Literature DB >> 33064332

Dynamic neural circuit disruptions associated with antisocial behaviors.

Weixiong Jiang1,2, Han Zhang1, Ling-Li Zeng3, Hui Shen3, Jian Qin3, Kim-Han Thung1, Pew-Thian Yap1, Huasheng Liu4, Dewen Hu3, Wei Wang4, Dinggang Shen1,5.   

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.
© 2020 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.

Entities:  

Keywords:  antisocial behavior; brain network; cognitive control function; default mode network; dynamic functional connectivity; functional MRI; resting state

Mesh:

Year:  2020        PMID: 33064332      PMCID: PMC7776000          DOI: 10.1002/hbm.25225

Source DB:  PubMed          Journal:  Hum Brain Mapp        ISSN: 1065-9471            Impact factor:   5.399


  100 in total

1.  Efficacy of different dynamic functional connectivity methods to capture cognitively relevant information.

Authors:  Hua Xie; Charles Y Zheng; Daniel A Handwerker; Peter A Bandettini; Vince D Calhoun; Sunanda Mitra; Javier Gonzalez-Castillo
Journal:  Neuroimage       Date:  2018-12-18       Impact factor: 6.556

2.  Influence of epoch length on measurement of dynamic functional connectivity in wakefulness and behavioural validation in sleep.

Authors:  Rebecca S Wilson; Stephen D Mayhew; David T Rollings; Aimee Goldstone; Izabela Przezdzik; Theodoros N Arvanitis; Andrew P Bagshaw
Journal:  Neuroimage       Date:  2015-03-10       Impact factor: 6.556

3.  A rating instrument for anxiety disorders.

Authors:  W W Zung
Journal:  Psychosomatics       Date:  1971 Nov-Dec       Impact factor: 2.386

4.  Regional cortical thinning in subjects with violent antisocial personality disorder or schizophrenia.

Authors:  Veena M Narayan; Katherine L Narr; Veena Kumari; Roger P Woods; Paul M Thompson; Arthur W Toga; Tonmoy Sharma
Journal:  Am J Psychiatry       Date:  2007-09       Impact factor: 18.112

5.  Dynamic functional connectivity of the default mode network tracks daydreaming.

Authors:  Aaron Kucyi; Karen D Davis
Journal:  Neuroimage       Date:  2014-06-25       Impact factor: 6.556

6.  Compensation through Functional Hyperconnectivity: A Longitudinal Connectome Assessment of Mild Traumatic Brain Injury.

Authors:  Armin Iraji; Hanbo Chen; Natalie Wiseman; Robert D Welch; Brian J O'Neil; E Mark Haacke; Tianming Liu; Zhifeng Kou
Journal:  Neural Plast       Date:  2015-12-27       Impact factor: 3.599

7.  Multi-Site Diagnostic Classification of Schizophrenia Using Discriminant Deep Learning with Functional Connectivity MRI.

Authors:  Ling-Li Zeng; Huaning Wang; Panpan Hu; Bo Yang; Weidan Pu; Hui Shen; Xingui Chen; Zhening Liu; Hong Yin; Qingrong Tan; Kai Wang; Dewen Hu
Journal:  EBioMedicine       Date:  2018-03-23       Impact factor: 8.143

8.  A toolbox for brain network construction and classification (BrainNetClass).

Authors:  Zhen Zhou; Xiaobo Chen; Yu Zhang; Dan Hu; Lishan Qiao; Renping Yu; Pew-Thian Yap; Gang Pan; Han Zhang; Dinggang Shen
Journal:  Hum Brain Mapp       Date:  2020-03-12       Impact factor: 5.038

9.  Assigning Clinical Significance and Symptom Severity Using the Zung Scales: Levels of Misclassification Arising from Confusion between Index and Raw Scores.

Authors:  Debra A Dunstan; Ned Scott
Journal:  Depress Res Treat       Date:  2018-01-21

10.  Dynamic neural circuit disruptions associated with antisocial behaviors.

Authors:  Weixiong Jiang; Han Zhang; Ling-Li Zeng; Hui Shen; Jian Qin; Kim-Han Thung; Pew-Thian Yap; Huasheng Liu; Dewen Hu; Wei Wang; Dinggang Shen
Journal:  Hum Brain Mapp       Date:  2020-10-16       Impact factor: 5.399

View more
  2 in total

1.  Neural alterations in opioid-exposed infants revealed by edge-centric brain functional networks.

Authors:  Weixiong Jiang; Stephanie L Merhar; Zhuohao Zeng; Ziliang Zhu; Weiyan Yin; Zhen Zhou; Li Wang; Lili He; Jennifer Vannest; Weili Lin
Journal:  Brain Commun       Date:  2022-05-05

2.  Dynamic neural circuit disruptions associated with antisocial behaviors.

Authors:  Weixiong Jiang; Han Zhang; Ling-Li Zeng; Hui Shen; Jian Qin; Kim-Han Thung; Pew-Thian Yap; Huasheng Liu; Dewen Hu; Wei Wang; Dinggang Shen
Journal:  Hum Brain Mapp       Date:  2020-10-16       Impact factor: 5.399

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.