Poster No:
829
Submission Type:
Abstract Submission
Authors:
Weixiong Jiang1, Shuaiqi Li1, Hong Wu2, Lin Li1, Yulong Xia1, Shoujun Huang1, Feng Gao3, Jing Yuan1, Xiaoping Ouyang4
Institutions:
1College of Mathematical Medicine, Zhejiang Normal University, Jinhua, Zhejiang, 2School of Marxism, Hunan First Normal University, Changsha, Hunan, 3School of Electronic Information, Hunan First Normal University, Changsha, Hunan, 4State Key Laboratory of Fluid Power & Mechatronic Systems, Zhejiang University, Hangzhou, Zhejiang
First Author:
Weixiong Jiang
College of Mathematical Medicine, Zhejiang Normal University
Jinhua, Zhejiang
Co-Author(s):
Shuaiqi Li
College of Mathematical Medicine, Zhejiang Normal University
Jinhua, Zhejiang
Hong Wu
School of Marxism, Hunan First Normal University
Changsha, Hunan
Lin Li
College of Mathematical Medicine, Zhejiang Normal University
Jinhua, Zhejiang
Yulong Xia
College of Mathematical Medicine, Zhejiang Normal University
Jinhua, Zhejiang
Shoujun Huang
College of Mathematical Medicine, Zhejiang Normal University
Jinhua, Zhejiang
Feng Gao
School of Electronic Information, Hunan First Normal University
Changsha, Hunan
Jing Yuan
College of Mathematical Medicine, Zhejiang Normal University
Jinhua, Zhejiang
Xiaoping Ouyang
State Key Laboratory of Fluid Power & Mechatronic Systems, Zhejiang University
Hangzhou, Zhejiang
Introduction:
The public health concern surrounding antisocial behavior (ASB) is profound, due to its extensive impact on society (Romeo 2006). Previous research has established a relationship between ASB and abnormalities in brain regions and functional connectivity (Jiang 2021; Mackey 2017), but detailed analyses of brain interaction remain scarce. Recent advancements have focused on nuanced constituents of brain activity, such as the decomposition of brain region interactions into synergistic and redundant components (Mediano 2021). This differentiation has revealed that synergistic interactions are prevalent in higher-order networks, while redundant interactions in sensorimotor ones (Luppi 2022). Our study aims to investigate the distinctions of these information components between individuals with ASB and those without, thus enhancing our understanding of ASB-associated brain dynamics.
Methods:
We recruited 49 volunteers (22.38 ± 3.25) from the School for Youth Offenders of Hunan Province, including 33 ASB subjects and 16 normal controls (NC). Resting-state fMRI data were preprocessed and parcellated into 268 regions of interest. Using the novel Integrated Information Decomposition (ΦID) method, we dissected brain interactions between each pair of brain regions into 16 distinct interactive elements (Mediano 2021), focusing on redundant (information that overlaps in two regions) and synergistic information (information that emerges when both regions are considered together, not by either region alone) (Luppi 2022). We constructed two connection matrices per subject: one for synergistic interaction and the other for redundant interaction. To investigate the characteristics of each component, we assessed ASB-related alterations in these interactions at both regional and network levels. Additionally, we complemented the analysis with network regional measures, including the betweenness centrality to assess the significance of a region and the clustering coefficient to gauge the tendency of nodes to cluster together (Rubinov 2010).
Results:
ASB subjects showed significant reductions in synergistic interactions, particularly in the left ventral and inferior frontal areas, right superior frontal regions, bilateral temporal, right parietal including precuneus areas, bilateral subcortical (insula, cingulum, and hippocampus), and occipital visual regions (Fig. 1A). In particular, the visual association network showed significant decreases (P=0.0126), a trend that was consistent across other networks (Fig. 1B). Redundant interactions also predominantly decreased in ASB subjects, particularly in the bilateral inferior temporal to temporal pole, bilateral inferior prefrontal areas, left middle cingulum, insula, and inferior parietal areas (Fig. 1C). While subnetwork analysis did not show significant differences, a generalized decline in redundant interactions was detected (Fig. 1D). Network metrics indicated altered patterns in both synergistic (Fig. 2A, B) and redundant (Fig. 2C, D) interactions in ASB individuals, characterized by a predominance of decreased betweenness centrality in synergistic interactions and clustering coefficient in redundant interactions. Conversely, the clustering coefficient in synergistic interactions and the betweenness centrality in redundant interactions showed variable changes across different brain regions.


Conclusions:
Our findings revealed significant reductions in both synergistic and redundant interactions in ASB subjects, suggesting impairments in functional brain connectivity. The pronounced decrease in synergy within the visual association network indicates potential disruptions in higher-order visual processing capabilities in individuals with ASB. Changes in network metrics further underscore the altered interaction patterns, signifying the intricate nature of the neural mechanisms involved in ASB. These insights offer a novel perspective into the neural underpinnings of ASB through the lens of synergistic and redundant brain interactions.
Disorders of the Nervous System:
Psychiatric (eg. Depression, Anxiety, Schizophrenia) 2
Emotion, Motivation and Social Neuroscience:
Social Neuroscience Other 1
Keywords:
Other - Antisocial behavior; synergistic interaction; redundant interaction; network metrics; brain dynamics
1|2Indicates the priority used for review
Provide references using author date format
Jiang, W. (2021), ‘Dynamic neural circuit disruptions associated with antisocial behaviors’, Human Brain Mapping, vol. 42, no. 2, pp.329-344.
Luppi, A.I. (2022), ‘A synergistic core for human brain evolution and cognition’, Nat Neurosci, vol. 25, no. 6, pp. 771-782.
Mackey, S. (2017), ‘Brain Regions Related to Impulsivity Mediate the Effects of Early Adversity on Antisocial Behavior’, Biol Psychiatry, vol. 82, no. 4, pp.275-282.
Mediano, P.A. (2021), ‘Towards an extended taxonomy of information dynamics via Integrated Information Decomposition’, arXiv preprint arXiv:2109.13186.
Piras, I.S. (2023), ‘A preliminary transcriptomic analysis of the orbitofrontal cortex of antisocial individuals’, CNS Neuroscience & Therapeutics.
Romeo, R. (2006), ‘Economic cost of severe antisocial behaviour in children-and who pays it’, BJPsych, vol. 188, no. 6, pp.547-553.
Rubinov, M.(2010), ‘Complex network measures of brain connectivity: uses and interpretations’, Neuroimage, vol. 52, no. 3, pp.1059-1069.