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Abnormal Information Flow in Schizophrenia Is Linked to Psychosis
Schizophrenia Bulletin ( IF 5.3 ) Pub Date : 2022-09-08 , DOI: 10.1093/schbul/sbac075
Yingxin Jia 1 , Kiwamu Kudo 1, 2 , Leighton B N Hinkley 1 , Melissa Fisher 3 , Sophia Vinogradov 3 , Srikantan Nagarajan 1 , Karuna Subramaniam 4
Affiliation  

Background and Hypothesis Prior research has shown that patients with schizophrenia (SZ) show disruption in brain network connectivity that is thought to underlie their cognitive and psychotic symptoms. However, most studies examining functional network disruption in schizophrenia have focused on the temporally correlated coupling of the strength of network connections. Here, we move beyond correlative metrics to assay causal computations of connectivity changes in directed neural information flow, assayed from a neural source to a target in SZ. Study Design This study describes a whole-brain magnetoencephalography-imaging approach to examine causal computations of connectivity changes in directed neural information flow between brain regions during resting states, quantified by phase-transfer entropy (PTE) metrics, assayed from a neural source to an endpoint, in 21 SZ compared with 21 healthy controls (HC), and associations with cognitive and clinical psychotic symptoms in SZ. Study Results We found that SZ showed significant disruption in information flow in alpha (8–12 Hz) and beta (12–30 Hz) frequencies, compared to HC. Reduced information flow in alpha frequencies from the precuneus to the medio-ventral occipital cortex was associated with more severe clinical psychopathology (ie, positive psychotic symptoms), while reduced information flow between insula and middle temporal gyrus was associated with worsening cognitive symptoms. Conclusions The present findings highlight the importance of delineating dysfunction in neural information flow in specific oscillatory frequencies between distinct regions that underlie the cognitive and psychotic symptoms in SZ, and provide potential neural biomarkers that could lead to innovations in future neuromodulation treatment development.

中文翻译:

精神分裂症的异常信息流与精神病有关

背景和假设 先前的研究表明,精神分裂症 (SZ) 患者的大脑网络连接中断,这被认为是其认知和精神病症状的基础。然而,大多数检查精神分裂症功能网络中断的研究都集中在网络连接强度的时间相关耦合上。在这里,我们超越相关指标来分析定向神经信息流中连通性变化的因果计算,从神经源到 SZ 中的目标进行分析。研究设计本研究描述了一种全脑脑磁图成像方法,用于检查静息状态下大脑区域之间定向神经信息流的连通性变化的因果计算,通过相转移熵 (PTE) 指标进行量化,从神经源到终点,在 21 个 SZ 中与 21 个健康对照 (HC) 进行比较,并与 SZ 中的认知和临床精神病症状相关联。研究结果 我们发现,与 HC 相比,SZ 在 alpha (8–12 Hz) 和 beta (12–30 Hz) 频率的信息流中表现出显着中断。从楔前叶到内侧-腹侧枕叶皮层的 alpha 频率信息流减少与更严重的临床精神病理学(即阳性精神病症状)相关,而脑岛和颞中回之间的信息流减少与认知症状恶化相关。
更新日期:2022-09-08
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