NeuroImage 50 (2010) 639–643

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Regional grey matter volume abnormalities in bulimia nervosa andbinge-eating disorder

Axel Schäfer a, Dieter Vaitl b, Anne Schienle a,b,⁎a Department of Psychology, University of Graz, Universitätsplatz 2/III, A-8010 Graz, Austriab Bender Institute of Neuroimaging, University Giessen, Germany, Otto-Behaghel-Str. 10, 35394 Giessen, Germany

⁎ Corresponding author. University of Graz, Departmtätsplatz 2/III, A-8010 Graz, Austria. Fax: +43 316 380

E-mail address: anne.schienle@uni-graz.at (A. Schien

1053-8119/$ – see front matter © 2009 Elsevier Inc. Adoi:10.1016/j.neuroimage.2009.12.063

a b s t r a c t

a r t i c l e i n f o

Article history:Received 9 July 2009Revised 19 October 2009Accepted 15 December 2009Available online 24 December 2009

Keywords:MRIVBMBinge-eating disorderBulimia nervosa

This study investigated whether bulimia nervosa (BN) and binge-eating disorder (BED) are associated withstructural brain abnormalities. Both disorders share the main symptom binge-eating, but are considereddifferential diagnoses. We attempted to identify alterations in grey matter volume (GMV) that are present inboth psychopathologies as well as disorder-specific GMV characteristics. Such information can help toimprove neurobiological models of eating disorders and their classification. A total of 50 participants(patients suffering from BN (purge type), BED, and normal-weight controls) underwent structural MRIscanning. GMV for specific brain regions involved in food/reinforcement processing was analyzed by meansof voxel-based morphometry. Both patient groups were characterized by greater volumes of the medialorbitofrontal cortex (OFC) compared to healthy controls. In BN patients, who had increased ventral striatumvolumes, body mass index and purging severity were correlated with striatal grey matter volume.Altogether, our data implicate a crucial role of the medial OFC in the studied eating disorders. The structuralabnormality might be associated with dysfunctions in food reward processing and/or self-regulation. Thebulimia-specific volume enlargement of the ventral striatum is discussed in the framework of negativereinforcement through purging and associated weight regulation.

© 2009 Elsevier Inc. All rights reserved.

Introduction

The common essential feature of bulimia nervosa (BN) and binge-eating disorder (BED) is the occurrence of recurrent binge episodes.Binge-eating refers to the intake of large amounts of food in arelatively short period of time. The afflicted individuals reportimpaired control while overeating and subsequent distress (APA,2000). Whereas in BN binge-eating is followed by compensatorybehavior to prevent weight gain (most frequently self-inducedvomiting), such regular activities are absent in BED. Despite thehigh lifetime prevalence of BED and BN (3.5% and 1.5% in women)studies on the functional as well as structural neuroanatomy of theseeating disorders are rare (Hudson et al., 2007).

Functional brain imaging has provided convergent evidence forthe role of the (medial) prefrontal cortex for the processing of foodcues in BED and BN (Karhunen et al., 2000; Uher et al., 2004; Schienleet al., 2009). In a single photon emission computed tomography study,female BED patients and non-binging women looked at a freshlycooked lunch. The food presentation provoked increased prefrontalactivation in the patients which was positively correlated withfeelings of hunger (Karhunen et al., 2000). In an fMRI experiment

ent of Psychology, Universi-9808.le).

ll rights reserved.

(Uher et al., 2004), bulimic and anorexic women were exposed toimages of food. The symptom provocation led to increased activationof the medial orbitofrontal cortex (OFC) and the anterior cingulatecortex (ACC) in the patients relative to a healthy comparison group.The authors relate the altered medial prefrontal response to thecompulsive features typical for both conditions. Schienle et al. (2009)observed a recruitment of OFC regions (medial, lateral), the ACC andthe insula during the viewing of food pictures in patients afflictedwithBN, BED, and in healthy individuals. Moreover, there was evidence fordifferential processing of visual food cues. Bulimic women respondedwith more subjective arousal as well as increased activation of theACC and the insula. The two brain areas are involved selectiveattention (ACC) and interoception (insula). By comparison, BEDpatients reported elevated reinforcement sensitivity and showedenhanced recruitment of the medial OFC. This region is part of thebrain reward system (Gray &McNaughton, 2000). Finally, Marsh et al.(2009) compared women with and without BN during a selectiveattention task (spatial incompatibility). The BN patients made moreerrors and failed to activate the OFC and the ACC. As these areas arecognitive control regions, the authors propose a self-regulatory deficitin bulimic patients.

Structural brain abnormalities in BN and BED patients have hardlybeen investigated. Earlier findings indicated diffuse brain atrophy(e.g., enlarged ventricle size) in patients with bulimia nervosa(Hoffman et al., 1989; Laessle et al., 1989). Approaches such as

640 A. Schäfer et al. / NeuroImage 50 (2010) 639–643

voxel-based morphometry (VBM) which allow investigating localizedabnormalities in brain volume are lacking for eating-disorderedpatients. One exception is a VBM study on recovered patients withanorexia and bulimia nervosa (Wagner et al., 2006). The patients hadbeen symptom-free for at least 2 years. Relative to women who hadnever suffered from eating disorders, recovered BN patients showedincreased insula volume. Besides this one difference, all three groupswere comparable in grey matter volume. Unfortunately, the patientshad not been studied during the acute phase of their disease.

Another VBM study on healthy obese individuals found reducedgrey matter density in several brain regions (middle frontal gyrus,putamen, postcentral gyrus, frontal operculum) relative to leancontrols (Pannacciulli et al., 2006). Moreover, the BMI of obeseparticipants was negatively correlated with grey matter density of thepostcentral gyrus. The authors point out that the identified regions areimplicated in taste processing (frontal operculum/extended insula;postcentral gyrus) and reward processing (putamen), whichmight berelated to altered eatingpatterns in obese individuals. Finally, there aretwoVBM investigations onpatientswith abnormal eating patterns dueto frontotemporal lobar degeneration (Whitwel et al., 2007; Woolleyet al., 2007). In both studies, hyperphagia and the craving of sweet foodwere associated with grey matter loss in the OFC and the insula.

As it is still not known whether eating-disordered behavior in BEDand BN patients is associated with structural brain abnormalities, weconducted the present VBM study. We investigated patients whocurrently suffered from BN and BED and compared themwith healthycontrols. Grey matter volumes (GMV) for specific brain regionsinvolved in food/reinforcement processing (medial/lateral OFC,insula, ACC, ventral/dorsal striatum) were analyzed by means ofvoxel-based morphometry. In addition, GMV was related to self-reports on specific eating disorder features.

Materials and methods

Participants

Women suffering from bulimia nervosa (BN – purge type, n=14),binge-eating disorder (BED, n=17) according to DSM-IV-TR (APA,2000) and normal-weight controls with no previous history of eatingdisorders (CG; n=19) participated in this study. The patientsreported a comparable illness duration (BN: M=7.3 years, SD=3.6,BED: M=6.8 years, SD=4.0; t(29)=0.5, p=.66). All women werenon-medicated and right-handed. None of them suffered fromamenorrhea. Participants had been recruited via announcements inlocal newspapers and at the university campus. Written informedconsent was obtained from each participant before entry. Clinicallyrelevant depression led to exclusion from the study. Those patientsinterested in treatment were assisted with referrals. The study hadbeen approved by the ethics committee of the German Society forPsychology.

Procedure

The participants underwent a standardized clinical interview formental disorders (Margraf et al., 1991), a specific eating disorderinterview (Jacobi et al., 1996), and filled out the Eating DisorderInventory (Diehl and Staufenbiel, 1994). This self-report measureincludes four scales addressing eating disorder relevant behaviors(fear of weight gain, binge-eating, purging, figure dissatisfaction).Typical items are as follows: “I am terribly afraid of gaining weight”; “Iexperience binge-eating episodes, where I cannot stop eating”; “I havethoughts about vomiting in order to lose weight”; “I think my behindis too big.” All subjects were weighed to determine the body massindex (BMI). Then the participants underwent structural andfunctional MRI scanning. The results for the fMRI study have beenreported elsewhere (Schienle et al., 2009).

MRI scanning

High-resolution structural MRI scans (160 sagittal slices,1 × 1×1 mm, FOV: 256 mm, TR=1900 ms, TI=1100 ms,TE=4.18 ms, flip angle=15°) were acquired using a 3D-MPRAGEsequence on a 1.5-T tomograph (Siemens Magnetom Symphony,Siemens, Erlangen, Germany). Data analysis was carried out withSPM5 (Wellcome Department of Imaging Neuroscience, London, UK)and the VBM toolbox (VBM5.1 version 1.19; http://dbm.neuro.uni-jena.de/vbm/vbm5-for-spm5/). Individual structural scans weresegmented using unified segmentation (Ashburner and Friston,2006). A Hidden–Markov random field approach was applied for thesegmentation to avoid misclassification of non-contiguous voxels.Modulated segments were used to assess volume differences. As afinal preprocessing step, segments were smoothed by a Gaussiankernel of 12 mm.

Pairwise t-comparisons (BEDbNCG, BEDbNBN, BNbNCG) werecomputed to assess group differences. In addition, covariations of greymatter volumes with self-report measures (scores on the eatingdisorder inventory) were computed bymeans of multiple regressions.The correlation analyses were restricted to the patient samples. In allanalyses of grey matter segments, total grey matter (sum of valuesfrom entire modulated grey matter segment) was considered acovariate. Exploratory analyses for white matter and cerebrospinalfluid (CSF) used total values for the respective tissue classes.Segments were thresholded before statistical analysis with anabsolute value of 0.15 in all computations.

We computed exploratory whole brain analyses as well as regionof interest (ROI) analyses to test specific GMV hypotheses. The ROIswere created with the WFUPickatlas (version 2.4, Maldjian et al.,2003) based on the parcellation by Tzourio-Mazoyer et al. (2002).Statistical parametric maps were initially thresholded by an uncor-rected p of .005. P valuesb .05 corrected for family-wise error wereconsidered significant for exploratory and ROI analyses. Small-volumecorrection was conducted for ROI analysis for the following masks:insula, medial/lateral orbitofrontal cortex (medOFC; latOFC; orbitalparts of all frontal gyri), as well as ventral/dorsal striatum (vstriatum;dstriatum), and anterior cingulate cortex (ACC).Whitematter and CSFwere analyzed bymeans of exploratory tests as no a priori hypotheseshad been formulated.

Results

Self-report data and BMI

Demographic and clinical characteristics of the three studysamples are displayed in Table 1. The groups differed in mean age(F(2,47)=3.9, p=.025), BMI (F(2,47)=31, pb .001) as well as in allEDI scales (all pb .001). The results of the follow-up Scheffé tests(Table 1) showed that the BED patients were slightly older than thehealthy controls; all other group comparisons were nonsignificant.BED and BN patients did not differ with regard to self-reported binge-eating severity, fear of weight gain, figure dissatisfaction, and age (allpN .10). The bulimic patients reported more purging behavior (vomi-ting) than BED patients and healthy controls (all pb .05). No groupdifferences were present for the duration of education (F(2,48)= 0.7,p=.56).

Group differences

The BN patients had a greater grey matter volume (GMV) of themedial and lateral orbitofrontal cortex as well as of the ventral anddorsal striatum compared to the BED patients (Table 2; Fig. 1).Relative to the healthy control group, bulimic women showedincreased GMV of the medial OFC and the ventral striatum. BEDpatientswere characterized by greater GMV of the ACC and themedial

Table 1Demographic and clinical characteristics of study samples.

BEDM (SD)

BNM (SD)

CGM (SD)

Significant groupdifferences

Age (years) 26.4 (6.4) 23.1 (3.8) 22.3 (2.6) BEDNCGEducation (years) 13.0 (1.5) 12.7 (0.8) 13.2 (0.9) NSBody mass index 32.2 (4.0) 22.1 (2.5) 21.7(1.4) BEDNBN, CGEDI_binge-eating 14.4 (2.0) 15.8 (2.0) 0.79 (1.4) BED, BNNCGEDI_vomiting 3.8 (2.5) 11.8 (2.5) 0.53 (0.9) BNNBEDNCGEDI_figure dissatisfaction 16.0 (3.8) 15.9 (2.7) 7.6 (3.5) BED, BNNCGEDI_fear of weight gain 13.4 (3.2) 15.4 (2.2) 3.4 (3.1) BED, BNNCG

BED: binge-eating disorder; BN: bulimia nervosa; CG: control group; EDI: Eating Disorder Inventory; NS: nonsignificant, significant group differences (Scheffé tests, pb .05).

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OFC than controls. All other ROI comparisons as well as theexploratory analyses were nonsignificant.

Groups were not different with respect to white matter as well asCSF volume.

Correlations of GMV with self-report measures and BMI

The regression analyses for the patient samples indicated that inbulimic women, the GMV of the ventral and dorsal striatum wasnegatively correlated with the BMI (Table 2 and Fig. 2). A marginallysignificant positive correlationwas observed for ventral striatumvolumeand purging behavior. All other correlations were nonsignificant.

Discussion

This is the first VBM study to demonstrate localized GMVabnormalities in patients suffering from binge-eating syndromes.Both eating-disordered groups, BN and BED, were characterized byincreased medial OFC volumes relative to healthy controls. Functionalneuroimaging has provided evidence of altered medial OFC processes

Table 2Group differences in grey matter volume (GMV) and correlations of GMV with bodymass index and purging behavior.

Region Side x y z t pFWE

BEDNCGACC L −2 16 30 4.99 .002ACC R 1 17 28 4.84 .003medOFC R 29 63 −3 3.93 .030

BNNBEDlatOFC L −33 43 −4 4.74 .009medOFC L −17 30 −15 3.78 .050vstriatum R 24 5 0 3.96 .012vstriatum L −26 6 0 3.64 .023dstriatum R 19 12 15 4.31 .008dstriatum L −25 9 3 4.05 .013

BNNCGmedOFC L −11 19 −16 4.06 .025medOFC R 11 22 −12 4.14 .021vstriatum L −11 17 −11 3.76 .016vstriatum R 11 21 −9 3.72 .019

Correlations

BN with purgingvstriatum L −15 7 −11 3.66 .086vstriatum R 19 5 −10 3.78 .078

BN with BMI (neg)dstriatum L −13 12 6 −4.62 .038vstriatum L −19 5 −8 −6.89 .003vstriatum R 21 9 −11 −4.34 .042

BED: binge-eating disorder; BN: bulimia nervosa; CG: control group; med/lat OFC:medial/lateral orbitofrontal cortex; v/dstriatum: ventral/dorsal striatum; neg:negative correlations; BMI: body mass index.All p values were corrected for family-wise error (FWE).

in both patient groups during the presentation of visual food cues(Karhunen et al., 2000; Uher et al., 2004; Schienle et al., 2009). Theelevated OFC reactivity has been interpreted to reflect altered rewardprocessing as this region represents the hedonic value of food stimuli(Kringelbach and Rolls, 2004) and is activated during the experienceand anticipation of pleasant taste (O'Doherty et al., 2002; Small et al.,2001; De Araujo et al., 2001; Kringelbach et al., 2003).

Morphological changes of the reward–learning circuit havealready been identified for other psychopathologies besides eatingdisorders. Individuals suffering from substance dependence (e.g.cocaine, amphetamine) were also characterized by changes in medialOFC grey matter (Franklin et al., 2002; Tanabe et al., 2009). Others,however, related orbitofrontostriatal abnormalities to dysfunctionalself-regulation and habit learning (e.g., Marsh et al., 2009).

A second structure of the brain reward system, the ventralstriatum (nucleus accumbens) was significantly enlarged in bulimicpatients relative to the other groups. Interestingly, this volumeincrease was associated with a lower BMI and a higher score on theeating disorder inventory scale ‘purging’. This means that patientswith larger ventral striatum GMV vomited more frequently and, bythis, executed more efficient weight control. This finding can beinterpreted in the framework of instrumental reward conditioning ornegative reinforcement. BN patients purge to reduce stress andweight (Jacobi et al., 1996). It is known that the ventral striatum isconcerned not onlywith the processing of the hedonic value of stimuliand reward-related environmental cues but also with the facilitationof the acquisition of behaviors related to obtaining a reward (e.g.,Diekhof et al., 2008). Thus, the enhancement of ventral striatumvolume in BN patients may result from their chronic use of certainnegative reinforcement strategies (purging) which are not applied bythe other groups (BED, CG). The combined increase of ventral striatumandmedial OFC volume in BN patients may hint at a joint alteration offood reward processing (OFC) and instrumental behavior to reducenegative effects of food intake such as weight gain (ventral striatum).It is of interest that the identified GMV changes in binge-eatingsyndromes were restricted to specific regions and not distributeddiffusely across the brain. Thus, a functional significance seems likely.

Reward learning has also been associated with the dorsal striatum(e.g., O'Doherty et al., 2002). This region showed greater volumes inBN patients relative to BED patients but did not differentiate betweenthe eating-disordered groups and healthy controls. Therefore, aninterpretation of possible disorder relevance seems to be premature.This statement also applies to the ACC volume enlargement in BEDpatients which could only be detected relative to healthy controls butnot relative to BN patients.

Finally, it has to be noted that we were not able to replicateprevious findings on a negative correlation between the BMI andpostcentral GM in obese individuals (Pannacciulli et al., 2006). Thisdeviating finding might be due to the fact that in the VBM study byPannacciulli et al. (2006) healthy individuals were studied, who hadno current eating disorder. Moreover, VBM findings on obeseindividuals have been inconsistent. Haltia et al. (2007) observedbrain white matter changes in obesity and no alterations in GMV.

Fig. 1. Group differences in grey matter volume. Group comparisons BNNBED (top left). Coronal slices in the top row are showing differences in the medial orbitofrontal cortex (left)as well as the dorsal striatum (right). BEDNCG (top right): Differences between groups in the medial orbitofrontal cortex (medOFC). BNNCG (bottom row) showing ventral striatum(left) and medial OFC (right) differences. All overlays were thresholded at pb .005 (uncorrected).

642 A. Schäfer et al. / NeuroImage 50 (2010) 639–643

Some limitations of the present investigation must be acknowl-edged. We only included female participants. Thus, the findingscannot be generalized to men. Also, the sample size was modest.However, the BN and BED patients were carefully selected to excludeconfounding effects of comorbidity and medication. Moreover, botheating-disordered groups only differed with regard to purgingbehavior, whereas other symptoms (binge-eating, fear of weightgain, figure dissatisfaction) were comparable. Finally, a second controlgroup of obese individuals without binge-eating symptoms shouldhave been included into the design.

Fig. 2. Correlation of grey matter volume of the left ventral striatum with body mass indeximage. Ventral striatum volume (MNI: −19, 5, −8) is residualized with respect to total gr

Despite the fact that we identified GMV abnormalities in brainregions concerned with reward processing and self-regulation, thedisorder specificity of this finding remains unclear. Prefrontal–striataldysfunctions as well as structural changes have been reported forother mental disorders (e.g., depression, substance dependence) asnoted before (Diekhof et al., 2008). Therefore, further studies (e.g.,twin studies) are highly recommended to find out whether specificGMV abnormalities are vulnerability markers for developing an eatingdisorder or whether these abnormalities are a result of the executionof disorder-specific behavior (e.g., purging) and/or an altered

in bulimic patients. Scatterplot (left) and t-map (right) overlaid on single-subject T1ey matter volume (overlay thresholded at pb .005, uncorrected).

643A. Schäfer et al. / NeuroImage 50 (2010) 639–643

nutritional status. There is evidence that individuals with eatingdisorders (particularly anorexia nervosa) show grey andwhite matterchanges as well as changes in CSF that resolve – at least partly - withimproved nutrition (e.g., Katzman et al., 1996; Lambe et al., 1997).Thus, treatment studies on the possible reversibility of structuralabnormalities in binge-eating syndromes are of high interest.

Conflict of interest

The authors have no conflict of interest to declare.

Acknowledgments

This study was supported by a grant from the German ResearchFoundation (Schi 556/5-1).

References

American Psychiatric Association, 2000. Diagnostic and Statistical Manual of MentalDisorders, 4th ed. American Psychiatric Press, Washington, DC.

Ashburner, J., Friston, K., 2006. Unified segmentation. NeuroImage 26, 839–851.De Araujo, I.E.T., Rolls, E.T., Kringelbach, M.L., McGlone, F., Phillips, N., 2003. Taste-

olfactory convergence and representation of pleasantness of flavour in the humanbrain. Eur. J. Neurosci. 18, 2059–2068.

Diehl, J.M., Staufenbiel, T., 1994. Essstörungs-Inventar (Eating Disorder Inventory).Supplement zum IEG. Verlag Dietmar Klotz, Eschborn.

Diekhof, E.K., Falkai, P., Gruber, O., 2008. Functional neuroimaging of reward processingand decision-making: a review of aberrant motivational and affective processing inaddiction and mood disorders. Brain Res. Rev. 59, 164–184.

Franklin, T.R., Acton, P.D., Maldjian, J.A., Gray, J.D., Croft, J.R., Dackis, C.A., O'Brien, C.P.,Childress, A.R., 2002. Decreased grey matter volume in the insular, orbitofrontal,cingulate, and temporal cortices of cocaine patients. Biol. Psychiatry 51, 134–142.

Gray, A., McNaughton, N., 2000. The Neuropsychology of Anxiety: An Enquiry into theFunctions of the Septo-hippocampal System, 2nd ed. Oxford University Press,Oxford.

Haltia, L.T., Viljanen, A., Parkkola, R., Kemppainen, N., Rinne, J.O., Nuutila, P., Kaasinen,V., 2007. Brain white matter expansion in human obesity and the recovering effectof dieting. J. Clin. Endocrinol. Metab. 92, 3278–3284.

Hoffman, G.W., Ellinwood, E.H.J., Rockwell, W.J., Herfkens, R.J., Nishita, J.K., Guthrie, L.F.,1989. Cerebral atrophy in bulimia. Biol. Psychiatry 25, 894–902.

Hudson, J.I., Hiripi, E., Pope, H.G., Kessler, R.C., 2007. The prevalence and correlates ofeating disorders in the national comorbidity survey replication. Biol. Psychiatry 61,348–358.

Jacobi, C., Thiel, A., Paul, Th, 1996. Cognitive Behavior Therapy for Anorexia and BulimiaNervosa. Beltz, Weinheim.

Karhunen, L.J., Vanninen, E.J., Kuikka, J.T., Lappalainen, R.I., Tiihonen, J., Uusitupa, M.J.I.,2000. Regional cerebral blood flow during exposure to food in obese binge eatingwomen. Psychiatry Res. Neuroimaging 99, 29–42.

Katzman, D., Lambe, E., Mikulis, D., Ridgley, J., Goldbloom, D., Zipursky, R., 1996.Cerebral gray matter and white matter volume deficits in adolescent girls withanorexia nervosa. J. Pediatr. 129, 794–803.

Kringelbach, M.L., O'Doherty, J., Rolls, E.T., Andrews, C., 2003. Activation of the humanorbitofrontal cortex to a liquid food stimulus is correlated with its subjectivepleasantness. Cereb. Cortex 13, 1064–1071.

Kringelbach, M.L., Rolls, E.T., 2004. The functional neuroanatomy of the humanorbitofrontal cortex: evidence from neuroimaging and neuropsychology. Prog.Neurobiol. 72, 341–372.

Laessle, R.G., Krieg, J.C., Fichter, M.M., Pirke, K.M., 1989. Cerebral atrophy and vigilanceperformance in patients with anorexia and bulimia nervosa. Neuropsychobiology21, 187–191.

Lambe, E.K., Katzman, D.K., Mikulis, D.J., Kennedy, S.H., Zipursky, RB, 1997. Cerebralgray matter volume deficits after weight recovery from anorexia nervosa. Arch.Gen. Psychiatry 54, 537–542.

Maldjian, J.A., Laurienti, P.J., Burdette, J.B., Kraft, R.A., 2003. An automated method forneuroanatomic and cytoarchitectonic atlas-based interrogation of fMRI data sets.NeuroImage 19, 1233–1239.

Margraf, J., Schneider, S., Ehlers, A. (Eds.), 1991. Diagnostic Interview for MentalDisorders. Springer, Berlin.

Marsh, R., Steinglass, J.E., Gerber, A.J., O'Leary, G., Wang, Z., Murphy, T., Walsh, T.,Peterson, B.S., 2009. Deficient activity in the neural systems that mediate self-regulatory control in bulimia nervosa. Arch. Gen. Psychiatry 66, 51–63.

O'Doherty, J.P., Deichmann, R., Crichley, H.D., Dolan, R.J., 2002. Neural responses duringanticipation of a primary taste reward. Neuron 33, 815–826.

Pannacciulli, N., Del Parigi, A., Chen, K., Le, D.S., Reiman, E.M., Tataranni, P.A., 2006. Brainabnormalities in human obesity: a voxel-based morphometry study. Neuroimage31, 1419–1425.

Schienle, A., Schäfer, A., Hermann, A., Vaitl, D., 2009. Binge-eating disorder: rewardsensitivity and brain activation to images of food. Biol. Psychiatry 65, 654–661.

Small, D.M., Zatorre, R.J., Dagher, A., Evans, A.C., Jones-Gotman, M., 2001. Changes inbrain activity related to eating chocolate: from pleasure to aversion. Brain 124,1720–1733.

Tanabe, J., Tregellas, J.R., Dalwani, M., Thompson, L., Owens, E., Crowley, T., Banich, M.,2009. Medial orbitofrontal cortex gray matter is reduced in abstinent substancedependent individuals. Biol. Psychiatry 65, 1160–1164.

Tzourio-Mazoyer, N., Landeau, B., Papathanassiou, D., Crivello, F., Etard, O., Delcroix, N.,Mazoyer, B., Joliot, M., 2002. Automated anatomical labeling of activations in SPMusing a macroscopic anatomical parcellation of the MNI MRI single-subject brain.NeuroImage 15, 273–289.

Uher, R., Murphy, T., Brammer, M.J., Dalgleish, T., Phillips, M.L., Ng, V., Andrew, C.M.,Williams, S.C.R., Campbell, I.C., Treasure, J., 2004. Medial prefrontal cortex activityassociated with symptom provocation in eating disorders. Am. J. Psychiatry 161,1238–1246.

Wagner, A., Greer, P., Bailer, U.F., Frank, G.K., Henry, S.E., Putnam, K., Meltzer, C.C., Ziolko, S.K., Hoge, J., McConaha, C., Kaye, W.H., 2006. Normal brain tissue volumes after long-term recovery in anorexia and bulimia nervosa. Biol. Psychiatry 59, 291–293.

Whitwel, J.L., Sampson, E.L., Loy, C.T., Warren, J.E., Rossor, M.N., Fox, N.C., Warren, J.D.,2007. VBM signatures of abnormal eating behaviours in frontotemporal lobardegeneration. NeuroImage 35, 207–213.

Woolley, J.D., Gorno-Tempini, M-L., Seeley, W.W., Rankin, K., Lee, S.S., Matthews, B.R.,Miller, B.L., 2007. Binge eating is associated with right orbitofrontal–insular–striatalatrophy in frontotemporal dementia. Neurology 69, 1424–1433.

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