In the last years, there has been a considerable increase of research into the neuroimaging correlates of inter-individual temperament and character variability-an endeavour for which the term 'personality neuroscience' was coined. Among other neuroimaging modalities and approaches, substantial work focuses on functional connectivity in resting state (rs-FC) functional magnetic resonance imaging data. In the current paper, we set out to independently query the questions asked in a highly cited study that reported a range of functional connectivity correlates of personality dimensions assessed by the widely used 'Big Five' Personality Inventory. Using a larger sample (84 subjects) and an equivalent data analysis pipeline, we obtained widely disagreeing results compared to the original study. Overall, the results were in line with the hypotheses of no relation between functional connectivity and personality, when more precise permutation-based multiple testing procedures were applied. The results demonstrate that as with other neuroimaging studies, great caution should be applied when interpreting the findings, among other reasons due to multiple testing problem involved at several levels in many neuroimaging studies. Of course, the current study results can not ultimately disprove the existence of some link between personality and brain's intrinsic functional architecture, but clearly shows that its form is very likely different and much more subtle and elusive than was previously reported.

3rd Faculty of Medicine Charles University Prague Czech Republic

Department of Radiology Institute for Clinical and Experimental Medicine Prague Czech Republic

Faculty of Electrical Engineering Czech Technical University Prague Prague Czech Republic

Institute of Computer Science Czech Academy of Sciences Prague Czech Republic

Institute of Psychology Czech Academy of Sciences Prague Czech Republic

National Institute of Mental Health Klecany Czech Republic

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Typicality of functional connectivity robustly captures motion artifacts in rs-fMRI across datasets, atlases, and preprocessing pipelines