FMRI based resting state networks challenged as predictors of stress coping styles and personality traits in healthy volunteers

• Published in: Pharmacopsychiatry
• Main Authors: Höhn, D, Spoormaker, VI, Czisch, M, Sämann, PG
• Format: Conference Proceeding
• Language: English
• Published: 01.09.2009
• ISSN: 0176-3679; 1439-0795
• DOI: 10.1055/s-0029-1240135

There is growing interest in the neurobiological underpinnings of personality, as personality traits such as neuroticism constitute risk factors for the development of psychiatric disorders, particularly depressive disorders and anxiety disorders (Watson 1997, Steunenberg et al. 2009). So far, mainly structural brain features and functional brain responses to defined emotional stimuli have been demonstrated to relate to personal traits (Canli et al 2001) – in the resting state, mainly PET and SPECT were employed so far to delineate specific neural circuits and regions that relate to personality dimension such as neuroticism (Kim et al 2008). Generally, fMRI constitutes a more widely available and less invasive method for resting state analysis that allows for an in-depth-characteriziation of multiple resting state networks (RSNs) including the default mode network. We present associations between individual stress coping styles (Response Styles Questionnaire), personality traits openness, extraversion, neuroticism, agreeableness and conscientiousness (Big-Five-Inventory), and total strength measures of about 14 established RSNs as wells as their multiregion-autocorrelation maps. Data were acquired from 45 healthy volunteers during 6 minute eyes-closed-wakeful-resting scans (1.5 Tesla, wholehead EPI). Data analysis is conducted using SPM5 and the FSL-MELODIC toolkit to identify the RSNs, and in-house software to extract amplitude measures and autocorrelation maps.