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Behav Brain Res ; 447: 114422, 2023 06 05.
Artigo em Inglês | MEDLINE | ID: mdl-37030546

RESUMO

BACKGROUND: Conduct disorder (CD) has been conceptualized as a psychiatric disorder associated with white-matter (WM) structural abnormalities. Although diffusion tensor imaging could identify WM structural architecture changes, it cannot characterize functional connectivity (FC) within WM. Few studies have focused on disentangling the WM dysfunctions in CD patients by using functional magnetic resonance imaging (fMRI). METHODS: The resting-state fMRI data were first obtained from both adolescent CD and typically developing (TD) controls. A voxel-based clustering analysis was utilized to identify the large-scale WM FC networks. Then, we examined the disrupted WM network features in CD, and further investigated whether these features could predict the impulsive symptoms in CD using support vector regression prediction model. RESULTS: We identified 11 WM functional networks. Compared with TDs, CD patients showed increased FCs between occipital network (ON) and superior temporal network (STN), between orbitofrontal network (OFN) and corona radiate network (CRN), as well as between deep network and CRN. Further, the disrupted FCs between ON and STN and between OFN and CRN were significantly negatively associated with non-planning impulsivity scores in CD. Moreover, the disrupted WM networks could be served as features to predict the motor impulsivity scores in CD. CONCLUSIONS: Our results provided further support on the existence of WM functional networks and could extended our knowledge about the WM functional abnormalities related with emotional and perception processing in CD patients from the view of WM dysfunction.


Assuntos
Transtorno da Conduta , Substância Branca , Humanos , Adolescente , Imagem de Tensor de Difusão/métodos , Transtorno da Conduta/diagnóstico por imagem , Transtorno da Conduta/patologia , Substância Branca/diagnóstico por imagem , Substância Branca/patologia , Imageamento por Ressonância Magnética/métodos , Emoções , Encéfalo
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