Dynamic neural circuit disruptions associated with antisocial behaviors
- Authors
- Jiang, Weixiong; Zhang, Han; Zeng, Ling-Li; Shen, Hui; Qin, Jian; Thung, Kim-Han; Yap, Pew-Thian; Liu, Huasheng; Hu, Dewen; Wang, Wei; Shen, Dinggang
- Issue Date
- 1-2월-2021
- Publisher
- WILEY
- Keywords
- antisocial behavior; brain network; cognitive control function; default mode network; dynamic functional connectivity; functional MRI; resting state
- Citation
- HUMAN BRAIN MAPPING, v.42, no.2, pp.329 - 344
- Indexed
- SCIE
SCOPUS
- Journal Title
- HUMAN BRAIN MAPPING
- Volume
- 42
- Number
- 2
- Start Page
- 329
- End Page
- 344
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/49619
- DOI
- 10.1002/hbm.25225
- ISSN
- 1065-9471
- Abstract
- Antisocial behavior (ASB) is believed to have neural substrates; however, the association between ASB and functional brain networks remains unclear. The temporal variability of the functional connectivity (or dynamic FC) derived from resting-state functional MRI has been suggested as a useful metric for studying abnormal behaviors including ASB. This is the first study using low-frequency fluctuations of the dynamic FC to unravel potential system-level neural correlates with ASB. Specifically, we individually associated the dynamic FC patterns with the ASB scores (measured by Antisocial Process Screening Device) of the male offenders (age: 23.29 +/- 3.36 years) based on machine learning. Results showed that the dynamic FCs were associated with individual ASB scores. Moreover, we found that it was mainly the inter-network dynamic FCs that were negatively associated with the ASB severity. Three major high-order cognitive functional networks and the sensorimotor network were found to be more associated with ASB. We further found that impaired behavior in the ASB subjects was mainly associated with decreased FC dynamics in these networks, which may explain why ASB subjects usually have impaired executive control and emotional processing functions. Our study shows that temporal variation of the FC could be a promising tool for ASB assessment, treatment, and prevention.
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Collections - Graduate School > Department of Artificial Intelligence > 1. Journal Articles
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