasks (Aron et al., 2004a, 2004b;

Chevrier et al., 2007; Rubia et al., 2003; Sharp et al., 2010; Xue

et al., 2008).

To determine whether similar prefrontal areas would be

responsible for motor inhibition during hypnotic paralysis and

intentional response withholding, Cojan et al. (2009) used fMRI

in a response inhibition paradigm to compare the effect of

hypnotic suggestion with voluntary inhibition in normal

conditions and with respect to simulated paralysis. A Go/Nogo

task combined with motor preparation was given to partici-

pants who either responded normally with both hands or

receivedasuggestionofunilateralparalysis (eitherviahypnosis

or simulation instruction). This study could thus directly test

whether specific inhibitory processes are activated during

induced paralysis on Go trials, and whether these inhibitory

processes are similar to those employed for voluntary inhibi-

tion on Nogo trials in a normal context and/or for feigned

paralysis.While the results confirmeda selective implicationof

the right IFG in both voluntary motor inhibition on Nogo trials

and simulated paralysis on Go trials, right prefrontal areas

showed an increased activation in all response conditions

during hypnosis, suggesting different inhibitory mechanisms

and a key role of right IFG in selective attention control beyond

motor inhibition only (Cojan et al., 2009).

In the presents study, we used ERP in the same Go/Nogo

paradigm to further elucidate the time-course of the recruit-

ment of inhibitory cortical mechanisms across different

conditions, with and without hypnosis. Several electrophysi-

ological investigations of Go/Nogo or Stop signal paradigms

have reported that two main ERP components are typically

associated with motor inhibition: the N2 and the P3 (Bokura

et al., 2001; Donkers and van Boxtel, 2004; Smith et al., 2007;

van Boxtel et al., 2001). The N2 wave consists of a negative

shift at a latency of 150 msec, with maximal amplitude over

the Fz electrode, whereas the P3 is a positive shift at a latency

of 300 msec, with a maximum at Fz and Cz electrode on the

scalp (Falkenstein et al., 1999). Recent work suggested that N2

and P3 may reflect distinct aspects of cognitive control and

inhibition. For instance, one study found that the N2 and the

P3 were differentially modulated by the amount of response

conflict and response withholding, respectively (Enriquez-

Geppert et al., 2010). Another study (Smith et al., 2007)

compared these ERPs in a Go/Nogo paradigm where the

participants had either to count (covert task) or to press

a button (overt motor task) in response to frequent tones (Go

stimuli) and not to the infrequent ones (Nogo stimuli) (Smith

et al., 2007). The N2 amplitude on Nogo trials did not differ

between the two tasks but the P3 amplitude on Nogo stimuli

was stronger for inhibiting the overt motor response in the

button-press task, compared to the covert counting task. The

authors concluded that only the P3 activity might directly

reflect motor inhibition, while the N2 potential could reflect

a “non-motoric” stage of inhibition control. However, even if

a consensus on the functional significance of the N2/P3

complex in inhibition task seems to emerge from these recent

data, it has also been shown that the P3 may encompass

a wide range of other cognitive control processes, such as




c o r t e x x x x ( 2 0 1 2 ) 1e1 44

context updating, decision making, attentional processes, in

addition to response inhibition (Bekker et al., 2004; Bruin et al.,

2001; Karch et al., 2010; Polich and Kok, 1995). It is unknown

whether this component would also be generatedwhenmotor

inhibition is induced by hypnotic suggestion, or whether it is

specific to voluntary inhibition.

The aim of our study was therefore to determine the

topographical patterns and time-course of brain activity

associated with motor execution and inhibition processes

during a Go/Nogo task, under a hypnotic suggestion of paral-

ysis, in comparison with normal conditions and simulated

paralysis. Our paradigm allowed us to directly test for any

commonality or specificity in ERPs generated by voluntary

motor inhibition on Nogo trials and inhibition caused by

hypnotic or simulated paralysis, in the same participants.

2. Methods

2.1. Participants

We recruited 24 healthy volunteers who were divided in two

different groups: Hypnosis and Simulation (eight women and

fourmen in each group, two left-handed in each). All gave their

written consent to participate according to the Geneva

University Hospital Ethics Committee. They were mainly

students from the medical university, matched for age (20e35

years old) and gender across the two groups. None had a history

of neurological or psychiatry disease, or took medication or

drugs. Participants in the Hypnosis group were taken from

a pool of pre-tested subjects who were screened for hypnotic

suggestibility with the Harvard Group Scale of Hypnotic

Susceptibility, Form A (Shor and Orne, 1963), and reached

a minimum score of 9 positive items. Then, they were also

individually tested on the Stanford Hypnotic Susceptibility

Scale, Form C (Weitzenhoffer and Hilgard, 1962) by an experi-

encedclinician (L.W.), andalso reacheda scoreof 9 on this scale.

Paralysis was produced by hypnosis in one group and by

voluntary simulation in the other group. In the hypnosis

condition, subjects received a suggestion that their left hand

was unable to move, prior to performing the Go/Nogo task.

The hypnotic induction was given by an experienced clinician

(N.C.). Induction was produced by a standard eye roll proce-

dure alongside with relaxation instructions (Maldonado and

Spiegel, 2008), followed by a suggestion describing that the

left hand progressively became heavy, stiff, and eventually

unable to move, while the right hand could still continue to

respond normally. In the simulation condition, participants

were asked to perform the Go/Nogo task while feigning

a paralysis of the left hand, and thus act “as if” they suffered

from motor weakness and “tried” to move their left hand but

were unable to do so. Subjects in the Simulation group were

not tested for hypnosis susceptibility and recruited on their

willingness to participate in an experiment investigating

motor paralysis.

2.2. Data acquisition

We used a Go/Nogo task similar to a previous study by Cojan

et al. (Cojan et al., 2009). Participants were presented with


pictures showing the dorsal view of a left or a right hand,

which could be of three different colours: grey, green, or red.

Each trial started with a fixation cross (duration from 1000 to

2000 msec), followed by a preparation cue (Prep) which

depicted either the left or the right hand in grey colour

(600e1000 msec) and instructed the participant to prepare

a movement (to press a button) with the corresponding hand.

This grey hand could turn either green (Go stimulus) or red

(Nogo stimulus), both with a fixed duration of 750 msec.

Participants had to press the button as quickly as possible

when hand turned green (75%), and to withhold the prepared

response if the hand turned red (25%). After each imperative

stimulus (Go or Nogo), a visual feedback was presented during

1000 msec, signalling correct, incorrect, or no response

detected. The order of presentation of left or right hands was

randomized. Stimulus display and behavioural response

recording were controlled by E-prime v.2 (Psychology Soft-

ware Tools, http://www.pstnet.com).

Four blocks of 120 trials (half right hand, half left hand)were

recorded with a 64-channel Biosemi ActiveTwo system, with

electrodes positioned according to the extended 10/20 system.

Four supplementary electrodes (electro-oculogram) were used

to record the eyes movements and blinks. The EEG signal was

continuously recorded with a sampling frequency of 512 Hz

and the electrodes offset potential was kept below 20 kU.

Both groups were tested in the normal or paralysis condi-

tion (simulated or hypnotically induced) in successive order,

counterbalanced across participants.

2.3. Data processing and analysis

Evoked related potentials were computed offline using

BrainVisionAnalyzer V.2. (Brain Products GmbH) after filtering

between .5 and 35 Hz. Epochs were selected from 100 msec

prior to onset of the stimulus to 750msec after the onset of the

imperative stimulus (Go or Nogo), with a baseline correction

using the 100 msec pre-stimulus recording period. Only

correct responses (to Go/Nogo cues) were analyzed and data

were down-sampled to 512 Hz for analysis.

In addition to standard averaging approach to compute ERP

peaks at selected electrodes (see Picton et al., 2000), we

employed a topographical analysis to determine time-

windows with distinct configurations of electric field corre-

sponding to successive “microstates” in the evoked EEG

response (Lehmann et al., 2010). This topographical analysis

allows the identification of stable configurations of electric

field (topographical maps) associated with different stages of

information processing from perception to motor response

(Michel et al., 2009). Unlike the classic waveform analysis that

concentrates on a few electrodes of interest, the topographic

approach takes into account all the electrodes to explain the

data at each time point (Michel et al., 2004; Pourtois et al.,

2008). Thus, this segmentation approach can isolate periods

with systematic changes in distribution of the global electric

field over the scalp, which are presumably generated by

different sources of activity, and identified in a data-driven

manner without any a priori on specific time point or scalp

sites for effects of interest (Michel et al., 2004).

The topographical segmentation analyses were conducted

with Cartool software (Brunet et al., 2011; freely available at


http://www.pstnet.com



c o r t e x x x x ( 2 0 1 2 ) 1e1 4 5

"http://sites.google.com/site/fbmlab/cartool"). This topo-

graphical analysis used a k-mean cluster analysis based on

the spatial correlation betweenmapswhich group together all

EEG maps with a high spatial similarity in the topographical

distribution of activity (Pascual-Marqui et al., 1995). Two

segmentations were computed on the group-averaged data:

one for the motor preparation phase (time-locked to the grey

hand cue), the other for imperative phase (time-locked to the

green/Go or red/Nogo hand cue). For the preparation phase,

the threshold of correlation for merging maps was set to 90%

and we rejected maps shorter than four time frames. For the

imperative phase, the threshold of correlation above which

themapsweremerged in the same cluster was set to 92%, and

we rejected maps shorter than three time frames. Different

parameters were chosen because of the different duration of

each phase (600 msec for preparation and 750 msec for

imperative phase) and the different distribution of map data

in the two conditions. Indeed, as the duration of the prepa-

ration phase was shorter, it was reasonable to allow fewer

maps to explain the data, by decreasing the threshold of the

correlation and increasing the minimum duration of a map.

The reliability of this segmentation in successive topogra-

phies, which corresponds to the solution with the optimal

number of maps explaining the whole EEG data, was assessed

by two criteria: the Cross Validation (CV) criterion and the

Krzanowski-Lai (KL) criterion. The best ratio between these

values was chosen to select the most robust segmentation

(Brunet et al., 2011; Michel et al., 2004, 2009; Murray et al., 2008).

The results of the cluster analysis are shown with colour-

coded segments under the Global Field Power (GFP) curves (see

Fig. 2). As the dominant scalp topographies are identified in the

group-average data, the segmentation analysis is then verified

statistically at the individual level in order to assesswhichmap

remain significantly present at the individual level in different

experimental conditions (Brunet et al., 2011). The statistical

analysis applies a fitting procedure based on the comparison

between single-subject ERP data from each participant and

topographical maps identified by the cluster analysis on the

group-averaged data (Murray et al., 2008).

Finally, we performed an analysis of the plausible neural

sources for topographies of interest. We then used the

Brainstorm software (Tadel et al., 2011) (freely available for

download online under the GNU general public license http://

neuroimage.usc.edu/brainstorm) and a minimum-norm esti-

mation (MNE) to reconstruct the source and analyze their

time-course of activity, across our different experimental

conditions and specific periods of topographical modulations.

The MNE assumes that the 3D current distribution should

have minimum overall intensity (Michel et al., 2004). The

solution space was based on three-sphere head model with

amatrix of 15 000 solutions points, distributed throughout the

MNI152 brain template.

3. Results

3.1. Behavioural results

ForGo trials in thenormalcontext, bothgroupsrespondedwith

high level of accuracy with both the left and right hand (95.1%


and99.3%respectively for theHypnosisgroup, 89.5%and98.3%

for the Simulators group). By contrast, in the paralysis context

(due to hypnosis or simulation), no responses were recorded

for the left “affected” hand, indicating a successful compliance

with our instructions of paralysis. However, in the paralysis

context, both groups showed a decrease in the accuracy with

the right hand (94.6% and 95.3% for hypnosis and simulator

respectively). A repeated-measures analyse of variane

(ANOVA) on the percentage of correct responses (in normal

context only) revealed amain effect of the hand (p< .001, with

higher accuracy for the right hand) and a main effect of the

group (p ¼ .03, simulators being slightly less accurate).

Furthermore, a second ANOVA comparing performance of the

right hand across experimental conditions showed a main

effect of the context (p ¼ .003), with a higher number of errors

during paralysis than during the normal context. Similar

analyses on reaction times (RT) showed a main effect of Hand

(p < .001), with longer RTs for the left hand. This lower perfor-

mance of the left hand is consistent with normal right-

handedness and thus independent of the paralysis context.

3.2. ERP results

We fist examined ERPs evoked by the preparation cues (grey

hands). A large P1-N1 waveform was observed for each hand

condition and each context, as typically elicited by a visual

stimulus onset, but without any modulation as a function of

paralysis (present or absent) in the two participant groups

(hypnosis or simulation). No differencewas observed between

the right and left hand.

Ourmain goal was to examine electrophysiological activity

associated with the inhibition of motor action in the different

experimental conditions. Voluntary motor inhibition was

probed by correct responses to Nogo stimuli in the normal

condition, which required an interruption of the prepared

action. These trials generated a positive waveform with

maximum amplitude at Cz electrode and a peak around

370 msec after cue onset (Fig. 1A), which was not seen on Go

trials. This Nogo effect is consistent with a P3 component as

commonly reported in other studies on inhibition (Bokura

et al., 2001; Falkenstein et al., 1999; Polich and Kok, 1995;

Smith et al., 2008). In the paralysis context, however, the

positive P3 deflection still occurred on Nogo trials for the right

hand, but this effect was no longer present for the left para-

lyzed hand, for both groups (Fig. 1B). In addition, ERPs on Go

trials were similar in the normal and paralysis contexts, with

no evidence for an extra P3 or any other additional activity

associated with movement inhibition in this condition

(Fig. 1B).

3.3. Topographical segmentation results

We performed two separate cluster analyses of ERP topogra-

phies for the preparation and the imperative phases, respec-

tively, across all trial conditions in each phase. These data

yielded a solution with four stable map configurations (micro-

states) over time for the preparation phase (Fig. 2), and 17maps

for the imperative phase (Fig. 3). These two sequences of maps

explained respectively 94.36% (preparation phase) and 92.25%


http://sites.google.com/site/fbmlab/cartool

http://neuroimage.usc.edu/brainstorm

http://neuroimage.usc.edu/brainstorm



Fig. 1 e ERPs in response to Go and Nogo cues. Data are shown for a) the normal context and b) paralysis context, displayed

in microvolts as a function of time post-cue onset, for electrodes Fz, Cz, and Pz (Go in green, Nogo in red, Left hand in dark,

Right hand in light, Hypnosis group in solid line, Simulation group in dash).

Please cite this article in press as: Cojan Y, et al., Time-course of motor inhibition during hypnotic paralysis: EEG topographicaland source analysis, Cortex (2012), http://dx.doi.org/10.1016/j.cortex.2012.09.013

Fig. 2 e Topographical segmentation analysis during the preparation phase. a) The topographical segmentation results is

shown under GFP curves for the eight different conditions during motor preparation (the two top rows represent left and

right hands in the normal context, the two bottom rows represent the paralysis context). Each colour labels a period of

distinct and stable electric field topography. b) The four topographic maps identified by the segmentation analysis during

a 600 msec post-cue period during preparation are shown with the nasion upward and left scalp leftward, in colours

corresponding to the segmentation.

c o r t e x x x x ( 2 0 1 2 ) 1e1 4 7

(imperative phase) of the variance in ERPs. For clarity, we

present the detailed results for each phase in separate sections.

3.3.1. Motor preparation phaseThe spatial topographical analysis revealed that preparation

cues elicited a succession of four distinct maps over time

(Fig. 2), which appeared identical across the eight experi-

mental conditions. Statistical analyses on the number of time

frames during which these maps were present across condi-

tions did not show any significant effect, suggesting a similar

sequence of processing stages during motor preparation for

the Hypnosis group and the Simulation group, for both the left

and right hands (see Fig. 2 for details). No lateralization

differentiating left versus right hand preparation was

observed in these maps.

3.3.2. Imperative phaseResults from the spatial cluster analysis on ERPs time-locked

to the imperative cue (Go or Nogo) revealed a series of 17

dominant scalp maps explaining the changes in EEG activity

across time and conditions. Topographies were clearly

different between Go and Nogo conditions in the normal

context (Fig. 3A and B; green- vs red-coloured hands, respec-

tively), and such differences overlapped with the peak of the


P3 component observed during inhibition in the waveform

analysis above (Fig. 3A and B). In both groups (Hypnosis and

Simulation), two topographies (maps #8 and #10) were

specifically associated with Go conditions, whereas a unique

topography (map #7) characterized the Nogo conditions. In

both groups also, these topographies were clearly present and

similar for the two hands in the normal context (Fig. 3A), but

they were abolished or modified for the left hand in the

paralysis context (Fig. 3B).

Statistical analyses were performed to formally compare

the number of time frames during which these maps were

present in each condition an each group. A mixed repeated-

measure ANOVA was first performed for maps #8 and #10 on

all trials from the normal context, using Instruction cue (Nogo

vs Go) as within-factor and Group (Hypnosis vs Simulation) as

between-factor. This revealed a significant main effect of

Instruction cue (p < .001), confirming a selective expression of

these twomaps in the Go condition (Fig. 3A, two top rows), but

there was no other main effect, nor any interaction.

Conversely, a similar analysis for map #7 revealed a main

effect of Imperative cue (p < .001), reflecting a specifically

longer expression of this topographical configuration in the

Nogo condition instead (Fig. 3A, two bottom rows). Again,

there was no other effect.




Fig. 3 e Topographical segmentation results for ERPs during the imperative instruction cue (Go vs Nogo). Data are shown for

the Hypnosis group (on the left) and Simulation group (on the right), in either a) the normal context or b) the paralysis

context. Red bars indicate the research window (306e445 msec). c) Topographies of interest appearing during the

306e445msec researchwindow are shownwith the colour code for the corresponding epochs in the segmentation analysis.

c o r t e x x x x ( 2 0 1 2 ) 1e1 48

We then tested for changes due to the paralysis by con-

ducting a repeated-measure ANOVA on the same maps with

Context (normal vs paralysis) and Hand (right vs left) as

within-factors and Group (Hypnosis vs Simulation) as

between-factor. For maps #8 and #10 on Go trials only, this

ANOVA revealed nomain effect but a significant interaction of

Hand � Context (p ¼ .01), which confirmed a selective disap-

pearance of these maps for the Left-Go trials during the

paralysis context (Fig. 3B, first top row), in keeping with the

absence of movement in this condition. However, this loss of

the Go-related maps did not differ between hypnotic and

simulated paralysis (no main effect nor interaction involving

Group; see Fig. 3A, top row in right vs left column).


The same analysis yielded similar results for map #7 on

Nogo trials, with a significant interaction of Hand � Context

(p ¼ .04) as well as a marginal effect of Group (p ¼ .08), but no

other effect or interaction. This again reflected a selective loss

of this Nogo-related map in the paralysis context, during both

hypnosis and simulation.

Most remarkably, the critical Left-Go condition under

hypnotic paralysis revealed a specific map (#11), which

appeared from 344 to 406 msec post-cue onset (GFP peak at

375 msec), and overlapped with the P3 time-window (Fig. 3B,

first row in left column). This topographical activity did not

appear in any other condition. In particular, it was clearly

different in comparison with 1) Left-Go trials in the normal




c o r t e x x x x ( 2 0 1 2 ) 1e1 4 9

context, and 2) Left-Go trials for simulators in the paralysis

context. Since this map was not present in all experimental

conditions (zero time frames were found for several condi-

tions in individual data), we restricted our statistical analysis

to trials from the paralysis context, using an ANOVA with

Instruction cue (Nogo vs Go) as within-factor and Group

(Hypnosis vs Simulation) as between-factor. This showed no

main effect, but a significant interaction between Group and

Instruction cue (p ¼ .04), indicating that this map #11 was

selectively associated with the “paralyzed” Left-Go trials in

the Hypnosis Group (Fig. 3B).

For completeness, we also tested for anymodulation of the

topographical organization of neural activity for the right

hand in each group and each context, but this revealed that

none of these different maps was significantly modified

during the left-hand paralysis in comparison with the normal

context.

In summary, our cluster analysis showed that in the

normal context, conditions requiring motor inhibition were

characterized by a unique topographical distribution (map #7),

while conditions requiring motor execution were represented

by two different maps arising in succession (maps #8 and #10)

during the same time-window, in all groups. However, during

induced paralysis, a unique topography (map #11) replaced

these topographies in the Left-Go condition for the Hypnosis

group specifically. This map #11 was not seen during simu-

lated paralysis, suggesting that neither classical voluntary

inhibition nor residual motor activity were present in this

time-window corresponding to inhibition and motor execu-

tion processes in other conditions.

3.4. Source localization

We next performed a source localization analysis (minimum-

norm BrainStorm) (Tadel et al., 2011) in order to test for the

neural sources leading to the specific topography differences

between conditions. First, we compared sources active in the

Nogo condition (map #7) relative to Go (maps #8 and #10),

during a time-window overlapping with these distinctive

maps and the P3 effect observed in ERPs (304e445 after

instruction cue onset). A t-test was applied on the intensity of

sources activated during this interval in these two conditions,

for the normal context and both groups. This revealed

a significant enhancement of sources in medial prefrontal

areas during the Nogo condition (t > 5.0, p < .001), with a peak

between 380e390 msec (Fig. 4) corresponding to the P3 effect

(375 msec, see Figs. 1 and 2).

More importantly, we then tested for neural sources

underlying the critical difference in activity around

334e406 msec (map #11) in the Left-Go condition under

hypnotic paralysis, relative to sources active in the Left-Go

with a simulated paralysis in the same time interval. Again,

a t-test was applied on the intensity of sources activated

during this interval in each of these conditions. As illustrated

in Fig. 5a, the rIFG was the only region exhibiting significantly

high activity during left hypnotic paralysis (t ¼ 2.16, p < .008),

overlapping with the mean latency of the P3 peak (375 msec).

To further test the modulation of activity in this region

across all experimental conditions, we defined a region of

interest (ROI) in the rIFG with 20 vertices in source space. We


then calculated the distributed inverse solution for each

subject and each condition, and extracted the averaged

intensity of activity in this ROI.

We then performed ANOVAs on these intensity values for

each hand separately (left and right) with the within-factors

Instruction cue (Go vs Nogo) and Context (Paralysis vs

Normal), plus the between-factor Group (Hypnosis vs Simu-

lation). For the right hand, there was a significant main effect

of Instruction cue (p < .003, F ¼ 13.05), reflecting greater

activity in rIFG in Nogo than Go, for both contexts (paralysis

and normal) and both group (Fig. 5B, right graph). For the left

hand, however, this analysis revealed a significant threeeway

interaction of Group � Context � Instruction (p ¼ .037,

F ¼ 4.93). This reflected the fact that, for this hand, a differ-

ential increase for Nogo versus Go arose for both groups in the

normal context (as for the right hand), whereas activity was

higher in the Hypnosis group than the Simulation group

during the paralysis context (Fig. 5B, left graph).

Follow-up ANOVAs conducted for the left hand in each

context separately confirmed a main effect of instruction cue

during the normal state (p < .001, F ¼ 19.08), but a main effect

of Group (p ¼ .005, F ¼ 9.75) during paralysis. Thus, source

activity in the rIFG appeared to be enhanced during both the

Left-Go and Left-Nogo trials during the hypnotic paralysis

context. Taken together, these data therefore indicate that

while Left-Go under hypnosis was associated with a unique

topography configuration (i.e., map #11) reflecting differential

activity in rIFG, this increase was also present in other trial

conditions involving the left hand during hypnotic paralysis.

4. Discussion

Our study provides new insights on the neural substrate and

time-course of executive control mechanisms underlying

motor inhibition induced by hypnosis, and also highlights

functional differences with voluntary motor inhibition

produced by simulation. The role of executive attentional

control during hypnosis has remained unclear in the litera-

ture, with some researchers proposing that it may heighten

monitoring and control functions, associated with increased

activity in frontal regions (e.g., ACC; see Cojan et al., 2009;

Egner and Raz, 2007; Halligan et al., 2000); but other

researchers suggested that it may actually involve reduced

control and hypoactivation of frontal areas, leading to more

automatic behaviours instead (Egner et al., 2005; Gruzelier,

1998; Kaiser et al., 1997). Here, by using a motor Go-Nogo

task which includes a motor inhibition component, we could

directly compare two distinct sources of inhibition, that is,

when required by task demands or when induced by

hypnosis. Our new data dovetail nicely with recent fMRI work

(Cojan et al., 2009) indicating that the right IFG may play a key

role in executive control mechanisms associated with the

induction of hypnotic paralysis.

The behavioural results during our task showed that

participants complied well with instructions in all conditions

and showed appropriate performance in each experimental

context: no response was made with the left hand on any trial

(Go or Nogo) during the paralysis state (in both the hypnosis

and Simulation groups), while very few errors were made in




Fig. 4 e Source localization for Nogo versus Go in normal condition with MNE constraints. Greater activity was generated in

medial prefrontal areas at the peak of activity during this map time-range (around 380 msec) on Nogo trials relative to go

trials in the normal context (both hands collapsed). Time-course of sources in ACC (shown in yellow) for Nogo (red) and Go

(green) conditions.

c o r t e x x x x ( 2 0 1 2 ) 1e1 410

the normal state (97% correct overall). However, the paralysis

context induced a slight decrease in performance with the

non-paralyzed right hand for both groups. This may reflect

a general effect of the context of paralysis and greater atten-

tional demands of the task in this condition, which required

a response to only half of the Go stimuli during the induced

paralysis and thus implied a partly dual task set with different

“rules” for left and right hand (see Cojan et al., 2009). In

contrast, in the normal context, participants had to respond

with both hands similarly, allowing for more concentration

and better accuracy. Importantly, however, this effect did not

differ between the Hypnosis and Simulation groups, and

if anything, the simulators tended to perform worse

Fig. 5 e Source localization for map #11 with MNE constraints. a)

peak activity during the time-range of map #11 (20 vertices). b)

right IFG is shown for the left hand (left graph) and right hand

window. These data indicate a significant threeeway interaction

hand, but a main effect of Go/Nogo (p < .01) for the right hand


(particularly in the normal context), ruling out any global

effect of hypnosis on attention or vigilance during the paral-

ysis context.

Our EEG measures allowed us to probe for the effect of

induced paralysis on neural activity associated with distinct

stages of motor preparation and motor inhibition. In partic-

ular, our modified Go/Nogo task enabled us to test whether

paralysis produced any change in the covertmotor intentional

stages prior to actual movement execution, in addition to any

active inhibition at the time of the execution command itself.

For the preparation phase, both the ERP waveforms and

topographical analysis converged to indicate no significant

modulations in the sequence or amplitude of brain activity

A unique generator was found in the right IFG based on the

Estimation of source intensity from an ROI centred on the

(right graph conditions) during the 304e445 msec time-

between Go/Nogo, context, and group (p < .05) for the left

(in both contexts).




c o r t e x x x x ( 2 0 1 2 ) 1e1 4 11

across all task conditions, suggesting similar steps of infor-

mation processing during the covert preparatory period

preceding the Go/Nogo imperative cue. The absence of

modulation concerning the left hand in the paralysis context

suggests that the participants were engaged in the motor

preparation in the samewaywith both hands. These data thus

also indirectly indicate that the hypnotic paralysis does not

imply a suppression of motor intention for the affected hand,

although we could not observe any positive marker of motor

preparation in this paradigm. Indeed, comparing right versus

left motor preparation in our task did not disclose a reliable

measure of asymmetrical preparatory activation such

as the lateralized readiness potential (Cui et al., 1999;

Muller-Gethmann et al., 2003), presumably due to the short

interval between preparation and execution in this task

(600e1000 msec). In any case, the lack of significant change or

asymmetry in ERP activity during preparation in the paralysis

context is broadly consistent with previous models postu-

lating a persevered motor intention in hypnotic paralysis

(Oakley, 1999), and add to previous findings showing intact

preparatory activation in right motor cortex for a left para-

lyzed hand under hypnosis (Burgmer et al., 2012; Cojan et al.,

2009). Thus, Burgmer et al. (2012) observed normal increases

in the mirror motor system during movement observation

after hypnotic paralysis of the left hand.

We note, however, that in our previous fMRI study using

a similar Go/Nogo paradigm (Cojan et al., 2009), we found

a specific increase in precuneus activity during the prepara-

tion of a left handmovement under the hypnotic suggestion of

paralysis. This effect was attributed to a possible role of

imagery and mnemonic processes associated with this region

in relation to the hypnotic suggestion (Rainville et al., 2002).

No correlate of this effect was found in the current ERP data.

Differences in sensitivity betweenmethods (EEG vs fMRI) and/

or differences in the timing of the presentation of PREP cues in

both studies could explain this discrepancy between the

results of both studies. In our previous fMRI study, the PREP

cues were presented with a longer duration (between

1000msec and 5000msec), while the present study focused on

a shorter time-window of 600 msec after the onset of the cue.

Even if temporal information is not readily accessible with

fMRI, we can assume that different, additional or stronger,

cognitive processes might take place within a longer time-

window. Therefore, our fMRI results could presumably

highlight later or more sustained processes that were not

accessible in the time-range of our analysis in the current ERP

study. This would accord with the view that activity in the

precuneus might reflect slow cognitive processes implicated

in motor imagery, memory, and self-representation (Cojan

et al., 2009) appearing after 600 msec.

The second important result of our study was the finding

that a specific succession of maps (map #8 and map #10)

characterized motor execution on Go trials (in normal condi-

tions), whereas a clearly distinct topography (map #7) arose

for motor inhibition on Nogo trials (in normal conditions).

These distinct maps for execution and inhibition were not

only present for both hands in the normal context but also

present for the normal (right) hand in the paralysis context

(see Fig. 3). Notably, the map associated with inhibition was

characterized by a specific voltage configuration over the


scalp, with a typical central positivity and high amplitude

(strong GFP) peaking 350e400 msec after the instruction cue

onset. Moreover, this map overlapped with the positive

component that was also selectively observed during Nogo

trials in our waveform analysis. Both the topography and

time-range of this inhibitory activity therefore accord with

a P3 effect that has frequently been reported in previous EEG

investigations of motor inhibition (e.g., Fallgatter et al., 1997;

Bokura et al., 2001; Polich, 2007; Enriquez-Geppert et al., 2010).

In contrast, with found no evidence for N2-like activity asso-

ciated with inhibition (see Bokura et al., 2001), but recent

research suggests that increases in N2 may not represent

response inhibition but rather response conflict processing

(Donkers and van Boxtel, 2004; Randall and Smith, 2011). As

there was no direct conflict between successive cues (prepa-

ration followed by instruction) in our paradigm, the current

findings seem consistent with the view that this positive P3-

like ERP configuration provides a reliable marker of neural

activity specifically associated with inhibitory processes

rather than conflict-monitoring (Enriquez-Geppert et al., 2010;

Smith et al., 2008). Furthermore, our source localization

analysis suggested that the distinctive topographical activity

associated with inhibition (map #7) was accompanied with

increased activity in medial prefrontal areas, consistent with

an important role of these areas (particularly supplementary

motor areas) in action inhibition (Coxon et al., 2009; Sagaspe

et al., 2011; Sharp et al., 2010; Tabu et al., 2012). Most criti-

cally, however, our EEG results showed that these inhibitory

processes active during the P3 time-range (map #7) were

similarly recruited during Nogo trials for both hands in the

normal context, but also during Nogo trials for the right hand

in the paralysis context. These findings indicate that the

induced paralysis did not impair information processing

mechanisms underlying motor inhibition for the right hand.

In addition, the absence of this specific EEG topography during

paralysis on the Left-Go trials (in both contexts) also suggests

that paralysis was not produced through the recruitment of

the same inhibitory mechanisms (see also Cojan et al., 2009).

Finally, a third important result concerned a distinctive

pattern of brain activity associated with hypnotic paralysis.

Indeed, we were able to demonstrate that one specific

configuration (map #11) was uniquely observed during the

hypnotic suggestion of paralysis on the critical Left-Go trials

(i.e., with the affected hand). This map was not identified by

the ERP segmentation analysis in any time point during any of

the other experimental conditions, including for the simu-

lated paralysis on Left-Go trials (see Fig. 3). Moreover, this

activity clearly differed from those seen during motor execu-

tion (maps #8 and #10) or voluntary inhibition (map #7). This

observation again highlights a functional difference in the

neural processes involved when a subject subjectively expe-

rienced a paralysis induced by hypnosis and has to execute

a movement, relative to when a subject fakes a paralysis

intentionally. In addition, it is worth noting that the latency of

map #11 also coincided with the latency of the P3 component,

which was related to voluntary response inhibition in the

present study (see above) and previous work (Enriquez-

Geppert et al., 2010; Smith et al., 2007). However, the exis-

tence of distinct topographies implies that they must have

been generated by different configuration of active sources in




c o r t e x x x x ( 2 0 1 2 ) 1e1 412

the brain (Michel et al., 2004). Accordingly, our source locali-

zation analysis revealed a distinctive activation in the right

inferior frontal cortex during the hypnotic paralysis, relative

to the simulated paralysis. These findings therefore suggest

a specific role of executive control mechanisms mediated by

right prefrontal areas in the mechanisms of hypnosis, a result

converging with recent data from fMRI (Cojan et al., 2009)

which also demonstrated a unique pattern of increased

activity in the right inferior and middle frontal gyri during left

hypnotic paralysis. The rIFG activates in various conditions

requiring a suppression or change in motor or cognitive

programs, including Nogo or Stop (Aron et al., 2003; Rubia

et al., 2003; Swick et al., 2011), whereas the rMFG is linked

with high-level executive functions (Talati and Hirsch, 2005),

such as attentional effort (Demeter et al., 2011) and adjust-

ment to novel stimulus-response contingencies (Brass et al.,

2005). More generally, therefore, our data provide new

support to the notion that the frontal cortex is not inhibited by

hypnosis, neither due to the specific suggestion of paralysis,

nor due themore general context of hypnosis. This adds to the

growing evidence that hypnosis may involve specific atten-

tional processes and thus corroborates neurocognitivemodels

linking hypnosis with attentional control (Cojan et al., 2009;

Crawford, 1994; Oakley, 1999; Oakley and Halligan, 2009).

Remarkably, when further inspecting the intensity of

source activity in the rIFG across conditions, we found that it

was also significantly increased by voluntary inhibition on

Nogo trials (relative to motor execution on Go trials) for both

hands in the normal context, and for the right hand in the

paralysis context. This pattern nicely dovetails with func-

tional neuroimaging (Aron et al., 2004a, 2004b; Garavan et al.,

1999; Hampshire et al., 2010; Konishi et al., 1999) and neuro-

psychology studies (for review see Aron et al., 2003; Chikazoe,

2010) that consistently reported that the rIFG is implicated in

tasks requiring response inhibition or executive control, in

concert with other fronto-parietal areas more generally

involved in top-down attention, orienting, or shifting

(Corbetta et al., 2008; Raz, 2004). However, this pattern of

activity in rIFGwasmarkedly (and selectively)modified for the

left hand in the paralysis context: this source showed a rela-

tive increase in intensity for all left conditions (Go and Nogo)

during hypnosis, whereas a relative decrease was seen in the

same conditions during simulation. Taken together, these

data suggest that, even though map #11 was selectively

expressed during the Left-Go trials under hypnosis, the rIFG

might not only be recruited for inhibiting movement with the

paralyzed hand in this condition, but rather bemore generally

engaged for controlling actions with the left hand during

hypnosis (unlike during simulation where it appeared dis-

engaged instead). Moreover, since map #11 was not seen in

our segmentation analysis for other conditions, it is likely that

the rIFG activity reflected by this map might have been mixed

with (and thus masked by) additional sources in fronto-

parietal networks during Nogo trials in the normal condi-

tions, with stronger field power, therefore resulting in

a distinct topography during these trials (i.e., map #7). In

keeping with the latter conjecture, our previous fMRI results

indicated that the right inferior frontal cortex may show

a sustained increase in activity during hypnosis as compared

with the normal state, irrespective of task conditions, which


was interpreted as reflecting a state of globally enhanced

monitoring or “hypercontrol” allowing external stimuli to be

effectively filtered out and internal representations to over-

ride instead. Therefore, our current finding that hypnotic

paralysis was associated with a unique configuration of brain

activity, as revealed by the specific appearance of map #11 in

Left-Go trials in this context, provides striking and converging

evidence across different methods and different populations

that the right inferior frontal areas may play a key role in

attentional mechanisms mediating hypnotic phenomena.

It remains to be clarified however whether this right-

hemispheric laterality, typically observed for both hands

during motor inhibition tasks (Aron et al., 2004a, 2004b;

Garavan et al., 1999; Hampshire et al., 2010; Konishi et al.,

1999), would also hold when hypnotic paralysis is induced

on the right side. Like many previous studies, we focused on

motor function of the left hand only (see also Blakemore et al.,

2003; Cardena et al., 2012; Cojan et al., 2009; Halligan et al.,

2000; Marshall et al., 1997), which could potentially bias the

laterality of our findings. However, our results are thus

comparable with these previous studies, and unlikely to differ

for right-sided motor changes since the most critical brain

areas were not related to elementary motor or sensory func-

tions. Nonetheless, future work should definitely address this

issue by comparing both arms. We also note that a recent EEG

study (Cardena et al., 2012) during hypnotically induced levi-

tation of the left arm reported changes in fast rhythmic

frequencies over the left frontal regions, rather than changes

in the right hemisphere. This difference between this study

and ours could reflect the difference in paradigm and lack of

inhibition during levitation (as opposed to paralysis), and

might accord with fMRI results showing more sustained

activation in left prefrontal cortex attributed to task-set

maintenance during hypnotic suggestion (Cojan et al., 2009).

In any case, the role of each hemisphere and the laterality of

hypnotic effects remain to be more fully clarified. Future

research also needs to better integrate the currentmodulation

of prefrontal control processes observed during an active

motor task with changes induced by hypnosis in the default

mode network at rest (McGeown et al., 2009; Pyka et al., 2011).

In sum, our EEG study adds novel support to previous

hypotheses that the prefrontal cortex is not hypoactive during

hypnosis but rather exhibits significant increases in activity

within brain regions intimately connected to executive

control and attention (Cojan et al., 2009; Ward et al., 2003). Our

data also confirm an involvement of specific control processes

during hypnotic paralysis, distinct from those implicated in

voluntary inhibition under normal conditions (see Cojan et al.,

2009) and reflected by a P3 component in ERPs, but seemingly

operating in the same time-window as voluntary inhibition. It

remains to be seen whether similar patterns are observed in

other hypnotic phenomena characterized by the inhibition of

different motor or sensory modalities.

Acknowledgement

This research was supported by a grant of the Swiss National

Science Foundation to PV and YC (No 32003B-127560).




c o r t e x x x x ( 2 0 1 2 ) 1e1 4 13

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