高精神分裂型个体的异常功能连接和大脑网络组织:一种脑电图研究
Jelena Trajkovic1,2, Giulia Ricci3,4, Gabriele Pirazzini3
1Centro studi e ricerche in Neuroscienze Cognitive, Dipartimento di Psicologia, Alma Mater Studiorum - Università di Bologna, Campus di Cesena, Cesena 47521, Italy.
Schizophrenia bulletin
|February 4, 2025
概括
具有高精神分裂特征的健康个体表现出大脑网络组织的改变. 这些发现表明大脑网络效率和连接性降低,支持精神分裂症的维度模型.
科学领域:
- 神经科学是一个神经科学.
- 精神病学是一种精神病学.
- 大脑网络分析 脑网络分析
背景情况:
- 振荡同步对于大脑区域的功能连接至关重要.
- 精神分裂症的特征是大脑网络组织异常.
- 在健康个体中,高度的精神分裂特征可能表明功能网络发生了改变.
研究的目的:
- 研究高精神分裂型的健康个体的静止状态功能网络变化.
- 检查大脑节奏在推动网络变化中的作用.
- 了解与精神病风险相关的神经生理学特征.
主要方法:
- 休息状态脑电图 (EEG) 记录来自健康参与者,具有低和高的精神分裂分数.
- 用光谱格兰杰因果分析来计算theta,alpha,beta和gamma波段的功能连接.
- 图形理论指标来评估全球和本地大脑网络属性.
主要成果:
- 高精神分裂型的个体表现出较低的局部效率 (乙,α波段) 和降低的全球效率 (乙,α,β波段).
- 观察到节点中心性降低和频率特定的功能连接性下降.
- 在较慢的频率下,上下连接减少,在更快的节奏下,上下连接减少.
结论:
- 患有高精神分裂型的健康个体表现出功能性大脑组织效率较低.
- 功能连接的系统性下降影响了自上而下的和自下而上的处理.
- 频率特定的网络变化支持精神分裂症的维度模型,并识别神经生理学特征.
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