Title
Fiber connectivity between the striatum and cortical and subcortical regions is associated with temperaments in Chinese males.
Abstract
The seven-factor biopsychosocial model of personality distinguished four biologically based temperaments and three psychosocially based characters. Previous studies have suggested that the four temperaments—novelty seeking (NS), reward dependence (RD), harm avoidance (HA), and persistence (P)—have their respective neurobiological correlates, especially in the striatum-connected subcortical and cortical networks. However, few studies have investigated their neurobiological basis in the form of fiber connectivity between brain regions. This study correlated temperaments with fiber connectivity between the striatum and subcortical and cortical hub regions in a sample of 50 Chinese adult males. Generally consistent with our hypotheses, results showed that: (1) NS was positively correlated with fiber connectivity from the medial and lateral orbitofrontal cortex (mOFC, lOFC) and amygdala to the striatum; (2) RD was positively correlated with fiber connectivity from the mOFC, posterior cingulate cortex/retrosplenial cortex (PCC), hippocampus, and amygdala to the striatum; (3) HA was positively linked to fiber connectivity from the dorsolateral prefrontal cortex (dlPFC) and PCC to the striatum; and (4) P was positively linked to fiber connectivity from the mOFC to the striatum. These results extended the research on the neurobiological basis of temperaments by identifying their anatomical fiber connectivity correlates within the subcortical–cortical neural networks.
Year
DOI
Venue
2014
10.1016/j.neuroimage.2013.04.043
NeuroImage
Keywords
DocType
Volume
NS,RD,P,HA,TCI,DTI,mOFC,lOFC,lPFC,dlPFC,PCC,dACC,ACC
Journal
89
Issue
ISSN
Citations 
null
1053-8119
3
PageRank 
References 
Authors
0.49
17
16
Name
Order
Citations
PageRank
Xuemei Lei151.61
Chuansheng Chen210114.56
Feng Xue3202.13
Qinghua He4194.19
Chunhui Chen5354.43
Qi Liu630.49
Robert K Moyzis751.61
Gui Xue814417.46
Zhongyu Cao950.93
Jin Li1051.27
He Li1141.84
Bi Zhu1250.93
Yuyun Liu1330.82
Anna Shan Chun Hsu1430.49
Jun Li1530.49
Qi Dong1610913.74