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Angelo Bona

Altered and asymmetric default mode network activity in a ‘‘hypnotic virtuoso’’: An fMRI and EEG study

09 Gennaio 2012

Altered and asymmetric default mode network activity in a ‘‘hypnotic virtuoso’’: An fMRI and EEG study

S. Lipari a, F. Baglio b,c,⇑, L. Griffanti b,d, L. Mendozzi e, M. Garegnani c, A. Motta f, P. Cecconi a, L. Pugnetti c

a Department of Radiology, Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy b MR Research Laboratory, Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy c Neurorehabilitation Unit, Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy d Department of Bioengineering, Politecnico di Milano, Milan, Italy

e Multiple Sclerosis Unit, Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy
f Department of Clinical Neurosciences, Villa San Benedetto Hospital, Hermanas Hospitalarias Albese con Cassano, Italy

article info

Article history:

Received 24 February 2011 Available online xxxx

Keywords:

Hypnosis
EEG
fMRI
Resting state
Default mode network

1. Introduction

abstract

Very highly hypnotizable subjects are rare, easily induced, and able to manifest the whole spectrum of hypnotic phenomena, including post-hypnotic amnesia.

The aim of this study was to detect and localize by means of quantitative functional MRI and EEG changes in cortical activity during hypnosis induction and deep ‘‘pure hypnosis’’ in a hypnotic ‘‘virtuoso’’ subject. We focused on areas forming the default mode network (DMN), since previous studies found that very highly suggestible subjects in hypnosis showed decreased activity in anterior DMN. During undisturbed hypnosis, our ‘‘virtuoso’’ subject showed not only detectable changes in DMN, but also peculiar activations of non-DMN areas and hemispheric asymmetries of frontal lobe connectivity.

Our findings confirm that hypnosis is associated with significant modulation of connec- tivity and activity which involve the DMN but are not limited to it, depending on the depth of the hypnotic state, the type of mental content and emotional involvement.

A key debate in hypnosis is what happens in the brain during ‘‘pure hypnosis’’ (a condition characterized by the absence of further suggestions after the hypnosis induction) and whether hypnosis involves a special altered state of consciousness (the state-non state debate) (see Kallio & Revonsuo, 2003, 2005; Lynn & Kirsch, 2006). Although many neurophysiological studies indicate that hypnosis is associated with clearcut, controllable and reversible modifications in brain activity and con- nectivity patterns (Egner, Jamieson, & Gruzelier, 2005; Gruzelier, 2006; Oakley & Halligan, 2009), none of the findings have yet resolved the key theoretical debate of hypnosis. Moreover, available findings do not define a unitary brain state, and indi- viduals differ widely in their ability to reach an hypnotic state (McConkey & Barnier, 2004; Terhune & Cardena, 2010). Accordingly, there appears to be no consistent reproducible pattern of functional brain changes associated with hypnosis, nor is there firm evidence concerning specific markers of hypnotizability (Williams & Gruzelier, 2001).

In most cases, in order to reduce variability between subjects, hypnotic states are often studied during externally imposed mental tasks (Cox & Bryant, 2008; Kosslyn, Thompson, Costantini-Ferrando, Alpert, & Spiegel, 2000; Mendelsohn, Chalamish,

⇑ Corresponding author at: Fondazione Don Carlo Gnocchi ONLUS, Via Capecelatro 66, 20148 Milan, Italy. Fax: +39 02 40308290. E-mail address: fbaglio@dongnocchi.it (F. Baglio).

Please cite this article in press as: Lipari, S., et al. Altered and asymmetric default mode network activity in a ‘‘hypnotic virtuoso’’: An fMRI and EEG study. Consciousness and Cognition (2011), doi:10.1016/j.concog.2011.11.006

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Solomonovich, & Dudai, 2008; Raz, Kirsch, Pollard, & Nitkin-Kaner, 2006; Raz, Shapiro, Fan, & Posner, 2002), but this strategy precludes the analysis of what is termed ‘‘pure hypnosis’’ (Rainville, Hofbauer, Bushnell, Duncan, & Price, 2002).

Very highly hypnotizable subjects – also called ‘‘virtuosos’’ – are rare, but they are easily induced and able to manifest the whole spectrum of hypnotic phenomena, including post-hypnotic amnesia (Kallio & Revonsuo, 2003). Such individuals pro- vide a unique opportunity to understand the changes in brain function and connectivity patterns underlying unconditioned hypnosis and its manifestations (Fingelkurts, Fingelkurts, Kallio, & Revonsuo, 2007a).

Over the past decade, the introduction of neuroimaging techniques, has made an important contribution in characterizing the underlying processes involved in hypnotic experiences.

Recently, attention has focused on resting state functional connectivity, which measures low frequency (<0.08 Hz) blood oxygen level dependent (BOLD) signal fluctuations between regions occurring at rest (Fox et al., 2005; Greicius, Krasnow, Reiss, & Menon, 2003). These fluctuations are presumed to relate to ‘‘spontaneous’’ neural activity, especially in cortical areas forming the ‘‘default mode network’’ (DMN). The anatomy of DMN has been characterized using different approaches (Fing- elkurts & Fingelkurts, 2011; Fox et al., 2005; Long et al., 2008; van den Heuvel, Mandl, Kahn, & Hulshoff Pol, 2009; Zang, Jiang, Lu, He, & Tian, 2004), all indicating as ‘‘core regions’’ the medial prefrontal cortex (PFC), the posteromedial cortex (PMC, which includes precuneus, posterior cingulated gyrus and retrosplenial cortex), the inferior parietal lobule (IPL), the lateral temporal cortex (LTC), and the hippocampal formation (HF) (Buckner, Andrews-Hanna, & Schacter, 2008; Fox & Raichle, 2007). There is some evidence that DMN activity during hypnosis shows a different pattern of brain activity com- pared to the non-hypnosis condition (Oakley & Halligan, 2009). Indeed, McGeown, Mazzoni, Venneri, and Kirsch (2009) showed that the induction of hypnosis can reduce anterior DMN activity during rest without increasing activity in other cor- tical regions. However, this was found comparing low and high suggestible subjects and using an fMRI block design approach (alternating the conditions of rest, active task, and passive task), which is different from a unique fMRI resting-state run dur- ing a task-free condition; in addition, the authors did not answer the question concerning the possible changes during ‘‘pure hypnosis’’. Moreover, there have been no attempts so far to characterize hypnosis in the absence of specific suggestions in very highly hypnotizable subjects using resting-state fMRI technique or combined neuroimaging approaches.

Our main purpose was to provide a more comprehensive description of brain activity changes taking place in and out of pure hypnosis in a ‘‘virtuoso’’ subject by the sequential use quantitative EEG and fMRI techniques and to focus the analysis on the DMN. Additionally, we assessed the consistency of the EEG changes in the frequency domain across sequential blocks of hypnotic induction (HI) in order to ascertain whether HI can be modelled as a linear process. Results are also discussed in terms of correspondence between EEG changes and specific fMRI indices of regional cortical activity during baseline and hypnosis.

2. Methods

2.1. Subject and procedure

The participant (M.F.) is a 45 years old right-handed female teacher with no history of neurological or psychiatric illness. She had no previous experience with the EEG or fMRI settings, but having been adequately informed she denied any problem concerning the equipment or procedures and willingly volunteered for this study. She provided written informed consent to participate in the study according to the recommendations of the declaration of Helsinki for investigations in human subjects.

On a scale measuring hypnotic susceptibility, she scored a maximum of 12 points when an independent scorer (not the hypnotist working with her) assessed her with the Stanford Hypnotic Susceptibility Scale, Form C (SHSS-C; Weitzenhoffer & Hilgard, 1962). She is able to reach a deep hypnotic state at the end of a brief induction period and to show the phenomena typical of ‘‘virtuoso’’ subjects (Cardeña, 2005; Hilgard, 1986; Pekala, 1991). In particular, as she loses the sense of time and of self-identify (Tart, 1970), she becomes deeply engaged emotionally and experiences at times feelings of ecstasy and oneness with the universe (Hilgard, 1986), or a great deal of visual imagery related to different personal identities in other historical contexts. The recovery to a normal state of consciousness is quite prolonged and requiresphysical stimulation; post-hypnotic amnesia is present when properly suggested during the induction. Her post-hypnotic phase is also characterized by physical and psychologic exhaustion.

The hypnotic state was induced by an anaesthesiologist with long-standing experience in hypnosis and who was well- acquainted with the participant. He used repetitive sentences, slowly pronounced, aimed at inhibiting rational control over thoughts, such as ‘‘let your mind go’’ or ‘‘your mind does not know . . .’’. After a few minutes during which the subject lay immobile keeping her eyes closed, her breath and pulse rate began to increase and she became diffusely hypotonic (hypnotic cataplexy); knowing she had reached the maximum level of hypnotic trance the hypnotist told her to forget everything from that point in order to induce post-hypnotic amnesia. This was necessary in order to prevent the rehearsal of potentially unpleasant material in the post-hypnotic period.

After the induction (HI), the hypnotist’s role was to maintain the hypnosis for the duration of the EEG and fMRI acquisitions. A first MRI session lasting a total of 9 min was performed before hypnosis induction, following which the EEG recordings took place in a dimly lighted and quiet room adjacent to the MRI Unit. A total of 3 min. of resting with eyes closed and 3 min. with eyes open recording was obtained before the hypnotist began his work. A total of 12 min of recording

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were obtained during HI. At the end of HI period, the electrodes were disconnected. While the subject’s hypnotic state was being maintained by the hypnotist, the subject was carried into the MRI unit to complete a final MRI session lasting 9 min. The recovery to a normal state of consciousness was quite prolonged and needed repetitive stimulation, after which the participant looked fatigued; this prevented further data collection in the post-hypnotic phase.

2.2. fMRI analysis

2.2.1. Data acquisition

Brain structural and fMRI scans were obtained on a 1.5 T Avanto System (Siemens, Enlargen, Germany). A detailed description of data acquisition is illustrated in the supplementary materials. Briefly, resting-state fMRI sequence was collected in two separate sessions lasting 9 min each (out- and in-hypnosis). The subject was instructed to keep as still as possible and to avoid specific thoughts.

2.2.2. Image postprocessing of functional data

A detailed description of MRI analysis is provided in the supplementary material. We compared ‘‘default mode’’ values in (experimental condition) and out (control condition) of hypnosis on the same virtuoso subject. Briefly, Regional spontaneous activity was examined by two complementary metrics: the regional homogeneity (ReHo, Zang et al., 2004), which is a mea- sure of the degree of regional synchronization of fMRI time courses, and the amplitude of low-frequency fluctuation (ALFF, Yang et al., 2007), which reflects cerebral physiological states. Moreover, functional connectivity (FC) analysis was per- formed, in order to measure the signal synchrony among regions that may reflect inter-regional correlations in brain activity. In particular, three regions of interest (ROIs) were localized in left and right middle PFC and in medial PFC (BA10). A voxel- wise FC analysis was then performed to generate FC z-maps. Positive connectivity in the individual FC z-maps means that the spontaneous signal fluctuations in brain networks are in phase with the fluctuations observed in the corresponding ROI; whereas negative connectivity means that the spontaneous signal fluctuations are antiphase related with the fluctuations observed in the corresponding ROI (Fox et al., 2005).

2.3. EEG and pulse rate data collection and analysis

2.3.1. EEG procedure and analysis

A detailed account of EEG methods and analysis is provided in the supplementary material section. Briefly, the EEG was recorded from 32 scalp positions, sampled at 512 Hz/channel with a 16 bits resolution for a total of 6 min of pre-hypnosis resting condition and of 12 min of HI under video-EEG monitoring. The latter condition was subsequently split into four con- secutive 3-min blocks for comparison with the resting condition. Off-line EEG processing included band-pass filtering, semi- automatic artifact removal, 2 s. epochs fragmentation, spectral power density (FFT) analysis, normalization and frequency band averaging. Determination of cortical sources for individual frequency band averages and conditions was performed with the sLORETA package (Pascual-Marqui, 2002). Within-subject comparisons across conditions were carried out on sLO- RETA solutions by means of nonparametric analyses for repeated measures with single-threshold tests to correct for multiple comparisons. Results were displayed as voxel-by-voxel t-values mapped onto template MRI images in Talairach space.

2.3.2. Heart rate and oxygen saturation

During resting and HI conditions heart rate and blood oxygen saturation level were sampled at 1 s intervals by finger infrared pulse oxymetry and subsequently averaged for each block as for the EEG data.

3. Results

3.1. fMRI

Out of hypnosis, the participant showed high ReHo and ALFF values within the DMN areas including PMC, medial PFC, LTC more on the right side, bilateral IPL, and HF more on the left side. The activity in the posterior part of this network extended from PMC to bilateral occipital areas, bilateral supplementary motor areas (SMA); anterior cingulate cortex and basal ganglia (caudate, pallidum) were also recruited (Fig. 1, panel A). The threshold for both maps (ReHo and ALFF) was set at corrected p < .05 with cluster size >54 (determined by the Monte Carlo simulation with AlphaSim in AFNI). Furthermore, FC z-maps analysis showed that medial PFC had positive correlations with PCC.

In hypnosis, the subject’s ReHo and ALFF maps exhibited high values in PMC, bilateral occipital areas, superior and inferior parietal lobule (predominant on the left side), bilateral angular gyri, frontal areas (medial PFC and middle frontal gyrus on the right side), anterior cingulate cortex (BA24), and right PH. With respect to baseline condition, however, lower values were observed in medial and middle PFC (Fig. 1, panel A). The threshold for both maps (ReHo and ALFF) was the same set in the previously described condition (out of hypnosis). Moreover, FC z-maps showed a preserved positive connectivity between the right middle PFC and posterior DMN areas (PMC), whereas the left PFC showed a positive connectivity with no- DMN areas (SMA, pre and postcentral gyri) and a negative connectivity with PMC.

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Fig. 1. fMRI, EEG and Pulse Rate results. Panel A: pattern of ReHo out of hypnosis (left) and during hypnosis (right). Red circles highlight a different activity in occipital cortical areas, whereas blue circles show the asymmetry in frontal brain regions. Panel B: localization of max sLORETA solutions (SPM, t-scores) for the EC vs HI block 4 comparison (red/blue areas for enhanced/reduced power): (1) Delta (1.5–4 Hz) enhanced over right BA7; (2) Theta and Alpha1 (4.5– 10.5 Hz) reduced over left BA17 and 19, bilateral BA18, (3) Alpha2 (10.5–12 Hz) reduced over left BA3, right BA17 and BA24, (4) Beta1 (12.5–18 Hz) enhanced over right BA40, (5) Beta2 (18.5–21 Hz) reduced over left BA40 and BA19, (6) Beta3 (21.5–30 Hz) reduced over right BA10; (7): Gamma (35– 44 Hz) enhanced over left BA40. Panel C: plot of mean raw (bars) and normalized (line) PR values during EO and HI blocks 1–4. See text for statistical thresholds and further details.

3.2. Cortical sources of EEG activities during hypnosis

The pattern of sLORETA changes at the time the subject reached the desired hypnotic state – corresponding to HI block 4 – is summarized in Fig. 1 (panel B), where the largest t-values and the side of prevalence is also shown. Delta power was sig- nificantly increased over parietal areas (R > L) and localized over BA7. Theta and alpha1 power were significantly reduced over occipital areas BA18 and 19, more on the left side. A decrease in alpha2 power density values was also observed over left central and postcentral areas (BA3 and 40), right occipital cortex (BA18), anterior cingulate (BA24, 32) and right inferior frontal cortex (BA47). The most relevant changes – implying more than 50% variations of suprathreshold voxels for a given BA – were seen in the motor, visual, and anterior cingulate areas. A focal increase of sLORETA values in the beta1 band was found on the right posterior temporal area (BA40). Significant decreases from baseline values were found in the remaining beta bands. Beta2 was reduced over the left frontal, central and posterior temporal cortices (BA6, 40 and 19) and anterior cingulum as well; beta3 and gamma band values were largely reduced over medial and lateral right prefrontal cortex (BA10). Finally, gamma values were increased over the left temporo-parietal (maximum on BA39) and middle frontal corti- ces (BA46). As to the side with the largest changes, the left sensorimotor areas prevailed over the right hemisphere and the same was found for the visual areas. The decrease in fast activities over frontal areas was clearly right-sided, whereas an increase was prevalent over the left temporo-parietal regions.

Among the areas contributing to the DMN, a large decrease (>50% of supra threshold voxels) of sLORETA values in the alpha2 band was found over BA23 and 24, and over BA10 in the beta3 and gamma bands; the largest increase – again in the gamma band – was localized in the posterior cingulate cortex (BA29 and 30).

Across HI blocks 1–4 the most consistent changes involved the sensorymotor areas (BA1–6) in the alpha2 band, and the anterior cingulate areas (BA24 and 32) in the beta2 band, both showing significant decreases of sLORETA values; however, we did not find any clear evidence for a linear progression of spectral changes as the subject was hypnotized.

3.3. Pulse rate and oxygen saturation

Measurements of pulse rate (PR) and peripheral blood% oxygen saturation were monitored during the whole experimen- tal session. Mean pulse rate (PR) for the 3 min. EC condition (84.9 ± 2.9) was used as reference to normalize PR of successive 3 min. periods during EO and HI. Z-score transformed means along with raw averages are plotted in Fig. 1 (panel C) showing that mean PR steadily increased from the beginning of HI and reached a plateau at the end of the procedure. Mean PR values exceeded the significance level (2.5 std. from the EC mean) by HI block2 onwards. Because of a ceiling effect, no significant changes in oxygen saturation could be observed in any of the HI periods when compared to the EC period.

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4. Discussion

The main purpose of this study was to verify by means of sequential quantitative EEG and fMRI recordings whether changes in the so-called default mode network occur as a highly hypnotizable subject enters a ‘‘pure’’ hypnotic state, e.g. characterized exclusively by internally driven mentation. fMRI was used to measure DMN brain activity during hypnosis and non-hypnosis conditions while EEG recording was used during hypnotic induction. Globally considered, our results con- firm the hypothesis that deep hypnosis is associated to very significant changes in ongoing neurophysiological measures of brain activity with respect to a pre-hypnotic condition (Crawford & Gruzelier, 1992; Fingelkurts et al., 2007a; Gruzelier, 2006; Halsband, Mueller, Hinterberger, & Strickner, 2009). Concerning fMRI, activations were observed in a complex neural network including occipital, parietal, precentral, prefrontal and cingulate areas (for a review see Oakley & Halligan, 2009). Interestingly, we found a significant enhancement of activity in posterior regions of the DMN (precuneus, posterior cingulate gyrus, retrosplenial cortex, IPL and PH) as opposed to a decreased or modified activity in anterior DMN areas (medial PFC, middle frontal gyrus, anterior cingulate cortex). A recent fMRI study comparing spontaneous brain activity during resting state in hypnosis to the same condition out of hypnosis, also showed that highly susceptible participants exhibit decreased brain activity in the anterior parts of the DMN network during hypnosis (McGeown et al., 2009). In this study, however, sus- ceptible individuals rated themselves as being on average mildly hypnotized, and their resting hypnotic condition was not further described in terms of the type of mental content and subjective experience; the depth of hypnosis and the type of spontaneous mental content may therefore explain why the authors did not find changes in cortical regions outside the ante- rior DMN. Unlike the latter study, we were able to analyze our subject’s brain activity when her depth of hypnosis reached a level consistent with a prevailing engagement by internally generated vivid experiences, which were likely associated to the activation of additional areas not included in DMN, such as the motor (SMA; BA6) and visual cortices (BA17, BA18, BA19) along with no modifications of activity in the posterior DMN regions.

In agreement with fMRI data, at the time of completion of the HI the most relevant EEG changes consisted in a decrease of alpha band activities localized over the motor and the visual areas; this was paralleled by significant increases of gamma band values over the left IPL. A likely explanation for the recruitment of primary and secondary visual areas (calcarine cortex, lingual gyrus and fusiform gyrus) in a subject with eyes closed and wearing an eye-mask, is that as the state of deep hypnosis was reached; she entered a vivid sensory-motor experience with hallucinatory components – which the hypnotist confirmed was the subject’s usual modality of achieving the hypnotic state – consistent with an activation of motor and sensory areas by an imagined interaction. However, if the state of pure hypnosis is not accompanied by visual hallucinations, then increase in alpha rhythm should be suspected. This was indeed shown in the previous studies (Fingelkurts, Fingelkurts, Kallio, & Revonsuo, 2007b). The theory of the ‘‘cortical representation of memory experience’’ (Buckner & Wheeler, 2001; Smith & Kosslyn, 2006) may also suggest an uncontrolled – e.g., not frontally mediated – access to visual associative areas based on the results of brain-imaging, neuropsychological and physiological studies indicating that distinct neocortical regions interact with medial temporal lobe to reinstate a memory. Interactions between the medial temporal lobe and various lateral cortical regions are thought to store memories outside the medial temporal lobe, forming links between the cortical representation of the experience. In our subject we can suggest an uncontrolled access to visual cortical associative areas interpreted as a memory experience.

Another important result emerged from the comparison of ReHo and ALFF maps between the two conditions (in and out of hypnosis). During hypnosis we found significant changes in the right middle PFC (BA10), anterior cingulum (BA24) and striatal area. All these structures are involved in many brain functions. Notably, however, the orbital cortex and the medial PFC have been implicated in memory retrieval and executive function (Aupee et al., 2001), affective values (O’Doherty, 2007; Rolls, 2004), inhibition (Elliott & Deakin, 2005), and conflict resolution (Yeung, Botvinick, & Cohen, 2004). Brodmann area 10, in particular, is involved in metacogniton (Burgess, Scott, & Frith, 2003) and self evaluation (Amodio & Devine, 2006). To be efficient, these cognitive functions require integrated information provided by the amygdala and striatum (Ferry, Ongur, An, & Price, 2000; Fudge, Breitbart, Danish, & Pannoni, 2005). As previously described, our subject exhibited a significantly high- er ALFF in striatal areas, consistent with a change in functional connectivity within the striato-pallidal–prefrontal network. Moreover, the anterior cingulate cortex (ACC) is a functionally complex structure that has been associated with pain sensation, motor inhibition, selective attention, conflict resolution and emotional relevance of incoming stimuli (Raz, Fan, & Posner, 2005). In a recent EEG case study with a single virtuoso subject, Fingelkurts and colleagues (2007b) showed that pure hypnosis is characterized by a pattern of neural activity implying heightened attentional resources. Moreover, in previous PET studies (Faymonville, Boly, & Laureys, 2006; Faymonville et al., 2000), the authors came to the conclusion that the midcingulate cortex mediates the analgesia which can be frequently achieved during hypnosis. This effect appears to depend on changes in the connectivity between ACC and insular, pregenual, frontal and pre-SMA regions as well as brain- stem, thalamus and basal ganglia. While a previous neurophysiological study (Fingelkurts et al., 2007a) reported a decreased interdependence of neuronal assemblies generating beta and gamma EEG frequencies in the whole cortex, but an increase of beta power over prefrontal electrodes (Fingelkurts et al., 2007b), our EEG analysis showed a decrease in fast beta and gamma bands localized over frontal cortices and ACC at the time of completion of the induction phase. This discrepancy may impact the understanding of the role frontal lobes play in hypnosis, e.g. greater activation to support increased attention, as found in some studies (Fingelkurts et al., 2007b; Kallio, Revonsuo, Hämäläinen, Markela, & Gruzelier, 2001), or reduced activation leading to lowered control over more posterior cortical activities, as proposed by others (Egner, Delano, & Hirsch, 2007;

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Gruzelier, 2006). But there is also evidence that fast activities may relate to other dimensions such as hypnotic susceptibility. For example Croft, Williams, Haenschel, and Gruzelier (2002) found that gamma activity (32–100 Hz) sources, localized by LORETA in the ACC, are related to the subjective experience of pain at baseline and during hypnosis in low susceptible indi- viduals, whereas in highly susceptible individuals, gamma was related to pain only at baseline. The issue is further compli- cated by the uncertainties still present in our understanding of the generators of fast EEG activities and of their functional interpretation (Crone et al., 2011; Engel and Fries, 2010) the combination of EEG/MEG recordings and fMRI may help unravel this complex issue in the near future, as is now being shown in the case of far more simple cognitive conditions (Scheeringa et al., 2011).

Another relevant fMRI result concerns the asymmetry of frontal lobe connectivity during the hypnotic condition. FC z- maps showed a preserved positive connectivity between the right middle PFC and posterior DMN areas (PMC), whereas the left PFC showed a positive connectivity with no-DMN areas (SMA, pre and postcentral gyri) and a negative connectivity with PMC. A recent paper comparing low and high susceptible individuals showed that the latter exhibited faster processing on the left hemisphere in baseline condition, and on the right hemisphere when hypnotized, possibly indicating a facilitation of illusory experiences (Naish, 2010). Similarly, Gruzelier (2006), using a haptic shape-discrimination task, showed that highly susceptible subjects in hypnosis have a particular asymmetry and shift in brain function due to reduced left hemi- spheric activity and right predominance. On the contrary, a recent study with EEG sLORETA functional imaging (Cardeña et al., 2012) observed that the left hemisphere and the prefrontal regions (BA10 and BA11) showed stronger excitatory activ- ity in an hypnotic left arm levitation task compared to voluntary left arm lifting. Though we did not employ cognitive or motor tasks in our subject during hypnosis, a clear-cut right-sided decrease of fast activity on the EEG and a side-reversal of FC connectivity pattern on fMRI was observed. Fingelkurts and co-workers (2007b) also described a right-sided dominance asymmetry in a virtuoso subject during pure hypnosis. In agreement with all the above studies, we interpret these data as indicating that the overall functional interplay between the two hemispheres shows laterality effects during hypnosis. Based on the available studies, the latter appear to depend on the chosen task (Cardeña et al., 2012; Gruzelier, 2006), the level of susceptibility (Cardeña et al., 2012; Naish, 2010) and the depth of hypnosis (Fingelkurts et al., 2007b). An unexpected EEG result was the activation of primary and secondary sensory-motor areas, more marked and persistent over the dominant hemisphere, as if the subject was actively moving in the environment. In fact, the blocking of sensory-motor rhythms within the upper alpha range is known to occur during imagined movements, and a reduction of posterior slow alpha activity is a consistent correlate of visual imagery (Cavallaro et al., 2010; Isotani et al., 2001). On fMRI, these sensory-motor areas exhib- ited high connectivity with the left frontal region involved in motor inhibition, as though any real movement correlated with visual imagery had been blocked.

Finally, we observed a significant progressive increase of the mean pulse rate from the resting EC period to HI block 4, possibly indicating that the experience must have been emotionally taxing. Mean heart rate or sympathetic drive had been previously reported to be reduced when hypnosis was induced by suggestions of relaxation, increased with stressful sugges- tions and was even more pronounced during negative emotional hypnotic events (Aubert, Verheyden, Beckers, Tack, & Vandenberghe, 2009; De Pascalis, Ray, Tranquillo, & D’Amico, 1998; VandeVusse, Hanson, Berner, & White Winters, 2010); however it could not be used to reliably differentiate high from low hypnotizable subjects (De Pascalis, Ray, Tranquil- lo, & D’Amico, 1998). An emotional activation was evident in our subject during deep hypnosis and should be considered as a potentially relevant factor in the production of increased asymmetries in functional brain connectivity patterns as compared to non-hypnotic or light hypnotic conditions (Isotani et al., 2001). Finally, contrary to heart rate measures we did not find any evidence for a continuum of EEG changes during hypnotic induction, thus confirming previous observations (Fingelkurts et al., 2007a; Katayama et al., 2007).

The principal limitations of our study concern the A–B design (pre-hypnosis and hypnosis), and the lack of systematic phenomenological probes for assessing depth and phenomenology.

As previously described, the subject’s susceptibility was tested with a standardized scale (Stanford Hypnotic Susceptibil- ity Scale, Form C), but a systematic phenomenological evaluation with a specific self-administered scale was not possible, due to her post-hypnotic amnesia and psychophysical state of fatigue at the end of the session. Nonetheless, we acknowledge the importance of a psychophenomenological approach to phenomenological assessment using reliable and robust method- ologies to test and quantify the subjective experiences associated with hypnosis. This is stressed by a recent work (Terhune & Cardena, 2010) showing that hypnotic virtuosos are distributed across at least two different general patterns of spontaneous experiences during deep hypnosis involving imagery, amnestic and dissociative processes (Barber, 1999; Barrett, 1996). New instruments (e.g. the PCI-HAP, Phenomenology of Consciousness Inventory – Pekala et al., 2010) have also been recently pro- posed to understand the cognitive and affective structures underlying the hypnotic experience (Pekala et al., 2010). However, the use of such detailed self-reported scales is sometimes problematic in very highly hypnotizable subjects if post-hypnotic amnesia is successfully induced. For this reason, we believe that neurophysiological and neuroimaging data are especially valuable in the characterization of the brain processes underlying the hypnotic experiences of these rare subjects (virtuosos). Regarding the design of the study, we adopted an A–B (pre-hypnosis and hypnosis) approach, because an A–B–A–B (Fingelkurts et al., 2007a) or an A–B–A design was not achievable because our subject was also fatigued and unable to repeat the whole EEG–fMRI procedure post-hypnosis. Had we repeated the recordings, the data would have been very likely different from those collected before the hypnotic induction and during the hypnotic phase, leading to an A–B–C design. Nonetheless, we are planning to extend our fMRI and EEG analyses to the post-hypnotic periods of highly susceptible sub- jects who are able to spontaneously recall hypnotic experiences upon reverting to normal consciousness, and to correlate

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neuroimaging findings to the new measures of hypnotic responsivity and experiential response, as recently suggested (Oak- ley & Halligan, 2009).

In conclusion, our study confirms that hypnosis is associated with very significant modulation of brain connectivity and activation patterns which involve but are not limited to the DMN; depending on the depth of the hypnotic state, the type of mental content and the emotional involvement, peculiar activations of non-DMN areas and hemispheric asymmetries can also be observed in hypnotic virtuosos during pure hypnosis.

Acknowledgments

The authors gratefully acknowledge Angelo Bona (MD, anaesthesiologist and psychotherapist, member of the American Society of Clinical Hypnosis and president of A.I.I.Re.), a valued collaborator with extensive experience in hypnosis induction.

Appendix A. Supplementary material

Supplementary data associated with this article can be found, in the online version, at doi:10.1016/j.concog.2011.11.006. References

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