NeuroImage 117 (2015) 367–374

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What makes your brain suggestible? Hypnotizability is associated withdifferential brain activity during attention outside hypnosis

Yann Cojan ⁎, Camille Piguet, Patrik VuilleumierDepartment of Neuroscience, University Medical School, University of Geneva, 1 rue Michel Servet, 1211 Geneva, SwitzerlandCentre for Neuroscience, University of Geneva, Switzerland

⁎ Corresponding author at: Department of NeuroscienUniversity of Geneva, 1 rue Michel Servet, 1211 Geneva,5402.

E-mail addresses: ycojan@gmail.com (Y. Cojan), camilpatrik.vuilleumier@unige.ch (P. Vuilleumier).

http://dx.doi.org/10.1016/j.neuroimage.2015.05.0761053-8119/© 2015 Elsevier Inc. All rights reserved.

a b s t r a c t

a r t i c l e i n f o

Article history:Received 13 February 2015Accepted 26 May 2015Available online 3 June 2015

Theoretical models of hypnosis have emphasized the importance of attentional processes in accounting forhypnotic phenomena but their exact nature and brain substrates remain unresolved. Individuals vary in theirsusceptibility to hypnosis, a variability often attributed to differences in attentional functioning such as greaterability tofilter irrelevant information and inhibit prepotent responses. However, behavioral studies of attentionalperformance outside the hypnotic state have provided conflicting results. We used fMRI to investigate therecruitment of attentional networks during a modified flanker task in High and Low hypnotizable participants.The task was performed in a normal (no hypnotized) state. While behavioral performance did not reliably differbetween groups, components of the fronto-parietal executive network implicated inmonitoring (anterior cingu-late cortex; ACC), adjustment (lateral prefrontal cortex; latPFC), and implementation of attentional control(intraparietal sulcus; IPS) were differently activated depending on the hypnotizability of the subjects: the rightinferior frontal gyrus (rIFG) was more recruited, whereas IPS and ACC were less recruited by High susceptibleindividuals compared to Low.Our results demonstrate that susceptibility to hypnosis is associatedwith particularexecutive control capabilities allowing efficient attentional focusing, and point to specific neural substrates inright prefrontal cortex.Significance statement:We demonstrated that outside hypnosis, low hypnotizable subjects recruited more pari-etal cortex and anterior cingulate regions during selective attention conditions suggesting a better detectionand implementation of conflict. However, outside hypnosis the right inferior frontal gyrus (rIFG) was morerecruited byhighly hypnotizable subjects during selective attention conditions suggesting a better control of con-flict. Furthermore, in highly hypnotizable subjects this region was more connected to the default mode networksuggesting a tight dialogue between internally and externally driven processes thatmay permit higher flexibilityin attention and underlie a greater ability to dissociate.

© 2015 Elsevier Inc. All rights reserved.

Introduction

Hypnosis is a special state of receptive concentration, allowing oneto filter sensations or thoughts, so as to modify the content of consciousawareness Price (1996). However, it is inducedwith different degrees ofsusceptibility among people (Shor and Orne, 1963). Although hypnosisis widely used for therapeutic applications such as pain relief or anxietyreduction (Hammond, 2010; Jensen et al., 2014), its neural mechanismsremain poorly understood.

Since early accounts in the 19th century (Braid, 1843), theoreticalmodels have underscored the importance of attentional processesin explaining hypnotic phenomena (Gruzelier, 1998). However, two

ce, University Medical School,Switzerland. Fax: +41 22 379

le.piguet@unige.ch (C. Piguet),

opposing hypotheses have been put forward. One view proposes thatindividuals who are highly susceptible to hypnosis (highs) are betterable to focus attention, allowingmore efficient concentration and filter-ing (Barber, 1960; Tellegen and Atkinson, 1974). Another view arguesthat highs may indeed be particularly adept at controlling attentionbut through the decoupling of executive control from sensorimotorprocessing, such that selective attention is actually reduced and behav-ior more easily driven by automatic processes (Hilgard, 1965, 1977;Crawford and Gruzelier, 1992; Woody and Bowers, 1994). Importantly,such individual differences in hypnotizability and attention skills consti-tute stable traits that can be observed outside the hypnotic state (Dixonet al., 1990; Dixon and Laurence, 1992; Egner et al., 2005; Rubichi et al.,2005; Iani et al., 2006). Unfortunately, behavioral studies comparingselective attention performance in highs and lows outside hypnosis havereported conflicting results; some studies using the Stroop task foundlarger interference in reaction times for highs (Dixon and Laurence,1992), supporting greater susceptibility to automatized responses butothers reported smaller interference effect (Rubichi et al., 2005), or no

368 Y. Cojan et al. / NeuroImage 117 (2015) 367–374

difference in Stroop effects between highs and lows (Egner et al., 2005).Using a flanker interference task some authors reported no differencebetween groups outside hypnosis (Iani et al., 2006).

Brain mechanisms of cognitive control have extensively been stud-ied using selective attention paradigms such as Stroop (MacDonaldet al., 2000; Egner and Hirsch, 2005a,b) or Ericksen flanker tasks(Botvinick et al., 1999; van Veen et al., 2001), that both require theparticipant to attend and respond to one stimulus dimension whileignoring another. These tasks recruit a distributed fronto-parietal net-work (Durston et al., 2003; Hazeltine et al., 2003; Brass et al., 2005), inwhich different components play different roles including monitoringand detecting conflict (dorsal anterior cingulate cortex, dACC) (Pardoet al., 1990; Bench et al., 1993; Barch et al., 2001; Milham et al., 2001),strategic adjustment (lateral prefrontal cortex, latPFC) (Aarts et al.,2009; Wittfoth et al., 2009), and implementation of top-down controlon information processing (intra parietal sulcus, IPS) (Egner andHirsch, 2005a,b). Neuroimaging studies of hypnotic relaxation usingStroop tasks reported greater activity in dACC in highs compared tolows (Egner et al., 2005), but lower activity during a hypnotic sugges-tion to suppress semantic word meaning (Raz et al., 2005). Restingstate analyses also suggest differences between highs and lows involv-ing baseline ACC activity and changes in connectivity between thisregion and attentional network with the default mode network whileperforming hypnosis (McGeown et al., 2009; Deeley et al., 2012; Hoeftet al., 2012), which further supports a role for attentional abilities inindividual sensitivity to hypnosis. In addition, highly hypnotizablesubjects show different activations in cortical and subcortical relays ofmotor pathways, including the thalamus, when they perform a motortask under hypnosis, suggesting some gating process that may regulatemotor output and explain the subjective experience of involuntarinessin the hypnotic state (Halligan et al., 2000; Blakemore et al., 2003;Cojan et al., 2009; Deeley et al., 2013; Muller et al., 2013). However,these studies focused on brain activity patterns during hypnosis, but itremains unclear how hypnotic susceptibility affects the efficiency ofbrain networks mediating cognitive control outside hypnosis.

Here we measured susceptibility to hypnosis with the Harvard scalein thirty-two healthy right-handed participants (Shor and Orne, 1963).Then they performed a modified flanker task during fMRI (see Fig. 1).According to the focused attention account, highs should show betterfiltering of irrelevant flankers and reduced interference relative tolows; and this reduction of conflict should elicit lower activity in theconflict detection network including dACC but higher activity in regionsof control (latPFC). In contrast, according to the dissociated control

Fig. 1.Modified flanker paradigm. Participantsmade a response with either the right or lefthand depending on the color of the central target (e.g. hot colors [red and yellow] requiringright hand responses, cold colors [blue and green] requiring left hand responses — or viceversa). Peripheral flankers were either congruent with the response summoned by thecentral target (color of the same type, hot or cold) or incongruent (colors of differenttypes, hot with cold). Color–hand associations were counterbalanced across subjects.

account, highs should exhibit greater interference due greater relianceon automatized processes; they should then elicit higher activity inthe dACC and a reduction in the controlwith lower latPFC activity. Alter-natively, the connectivity between regions responsible for the controland the detection of conflict might be modulated by susceptibility tohypnosis and modulate the behavior. Importantly, by designing thisnovel flanker task with different categories of peripheral distracters,we were able to recruit both cognitive control (i.e. fronto-parietal)and sensory (i.e. visual) systems to different degrees, and thus probefor individual variability in attentional filtering as a function of suscep-tibility to hypnosis. Furthermore, by comparing faces and non-facestimuli as peripheral distracters, we could test how differences in theability to filter out irrelevant information affected sensory responsesat different stages of visual processing, in both early and higher-levelvisual areas (e.g. including the fusiform face area, FFA).

Methods

Participants

Thirty-two healthy right-handed subjects, 18 females and 14 males,volunteered to participate in the study. They had no past neurologicalor psychiatric disease, and normal or corrected-to-normal vision. Theseparticipantswere selected after screening their responsiveness to hypno-sis bymeans of theHarvardGroup Scale of Hypnotic Susceptibility—FormA (HGSHS-A, (Shor and Orne, 1963)) during a group session. This scale isa standard andwidely usedmeasure of hypnotizability (e.g. (Egner et al.,2005; Raz et al., 2005; De Pascalis and Russo, 2013)) examining theresponsiveness of individuals to a variety of hypnotic suggestions.

Task

Wedesigned a novelflanker taskwith face distracters, allowingus tomeasure not only response interference by irrelevant information butalso the level of processing along the visual pathways. Visual stimuliconsisted of iso-luminant circles of four possible colors (red, yellow,blue, green) that were surrounded by four flankers distributed right,left, above, and below the central target. Participants had to makea speeded discrimination response to the central target color andresponded using bothhands (see Fig. 1). Counterbalanced between sub-jects, onehandwas associated to hot colors (red or yellow),whereas theother handwas associated with cool colors (green or blue). The color offlankers always differed from the color of the target and could either becongruent (e.g., yellow surrounded by red or vice-versa for hot colors)or incongruent (e.g., yellow surrounded by green). Orthogonally tothis, flankers could be either faces (with neutral expression) or scram-bled pictures (see Fig. 1). Luminance and contrast was globallymatchedbetween these two flanker conditions. Each display was presented for500 ms, and then replaced for 1.5 s by empty circles appearing with afixation cross in the middle of the central one in order to help maintainattention to the target location. All images were projected on a screenand reflected on a mirror mounted on the MRI head coil, with a size of9.5° visual angle. Null events (i.e. longer inter-trial intervals withoutany stimuli) were introduced in the trial sequence to optimize designsensitivity to BOLD effects. All conditions were presented in 4 blocksof 160 trials (in pseudo-randomized order), separated by short breaks.Prior to fMRI, all participants performed the task for a short trainingblock of 20 trials.

Task performance was measured by recording response times (RTs)and accuracy (% correct) in all four experimental conditions. We re-moved RTs which were away from the mean by more than 2 standarddeviations resulting in the exclusion of 4.4% of the trials. These behav-ioral data were then analyzed with Microsoft Excel and SPSS usingstandard ANOVA and t-test procedures.

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fMRI acquisition and analysis

MRI data were acquired on a 3 T whole-body Trio Siemens system,using the standard head coil configuration. For each participant, struc-tural images were acquired with a 3D-GRE T1-weighted sequence(FOV = 230 mm, TR/TE/Flip = 1900 ms/2.32 ms/9°, matrix =256 × 256, slice-thickness = 0.9 mm); and functional images with aGRE EPI sequence (TR/TE/Flip = 1700 ms/30 ms/90°, FOV = 192 mm,matrix = 64 × 64). Each functional image comprised 36 contiguous4 mm axial slices oriented parallel to the inferior edge of the orbito-frontal cortex. For each of the four experimental blocks, a total of 230functional images were acquired continuously.

Functional images were analyzed using the general linear model(Friston et al., 1998) for event-related designs in SPM8 (WellcomeDept. of Imaging Neuroscience, London, UK; http://www.fil.ion.ucl.ac.uk/spm). All images were realigned, normalized to an EPI-template(re-sampled voxel-size of 3 mm), spatially smoothed (8 mm FWHMGaussian kernel), and high-pass filtered (cutoff 128 s).

Statistical analyses were performed on a voxelwise basis across thewhole-brain using standard methodology. Individual events weremodeled by a synthetic hemodynamic response function (HRF). Five re-gressors were used to model experimental conditions: congruent trialsfor face and non-face (scrambled) flankers separately; and incongruenttrials for face and non-face flankers. Furthermore, we added a regressorfor error trials. To account for residual movement artifacts after realign-ment, movement parameters derived from realignment corrections(3 translations, 3 rotations) were entered as covariates of no interest.Statistical parametric maps were generated from linear contrasts be-tween the HRF parameter estimates for the different conditions.

A random-effect group analysis was then conducted on contrastimages from the individual analyses, using a flexible factorial ANOVA(Friston et al., 1998). To determine activation differences due to individ-ual level of hypnotic susceptibility, the HGSHS-A score was added as aparametric covariate in the second-level design matrix as well as theglobal RT of the task. Note that a categorical analysis with two groups(highs and lows) was also performed and showed globally similar re-sults (not reported). As standard practice, focal activationswere consid-ered as significant at a voxel level of p b 0.001 (uncorrected,whole brainanalysis). For main contrasts, the voxels also survived a correction formultiple comparisons (FDR p b 0.05 in 10 mm sphere).

To further investigate the mechanisms of attentional filtering andtheir modulation by hypnotic susceptibility, we also conducted an anal-ysis of functional connectivity between regions found to be involved inattentional control in our paradigm. After selecting a region of interest(ROI) in the rIFG based on the main effect of congruency in the flankertask (see result section), its functional connectivity across conditionswas assessed by using a psycho-physiological interaction PPI analysis(Friston et al., 1997). The first eigenvariate of the time series of voxelswithin the seed ROI (rIFG) was deconvolved from the HRF in order togenerate an estimated neuronal time series (Gitelman et al., 2003),which was then multiplied by a vector coding for the psychologicalcontext (i.e., incongruent vs. congruent trials) and reconvolved withthe HRF. This new predictor was entered into a GLM along with thepsychological-context vector, the original eigenvariate time series forthe seed region, and covariates of no interest (the same as in the preced-ing analysis). Finally, to determine whether these modulations of con-nectivity were linked to susceptibility to hypnosis, we performed a

Table 1Behavioral results.

Cf If

Reaction time (ms (SEM)) 464 (12) 499 (13)Highs/lows 492 (21)/424 (16) 530 (20)/45Error rate (% (SEM)) 3.04 (0.43) 7.68 (1.17)Highs/lows 1.40 (0.29)/4.10 (0.69) 4.42 (1.40)/7

correlation analysis between PPImaps, HGSHS-A scores aswell as globalRT of the task.

Results

Behavior

Response times (RTs)were compared across the four different flank-er conditions using a 2 × 2 repeated-measure ANOVA with congruency(same vs different color–response association) and nature (face vsscramble) of flankers as factors. As predicted, there was a significantcongruency effect on RTs (F(1, 31) = 56.61, p b .001), reflecting slowerresponses when the target and flankers were associated with differenthands (Table 1). There was no effect or interaction due to the natureof flankers (face vs scrambled image, F(1, 31) = 0.02, p N 0.8; F(1, 31) =0.13, p N 0.7, respectively). The size of the incongruency effect (RT inincongruent condition-RT in congruent condition) did not correlatewith the hypnosis susceptibility score obtained with HGSHS-A (R2 =.0267; p N 0.3). Nonetheless a significant positive correlation wasfound between the mean reaction times (pooled across all conditions)and susceptibility to hypnosis (R2 = 0.185, p b 0.02; Fig. 2A).

The mean error rate was low (average = 3.84 ± 2.34% across allconditions, see Table 1 for details of conditions). There was again a sig-nificant effect of congruency (F(1,31)= 20.26; p b 0.001) but no effect offaces (F(1.31) = 0.38; p = 0.54) and no interaction (F(1,31) = 0.38; p =0.54). In keeping with the RT data, a significant negative correlationwas found between the total error rate (across all conditions) andsusceptibility to hypnosis (R2 = 0.180, p b 0.02; Fig. 2B).

Overall, these behavioral data indicate that our paradigm success-fully produced interference by peripheral flankers, and thus evokedgreater cognitive control on incongruent trials. Because susceptibilityto hypnosis correlated with a decreased error rate and an increasedreaction time, this could reflect different processing strategies betweenhighs (whowere slower butmore accurate) and lows (whowere fasterbut less accurate). Therefore we also calculated an “efficiency index”,defined as a ratio of the hit-rate divided by RT, which is a commonprocedure formeasuring and interpreting behavioral effects that poten-tially reflect a combination of factors (e.g. speed-accuracy trade-offs;(Salthouse and Hedden, 2002)). We found that this global efficiencyindex correlated negatively with susceptibility to hypnosis (R2 = 0.17,p b 0.02; Fig. 2C), demonstrating that even if highs responded slower,they did not compensate by better hit rate. Rather, they appeared lessefficient than lows overall as they took longer to respond for similaraccuracy.

fMRI

Main effects of flanker taskWe first identified brain regions showing a main effect of response

interference by comparing incongruent vs congruent trials (I–C). Asexpected, this contrast highlighted a fronto-parietal network includingthe dACC, superior parietal cortex (IPS), superior frontal gyrus (frontaleye field), and inferior frontal gyri (IFG). Significant increases werealso found in fusiform gyrus and insula bilaterally (Table 2A). Thesefindings demonstrate a robust engagement of the attention network,consistent with previous studies using flanker paradigms (Casey et al.,2000; Botvinick et al., 2001; Wager et al., 2005; Fan et al., 2007).

Cs Is

463 (12) 500 (14)4 (20) 491 (22)/418 (14) 536 (24)/448 (21)

3.04 (0.40) 7.15 (1.33).22 (1.67) 1.68 (0.37)/3.13 (0.77) 4.42 (0.99)/6.83 (1.89)

Fig. 2. Behavioral results. A. Correlation between individual variability in average reaction time (RT) in the flanker task (across all trials) and hypnotizability (HGSHS-A). B. Similar corre-lation with average errors rate. C. Correlation with the efficiency index (ratio of hit rate over reaction time), taking into account both speed and accuracy.

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The main effect of face flankers (relative to scramble) activatedspecifically the bilateral fusiform face area (FFA, Table 2B).

No voxel survived the interaction.

Correlations with hypnotizabilityWe hypothesized that neural activity mediating cognitive control

would vary depending on the level of hypnotizability. To test thishypothesis, we correlated the Harvard score from each individual withthe whole brain activity observed in I N C contrast above. Resultsrevealed a selective positive correlation with the right inferior frontalgyrus (rIFG), indicating that this region was recruited stronger duringconflict trials in individuals with higher susceptibility (Fig. 3). Therewas no negative correlation.

To examine how differences in cognitive control affected sensoryresponses to distracters, we next performed a similar correlation foractivations elicited by the visual content of flanker distracters, usingthe Face vs Scrambled contrast. This analysis revealed a negativecorrelation of hypnotizability with dACC and superior parietal regions(Table 3B), reflecting lower engagement of these areas in highs thanlows in the presence of face distracters. Interestingly, a conjunctionanalysis revealed that these regions were the same as those activatedby the main effect of incongruency (Table 3C). This suggests a greater

Table 2Main task effects.

Condition R/L Brain region x y z Z value

A. I N C L Sup pariet lobule −27 −67 34 6.76R Sup pariet lobule 33 −67 31 6.36L Inf front gyrus −42 2 28 5.61R Sup front gyrus 3 17 49 6.00R Inf front gyrus 42 11 25 5.46R Insula 30 29 −2 4.46L Fusiform 51 −55 −17 4.97L Insula −30 20 4 5.22R Fusiform −51 −55 −14 5.19

C N I R vmPFC 3 38 −17 3.99B. F N S

S N FR FFA 42 −46 −23 4.07L FFA −39 −58 −17 3.97L MTG −63 −31 −2 4.97L Middle occipital −24 −100 4 4.60

Abbreviations: C = congruent, I = incongruent, F = face, S = scramble.

interference elicited by face stimuli (relative to scrambled images)which was enhanced in low susceptible participants. Accordingly,when we analyzed the face-specific response (Face N Scramble) in the

Fig. 3. Brain imaging results. A. The main effect of attentional control (incongruent Ncongruent) during the flanker task across all participants. B. The main effect of type ofdistracters (face N scramble). Threshold = p b 0.001.

Table 3Correlation between brain activity and susceptibility with hypnosis.

Condition R/L Brain region x y z Z-value

A. I N C (positive) R IFG 54 35 10 3.32B. F N S (negative) L Sup pariet lobule −27 −58 40 3.63

R dACC 0 −4 55 4.63L Inf pariet lobule −63 −31 37 5.28

C. Conjunction(correlation hypnosiswith S N F and maineffect I N C)

R dACC 3 11 46 3.89L Inf pariet lobule −48 −40 46 3.83L Sup pariet lobule −30 −58 46 3.30R Sup pariet lobule 30 −70 43 3.60

D. IS N IF (positive) R dACC 9 8 40 4.87R Sup pariet lobule 60 −37 28 5.52L Sup pariet lobule −63 −31 37 5.13

Fig. 4. Correlation of hypnosis susceptibility with activation of brain systems mediating cognitive control. A. The contrast I N C shows a selective positive correlation of higher hypnosissusceptibility (Harvard scale) with increased activity in rIFG (54; 38; 4), reflecting greater recruitment of this area in highs when confronted with interference. B. The contrast F N Sshows a negative correlation of high susceptibility with activity in both ACC and posterior parietal cortex, indicating that lows activate more these regions when distracting flankersare faces.

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incongruent condition and congruent condition separately, we foundthat the incongruent condition was mostly responsible for this correla-tion (Fig. 4). No correlation was observed in FFA or lower-level visualareas as a function of hypnotizability.

ConnectivityWe also examined whether hypnotizability influenced the func-

tional connectivity between brain regions during attention control.To this aim we performed a standard psycho-physiological interactionanalysis using the rIFG as a seed. This analysis revealed a context-specific modulation (incongruent vs. congruent) of its connectivitywith the dorsolateral components of attentional networks includingthe parietal and prefrontal cortex (see Table 4A and Fig. 5A). The latterregionswere functionallymore connectedwith the rIFG in the presenceof interference by irrelevant flankers. There was no modulation of con-nectivity with ACC, however. Furthermore, this pattern of connectivitywas modulated by individual susceptibility to hypnosis. A whole-brainparametric analysis of the PPI connectivity map for the rIFG in theincongruent flanker condition showed a significant positive correlationbetween hypnotizability scores and concomitant increases of connec-tivity with the precuneus, ventromedial prefrontal cortex (vmPFC),and nucleus accumbens (cf. Table 4B, Fig. 5B).

Table 4Differential connectivity of right IFG (54 38 4) on incongruent trials (I–C) as shown by PPI.

Condition R/L Brain region x y z Z value

A. Main effect ofconnectivity

L Mid frontal gyrus −42 20 37 3.98R Orb mid frontal gyrus 30 50 −11 3.69R Mid frontal gyrus 51 20 43 3.57L Parietal −57 −46 31 3.47

B. Correlation ofconnectivitywith hypnosissusceptibility

R/L Precuneus 3 −55 46 3.41L vmPFC −9 35 −14 4.08

Discussion

Ourmodifiedflanker paradigmallowedus to reliably compare selec-tive attention capabilities in high vs low hypnotizable individuals, butoutside the hypnotic state. By manipulating the content of peripheraldistracters, we could investigate the recruitment of control processes(e.g. during interference) and the filtering of sensory information invisual areas (e.g. FFA). Thus, our paradigm allowed us to assess brainactivation patterns corresponding to both the source and the effectof attentional control (Kastner et al., 1999; Corbetta et al., 2000;Vuilleumier and Driver, 2007). Behaviorally, we observed typicalincongruency effects (Eriksen and Eriksen, 1974) for both face andnon-face distracters, that is, slower RTs when task-irrelevant flankerstended to promote a manual response opposite to that required forthe central target. Remarkably, RTs correlated positively with hypnoticsusceptibility, with a general slowing and fewer errors for high suscep-tible individuals. This slowing did not concern incongruent trials only,but all trial types equally. This suggests a difference in task strategywhereby the highs appearmore cautious andmay privilege amore con-trolled processing mode (across all trial types). Thus, highs and lowsmay achieve a globally similar performance in attentional filtering butby employing different “styles” of cognitive control.

Our data accord with a study by Iani et al. (Iani et al., 2006) who re-ported similar behavioral results for a standard flanker task (slower RTsbut also fewer errors for highs). These findings however contrast withstudies using Stroop tasks where no difference was observed betweenhighs and lows outside the hypnotic state (Kallio et al., 2001; Egneret al., 2005). Only one study found better Stroop performance forhighs (Rubichi et al., 2005). However, the nature of response conflictis different in Stroop and flanker tasks, since the overlap between rele-vant and irrelevant stimulus dimensions occurs at a semantic levelin Stroop tasks, but at the perceptual level in flanker tasks (van Veenand Carter, 2005; Nieuwenhuis et al., 2006; Egner and Raz, 2007). Thelatter effects might be more sensitive to attentional capabilities relatedto hypnotizability. More generally, our study provides novel support

Fig. 5. Functional connectivity of the rIFG (54 35 10). A. PPI contrast showing increased connectivity of the rIFGwith a fronto-parietal network in incongruent trials compared to congruenttrials. B. Correlation of PPImapswith hypnosis suggestibility, showing a positive correlation (left panel)with activity in vmPFC and precuneus (right panel). These results indicate that thispattern of increased functional connectivity between rIFG and the latter midline regions during incongruent trials is larger in highs than lows.

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to the notion that attentional control may operate differently inhypnotizable subjects outside the hypnotic state. However, it re-mains to be determined in future research whether such differencesare found only in some tasks (e.g. flanker interference) but not others(e.g. Stroop) by testing the same individuals on a range of attentionaltasks.

At the brain level, we identified a bilateral network encompassingthe ACC, IFG, insula and IPS, that was differentially recruited when pro-cessing incongruent compared to congruent trials, consistentwith otherstudies on cognitive control (Pardo et al., 1990; Bench et al., 1993; Caseyet al., 2000; Barch et al., 2001; van Veen et al., 2001; Fan et al., 2003;Hazeltine et al., 2003; Carter and van Veen, 2007). Critically, both dorsalACC and IPS were more active in individuals with low susceptibility tohypnosis during the incongruent conditions, particularly when faceswere presented in the flankers. ACC is known to mediate responseconflict detection (Carter and van Veen, 2007), whereas IPS is responsi-ble for selective allocation of attention to task-relevant information(Corbetta et al., 2000). In flanker tasks similar to ours, dACC activitywas previously found to covariate with the degree of conflict elicitedby incongruent stimuli (Carter et al., 1998; Botvinick et al., 1999;Kerns et al., 2004), supporting a key role in monitoring and signalingresponse conflict (Botvinick et al., 2001; Botvinick et al., 2004). Severalauthors underscored the role of ACC in hypnosis (Egner et al., 2005;Raz et al., 2005) and suggested that hypnosis might modulate ACCreactivity to response conflicts, but these studies focused on the hypnot-ic state and did not examine ACC activity outside hypnosis. However,differences between highs and lows have also been observed at base-line, outside hypnosis (Egner and Raz, 2007). In our study, even thoughfaces were not relevant for the central color task, lows recruited morethese areas in response to these distracters, suggesting that facesevoked more conflict and needed more attentional resources for beingfiltered out. These data accord with research showing that face stimulicapture attentionmore strongly than other visual stimuli due to their in-trinsic social significance, even with a neutral expression (Vuilleumieret al., 2001). Nonetheless, no difference was found between highsand lows in FFA or other visual areas, suggesting that equal attentionalfiltering was actually achieved by increased activity in ACC and IPS forlows.

Conversely, we found a highly selective positive correlation betweensusceptibility to hypnosis and recruitment of the rIFG during selectiveattention. The more an individual is susceptible to hypnosis, the morethis region is engaged in response to incongruent trials. This result sug-gests that highs exertmore control in conditions associatedwith greaterconflict. Remarkably, such increase in rIFGwas not accompanied by anydifference in behavioral performance for incongruent trials in highscompared to lows. This patterns accords with the idea that highs andlows differ in the way they engaged their executive control system dur-ing selective attention, although they eventually achieve the same levelof distracter filtering overall. It is remarkable that, in a previous fMRIstudy of hypnotic paralysis during a go/nogo task, selective increaseswere also observed in rIFG during hypnosis relative to normal aware-ness, without changes in other components of the cognitive controlnetwork such as ACC and IPS (Cojan et al., 2009). The rIFG activated tomotor inhibition (nogo trials)when the taskwas performed in a normalstate, but it activated to all imperative events (go and nogo) under hyp-nosis. This increase could therefore not be explained bymotor inhibitionalone but was attributed to higher attentional control induced by hyp-nosis (Cojan et al., 2009). Likewise, a study using EEG during hypnoticparalysis (Cojan et al., 2013) also found a distinctive source of activityin rIFG during the P300 time-range when participants performed thesame go–nogo task under hypnosis. In the current study, the rIFG acti-vated stronger in highs than low outside the hypnotic state, while theywere confronted with stimuli interfering with goal-relevant responses.

The rIFG has been consistently implicated in executive controlmechanisms, particularly for inhibition conditions (i.e., go–nogo tasks,stop tasks; see (Xue et al., 2008; Aron et al., 2014). However, someauthors have defended a more general role in the processing of salientor task-relevant information (Corbetta et al., 2000; Hampshire et al.,2009). In support of the latter view, several studies have shown thatrIFG activation during response inhibition is task dependent ratherthan determined by inhibitory demands alone (Simmonds et al., 2008).Moreover, the rIFG is recruited across a range of conditions that requiresustained attention but have no obvious response inhibition component(Duncan and Owen, 2000;Miller and Cohen, 2001; Shallice et al., 2008a;Shallice et al., 2008b; Hampshire et al., 2009) and in some cases requireno overt response whatsoever (Hon et al., 2006). These data suggests

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that the rIFG may play a general role in attentional control, allowing aflexible and rapid adaptation of behavioral responses to currently rele-vant and salient stimuli (Corbetta and Shulman, 2002). Furthermore,there is some evidence that the rIFG is also recruited during attentionalswitching (Dove et al., 2000; Cools et al., 2002; Hampshire and Owen,2006), i.e., when the focus of attention is shifted from one locus or di-mension to another (Monsell, 2003). Both the saliency and the switchingaccounts converge to indicate a key role for rIFG in reconfiguring therepresentation of the currently attended input in order to guide goal-directed behavior.

The current study does not only reveal that rIFG activity is higherfor susceptible individuals in the incongruent condition, but also thatit is more connected with key regions of the default mode network(e.g. precuneus and vmPFC) in this condition. In addition, in all partici-pants, the rIFG was found to be generally more connected with thedorsal attentional network during incongruent trials, irrespective ofhypnotizability. The default mode network is thought to mediateinternal representations from memory as well as emotional regulationprocesses and introspection (Land, 2014; Cavanna and Trimble, 2006).Furthermore, the precuneus has already been found to activate duringhypnotic suggestions (Rainville et al., 2002; Cojan et al., 2009). Takentogether, these results suggest that both introspection abilities andtheir relationship with attentional control play a crucial role in hypnoticphenomena. A particular balance between attention and introspectiveself-centered focusing might constitute key ingredients for permittingone tomodify the content of awareness, so as to replace external inputsor sensations by internally driven imagery and memories under theinfluence of hypnotic suggestions. The classic notion that focalizingattention is responsible for inducing the hypnotic trance (Braid, 1843)may have its origin in this modulation of connectivity between theattention and default-mode networks. In highs, a greater ability or ten-dency to selectively focus attention while simultaneously engagingmore introspective self-monitoring processes, through enhanced con-nectivity between control and internal self-centered representations,might contribute to the subjective experience of “psychic dissociation”,that is considered as one of the core phenomena of hypnosis (Hilgard,1974).

Conclusion

Theoretical models of hypnosis have traditionally emphasized theimportance of attentional control processes in accounting for hypnoticphenomena and susceptibility to hypnosis. However, behavioral evi-dence for differential attentional functioning in highs vs lows haveremained controversial (Egner et al., 2005; Rubichi et al., 2005; Ianiet al., 2009), and neurophysiological models postulating a crucial in-volvement of the frontal lobes inmediating both hypnosis and hypnoticsusceptibility (Gruzelier, 1998) are still largely speculative. A criticalrole of ACC has often been underscored (Egner and Raz, 2007), whereasother components of the attention control system were generallyignored. Our novel fMRI results demonstrate that different parts withinthe fronto-parietal network involved in task-setting (lateral PFC),implementation of control (parietal cortex), and response conflict de-tection (dACC), are differently recruited during the same task depend-ing of individual susceptibility to hypnosis, even outside the hypnoticstate itself. Specifically, we show that rIFG is more recruited by highs,whereas parietal cortex and ACC are more recruited by lows duringselective attention conditions. In addition, the rIFG is more connectedto the default mode network in highs, suggesting a tight dialoguebetween internally and externally driven processes that may permithigher flexibility in attention and underlie a greater ability to dissociatein those individuals. Our results thus provide new evidence for a keyrole of the right PFC in attentional processes implicated in hypnosis,and shed light on the possible neural mechanisms of this fascinatingability of the human mind.

Acknowledgment

This work was supported by grants from the Swiss National ScienceFoundation (SNF no 32003B_127560) and Cogito Foundation, plus anaward of the Geneva Academic Society to PV (Foremane Fund).

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