在高精神分裂型中增加结构连接性
Eirini Messaritaki1, Sonya Foley1, Kali Barawi2
1Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, UK.
Network neuroscience (Cambridge, Mass.)
|June 19, 2023
概括
这项研究发现,在健康个体中,较高的精神分裂性得分与感觉运动和默认模式网络中的结构性大脑连接的改变有关. 这些发现提供了关于精神分裂症的神经基础和精神分裂症的潜在联系的见解.
科学领域:
- 神经科学是一个神经科学.
- 精神病学是一个精神病学.
- 网络科学 网络科学
背景情况:
- 精神分裂,一种人格特征,与精神分裂症有共同的病因因素.
- 了解精神分裂症的神经基础可能会揭示精神分裂症的病理生理学.
研究的目的:
- 为了研究大脑结构连接和健康成年人的精神分裂之间的关系.
- 探索结构性大脑网络的图形理论特性,与精神分裂性得分相关.
主要方法:
- 利用来自两个独立队列 (140名和115名参与者) 的扩散MRI数据来构建结构性大脑网络.
- 为默认模式,传感动力,视觉和听觉子网络计算的图形理论指标.
- 相关联的网络指标与从精神分裂型人格调查问卷 (SPQ) 获得的精神分裂型得分.
主要成果:
- 在传感器和默认模式子网络中,观察到分裂性得分与平均节点度和平均聚类系数之间的正相关性.
- 涉及的关键大脑区域包括右后中心,左侧中心叶片,右上额头,左侧海马和双侧前.
- 这些已识别的节点在精神分裂症中显示功能连接受损.
结论:
- 结构性大脑网络的改变与健康个体的精神分裂有关.
- 研究结果表明,传感运动和默认模式网络中断可能代表精神分裂症和精神分裂症之间共同的神经脆弱性.
- 这项研究为精神分裂症的神经生物学基础提供了新的见解.
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