Disrupted local beta band networks in schizophrenia revealed through graph analysis: A magnetoencephalography study
Disrupted local beta band networks in schizophrenia revealed through graph analysis: A magnetoencephalography study
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DOI：
10.1111/pcn.13362
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发表时间：
2022-04
影响因子：
11.9
通讯作者：
Minami Tagawa;Y. Takei;Yutaka Kato;Tomohiro Suto;N. Hironaga;Takefumi Ohki;Yumiko Takahashi;K. Fujih
中科院分区：
文献类型：
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作者：
Minami Tagawa;Y. Takei;Yutaka Kato;Tomohiro Suto;N. Hironaga;Takefumi Ohki;Yumiko Takahashi;K. Fujih
精神分裂症(SZ)以精神症状和认知障碍为特征，被认为是一种由于神经网络形成异常而导致的连接障碍综合征。虽然许多研究已经帮助阐明了SZ的病理生理学，但精神症状背后的许多方面的机制仍然不清楚。本研究运用图论分析方法，从微观指标和宏观指标两个方面对静息状态网络(RSN)的特征进行了评价，确定了SZ潜在的生物标志物候选。具体地说，我们区分了频域的拓扑特征，并结合SZ患者的精神症状对其进行了研究。
Schizophrenia (SZ) is characterized by psychotic symptoms and cognitive impairment, and is hypothesized to be a ‘dysconnection’ syndrome due to abnormal neural network formation. Although numerous studies have helped elucidate the pathophysiology of SZ, many aspects of the mechanism underlying psychotic symptoms remain unknown. This study used graph theory analysis to evaluate the characteristics of the resting‐state network (RSN) in terms of microscale and macroscale indices, and to identify candidates as potential biomarkers of SZ. Specifically, we discriminated topological characteristics in the frequency domain and investigated them in the context of psychotic symptoms in patients with SZ.