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A preliminary study of the topological patterns of the brain structural networks and its relationship with the course in depression / 中华行为医学与脑科学杂志
Chinese Journal of Behavioral Medicine and Brain Science ; (12): 207-210, 2014.
Artigo em Chinês | WPRIM | ID: wpr-447909
ABSTRACT
Objective To investigate the small-worldness and the betweenness centrality of the nodes in the brain structural networks and its relationship with the course and the central role of the brain regions in the transmission of information across the whole brain in depression.Methods The diffusion tensor imaging data were obtained from 27 depression patients and 33 healthy controls.The brain structural networks were constructed using the complex network theory.Results The brain structural networks had small-world properties in both groups.When compared with the healthy,the betweenness centrality of the nodes of the networks in depression significantly decreased in right superior frontal gyms (orbital part) (P=0.00035,region survived critical FDR threshold for multiple comparisons),and left putamen (P=0.00054,region survived critical FDR threshold for multiple comparisons).Significant negative correlation was found between the betweenness centrality of left hippocampus and the course in the depression(r=0.50,P=0.016).Conclusion Both of the brain structural networks in depression patients and normal people have the property of small-worldness.But the central role of orbit frontal cortex and putamen in the transmission of information across the whole brain is declined,and the betweenness centrality of hippocampus is negatively related with the course in the depression.

Texto completo: DisponíveL Índice: WPRIM (Pacífico Ocidental) Idioma: Chinês Revista: Chinese Journal of Behavioral Medicine and Brain Science Ano de publicação: 2014 Tipo de documento: Artigo

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Texto completo: DisponíveL Índice: WPRIM (Pacífico Ocidental) Idioma: Chinês Revista: Chinese Journal of Behavioral Medicine and Brain Science Ano de publicação: 2014 Tipo de documento: Artigo