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Activity in parahippocampal gyrus during cognitive tasks correlates with tendency to ruminate C.Piguet1, M. Desseilles1, 2Y. Cojan1,V. Sterpenich1, A. Dayer, J.-M. Aubry, G. Bertschy3, P. Vuilleumier1 1Department of Neuroscience, Faculty of Medicine, University of Geneva, Switzerland of Psychiatry, University Hospital of Geneva, Switzerland 3Department of Psychiatry and Mental Health, Strasbourg University Hospital, University of Strasbourg, INSERMu666, France 2Department Background & Aim Material & Methods Subjects: 32 mood disorder patients (MDD (N=9), BD-I (N=7), BD-II (N=13) or BD-others (N=3)), 31 matched controls Rumination is frequently encountered in mood disorders, and is associated with poorer clinical outcome. Ruminative thinking has been proposed to originate from abnormalities in cognitive processes such as associative thinking or mental flexibility (1–3). Moreover, rumination might be a relevant dimensional trait which encompass mood and anxiety disorders (4). Here we used a trait measure of rumination, the Ruminative Response Scale (RRS), and in particular its brooding subscore, representing the most negative aspect of rumination, to investigate the neural correlates of this dimension during specific cognitive tasks in both healthy and mood disorders participants. TASK: Free Word Association • Condition “close”: 2 words that first come to your mind, production process • Condition “remote”: 2 words as far as possible, inhibition of automatisms • Stimuli: positive, negative and neutral words with 40-60% association in French language TASK: Task Switching < N (males) p value 40.25 (8.8) 39.6 (8.7) 13.3 (3.2) 14 (3) 23 (9) 24 (7) 13.75(9.3) 2 (1.8) * < 0.001 Young 2.4 (2.9) 0.4 (0.8) * < 0.001 Hamilton Anxiety 13.2 (8.2) 3.3 (2.3) * < 0.001 RRS 55.2 (11) 33.8 (9.9) * < 0.001 Brooding 12.5 (3.1) MADRS • Condition “inhibition”: ABA sequence compared to CBA sequence < 10 60 10 + 20650 ms SPM{T57} 30 3 tasks: emotion – gender- color 40 «which face is different of the others regarding the cue?» 50 Height threshold T = 3.239478 {p<0.001 (unc.)} 60 Extent threshold k = 0 voxels fMRI 1 Results 2 3 1 4 2 Design matrix Brooding@sF2 1 Brooding@sF2 2 Group 1 Group emotion 150 ms 50 Extent threshold k = 0 voxels Statistical analysis: Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 3 4 Design matrix Association > control task, Inhibition > control task, positive correlation for all subjects positive correlation for all subjects x,y,z = -24 -4 -32 MNI p<0.001 unc. Z score 3.28 x,y,z = -15 -13 -20 MNI p<0.001 unc. Z score 3.4 4 parameters (gray not uniquely specified) parameter estimability 3 Discussion & Conclusion Design description... Design : Global calculation : Grand mean scaling : Global normalisation : Parameters : < 3T whole-body MAGNETOM Trio Tim VB15 system (Siemens GmbH), 32 channel head coil. 20 images: 3D T1 weighted sequence, 1 mm SPM{T•structural } 59 isotropic voxels 30 •functional images: EPI sequence, sparse sampling (TR = 9 s or 2.04 s, 3x3 mm resolution, 36 axial slices, 40 thickness 3 mm) •Data analysis: SPM8, SPSS SPMresults: .\inhib_control Height threshold T = 2.661759 {p<0.005 (unc.)} images < < SPMresults: .\assoc_control 8.1 (2.4) * < 0.001 1200 ms • Stimuli: happy, sad and neutral faces, colored in red or green. MRI data acquisition: < emotion 10 independant t-test 31 (14) Level of education Laterality (not righthanded) contrast(s) contrast(s) 32 (14) Age 650 ms SPMmip [-15, -13, -20] M (SD) + (emotion-emotion) 10 M (SD) SPMmip [-24, -4, -32] Characteristics Controls Brooding_ALL • Condition “switch”: AAB sequence, for example Brooding_ALL emotion-color, compare to repetition BBB Demographic Data Patients X=9 Two-sample t-test omit <no grand Mean scaling> <no global normalisation> 2 condition, +2 covariate, +0 block, +0 nuisance 4 total, having 4 degrees of freedom leaving 59 degrees of freedom from 63 images 2 Two different fMRI tasks, cognitive conditions with high attentional load 1 Activity in the parahippocampal gyrus correlated with brooding tendency across all subjects. 0 selective activity fits well with The effect was small despite the relatively large sample, but this our previous work conducted with a different sample (5) Fits with the model of reduced control on overactivation of self-related and autobiographical memory regions that may contribute to rumination. The fact that this correlation is significant for a mixed sample of healthy and clinical participants does not support a specific involvement of rumination in mood disorders, but rather suggests that rumination is a physiological process that might become pathological under specific circumstances such as diminished cognitive control. No disclosure of interest [email protected] 3 References 1. Bar M (2009) Trends2Cogn Sci. 13: 456–63. 2. Gotlib IH, Joormann J (2010) Annu Rev Clin Psychol. 6: 1 285–312. 3. Koster EH et al. (2011) Clin Psychol Rev. 31: 138–45. 0 4. Nolen-Hoeksema S, Watkins ER (2011) Perspect Psychol Sci. 6: 589–609. 5. Piguet C et al. (2014). Biol Psychol. 103: 195–202.