TY  - JOUR
AU  - Nostro, Alessandra D.
AU  - Müller, Veronika
AU  - Varikuti, Deepthi
AU  - Pläschke, Rachel
AU  - Hoffstaedter, Felix
AU  - Langner, Robert
AU  - Patil, Kaustubh
AU  - Eickhoff, Simon
TI  - Predicting personality from network-based resting-state functional connectivity
JO  - Brain structure & function
VL  - 223
IS  - 6
SN  - 1863-2661
CY  - Berlin
PB  - Springer
M1  - FZJ-2018-02562
SP  - 2699–2719
PY  - 2018
AB  - Personality is associated with variation in all kinds of mental faculties, including affective, social, executive, and memory functioning. The intrinsic dynamics of neural networks underlying these mental functions are reflected in their functional connectivity at rest (RSFC). We, therefore, aimed to probe whether connectivity in functional networks allows predicting individual scores of the five-factor personality model and potential gender differences thereof. We assessed nine meta-analytically derived functional networks, representing social, affective, executive, and mnemonic systems. RSFC of all networks was computed in a sample of 210 males and 210 well-matched females and in a replication sample of 155 males and 155 females. Personality scores were predicted using relevance vector machine in both samples. Cross-validation prediction accuracy was defined as the correlation between true and predicted scores. RSFC within networks representing social, affective, mnemonic, and executive systems significantly predicted self-reported levels of Extraversion, Neuroticism, Agreeableness, and Openness. RSFC patterns of most networks, however, predicted personality traits only either in males or in females. Personality traits can be predicted by patterns of RSFC in specific functional brain networks, providing new insights into the neurobiology of personality. However, as most associations were gender-specific, RSFC–personality relations should not be considered independently of gender.
LB  - PUB:(DE-HGF)16
C6  - pmid:29572625
UR  - <Go to ISI:>//WOS:000434980400013
DO  - DOI:10.1007/s00429-018-1651-z
UR  - https://juser.fz-juelich.de/record/845281
ER  -