TY - JOUR
T1 - The divided brain
T2 - Functional brain asymmetry underlying self-construal
AU - Shi, Gen
AU - Li, Xuesong
AU - Zhu, Yifan
AU - Shang, Ruihong
AU - Sun, Yang
AU - Guo, Hua
AU - Sui, Jie
N1 - Publisher Copyright:
© 2021
PY - 2021/10/15
Y1 - 2021/10/15
N2 - Self-construal (orientations of independence and interdependence) is a fundamental concept that guides human behaviour, and it is linked to a large number of brain regions. However, understanding the connectivity of these regions and the critical principles underlying these self-functions are lacking. Because brain activity linked to self-related processes are intrinsic, the resting-state method has received substantial attention. Here, we focused on resting-state functional connectivity matrices based on brain asymmetry as indexed by the differential partition of the connectivity located in mirrored positions of the two hemispheres, hemispheric specialization measured using the intra-hemispheric (left or right) connectivity, brain communication via inter-hemispheric interactions, and global connectivity as the sum of the two intra-hemispheric connectivity. Combining machine learning techniques with hypothesis-driven network mapping approaches, we demonstrated that orientations of independence and interdependence were best predicted by the asymmetric matrix compared to brain communication, hemispheric specialization, and global connectivity matrices. The network results revealed that there were distinct asymmetric connections between the default mode network, the salience network and the executive control network which characterise independence and interdependence. These analyses shed light on the importance of brain asymmetry in understanding how complex self-functions are optimally represented in the brain networks.
AB - Self-construal (orientations of independence and interdependence) is a fundamental concept that guides human behaviour, and it is linked to a large number of brain regions. However, understanding the connectivity of these regions and the critical principles underlying these self-functions are lacking. Because brain activity linked to self-related processes are intrinsic, the resting-state method has received substantial attention. Here, we focused on resting-state functional connectivity matrices based on brain asymmetry as indexed by the differential partition of the connectivity located in mirrored positions of the two hemispheres, hemispheric specialization measured using the intra-hemispheric (left or right) connectivity, brain communication via inter-hemispheric interactions, and global connectivity as the sum of the two intra-hemispheric connectivity. Combining machine learning techniques with hypothesis-driven network mapping approaches, we demonstrated that orientations of independence and interdependence were best predicted by the asymmetric matrix compared to brain communication, hemispheric specialization, and global connectivity matrices. The network results revealed that there were distinct asymmetric connections between the default mode network, the salience network and the executive control network which characterise independence and interdependence. These analyses shed light on the importance of brain asymmetry in understanding how complex self-functions are optimally represented in the brain networks.
KW - Brain asymmetry
KW - Hemispheric specialisation
KW - Resting state functional connectivity (rsFC)
KW - Self-construal
UR - http://www.scopus.com/inward/record.url?scp=85110486515&partnerID=8YFLogxK
U2 - 10.1016/j.neuroimage.2021.118382
DO - 10.1016/j.neuroimage.2021.118382
M3 - Article
C2 - 34252524
AN - SCOPUS:85110486515
SN - 1053-8119
VL - 240
JO - NeuroImage
JF - NeuroImage
M1 - 118382
ER -