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精神分裂症静息态网络γ活动增加的细胞和回路模型。

Cellular and circuit models of increased resting-state network gamma activity in schizophrenia.

作者信息

White R S, Siegel S J

机构信息

Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, United States.

Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, United States.

出版信息

Neuroscience. 2016 May 3;321:66-76. doi: 10.1016/j.neuroscience.2015.11.011. Epub 2015 Nov 11.

Abstract

Schizophrenia (SCZ) is a disorder characterized by positive symptoms (hallucinations, delusions), negative symptoms (blunted affect, alogia, reduced sociability, and anhedonia), as well as persistent cognitive deficits (memory, concentration, and learning). While the biology underlying subjective experiences is difficult to study, abnormalities in electroencephalographic (EEG) measures offer a means to dissect potential circuit and cellular changes in brain function. EEG is indispensable for studying cerebral information processing due to the introduction of techniques for the decomposition of event-related activity into its frequency components. Specifically, brain activity in the gamma frequency range (30-80Hz) is thought to underlie cognitive function and may be used as an endophenotype to aid in diagnosis and treatment of SCZ. In this review we address evidence indicating that there is increased resting-state gamma power in SCZ. We address how modeling this aspect of the illness in animals may help treatment development as well as providing insights into the etiology of SCZ.

摘要

精神分裂症(SCZ)是一种以阳性症状(幻觉、妄想)、阴性症状(情感迟钝、言语减少、社交能力下降和快感缺失)以及持续性认知缺陷(记忆、注意力和学习能力)为特征的疾病。虽然主观体验背后的生物学机制难以研究,但脑电图(EEG)测量的异常为剖析脑功能中潜在的神经回路和细胞变化提供了一种方法。由于将事件相关活动分解为其频率成分的技术的引入,EEG对于研究大脑信息处理是不可或缺的。具体而言,伽马频率范围(30 - 80Hz)的大脑活动被认为是认知功能的基础,并且可以用作内表型来辅助SCZ的诊断和治疗。在这篇综述中,我们阐述了表明SCZ静息态伽马功率增加的证据。我们探讨了在动物模型中模拟该疾病的这一方面如何有助于治疗开发以及深入了解SCZ的病因。

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