Structure and dynamics of functional networks in child-onset schizophrenia

Autor(es)

de Arruda, Guilherme Ferraz ^[1] ; Costa, Luciano da Fontoura ^[2] ; Schubert, Dirk ^[3] ; Rodrigues, Francisco A. ^[1]

Afiliação do(s) autor(es)

^[1] Univ Sao Paulo, Inst Ciencias Matemat & Computacao, Dept Matemat Aplicada & Estat, BR-13566590 Sao Carlos, SP - Brazil

^[2] Univ Sao Paulo, Inst Fis Sao Carlos, BR-13560970 Sao Carlos, SP - Brazil

^[3] Radboud Univ Nijmegen, Med Ctr, Donders Inst Brain Cognit & Behav, Dept Cognit Neurosci, NL-6500 HB Nijmegen - Netherlands

• Tipo de documento: Artigo Científico
• Fonte: CLINICAL NEUROPHYSIOLOGY; v. 125, n. 8, p. 1589-1595, AUG 2014.
• Citações Web of Science: 4

Resumo

Objective: Schizophrenia is a neuropsychiatric disorder characterized by cognitive and emotional deficits and associated with various abnormalities in the organization of neural circuits. It is currently unclear how and to which extend the global network organization is changed due to such disorder. In this work, we analyzed cortical networks of healthy subjects and patients with child-onset schizophrenia to address this issue. Methods: We performed a comparison of cortical networks extracted from functional MRI data of patients with schizophrenia and healthy subjects considering their topological and dynamical properties. Results: Among 54 network measures tested, only four contributed substantially to a discrimination between the classes of healthy and schizophrenic subjects, with a sensitivity of 90% and specificity of 74%. However, such classes of networks did not differ significantly with respect to the level of network resilience and synchronization. Conclusions: Schizophrenic subjects have cortical regions with higher variance of network centrality, but less modular structure. Significance: Our findings suggest that it is possible to establish data analysis routines that allow automatic diagnosis of a multifaceted disease like child-onset schizophrenia based on fMRI data of individual subjects and extracted network properties. (C) 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved. (AU)

• Processo FAPESP: 10/19440-2 - Caracterização, análise, simulação e classificação de redes complexas
• Beneficiário: Francisco Aparecido Rodrigues
• Modalidade de apoio: Auxílio à Pesquisa - Regular
• Processo FAPESP: 11/50761-2 - Modelos e métodos de e-Science para ciências da vida e agrárias
• Beneficiário: Roberto Marcondes Cesar Junior
• Modalidade de apoio: Auxílio à Pesquisa - Temático