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精神分裂症中语义脑网络的紊乱:fMRI 研究。

Disorganization of Semantic Brain Networks in Schizophrenia Revealed by fMRI.

机构信息

Department of Psychiatry and Behavioral Sciences, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, Tokyo, Japan.

Department of Psychiatry, Graduate School of Medicine, Kyoto University, Kyoto, Japan.

出版信息

Schizophr Bull. 2023 Mar 15;49(2):498-506. doi: 10.1093/schbul/sbac157.

Abstract

OBJECTIVES

Schizophrenia is a mental illness that presents with thought disorders including delusions and disorganized speech. Thought disorders have been regarded as a consequence of the loosening of associations between semantic concepts since the term "schizophrenia" was first coined by Bleuler. However, a mechanistic account of this cardinal disturbance in terms of functional dysconnection has been lacking. To evaluate how aberrant semantic connections are expressed through brain activity, we characterized large-scale network structures of concept representations using functional magnetic resonance imaging (fMRI).

STUDY DESIGN

We quantified various concept representations in patients' brains from fMRI activity evoked by movie scenes using encoding modeling. We then constructed semantic brain networks by evaluating the similarity of these semantic representations and conducted graph theory-based network analyses.

STUDY RESULTS

Neurotypical networks had small-world properties similar to those of natural languages, suggesting small-worldness as a universal property in semantic knowledge networks. Conversely, small-worldness was significantly reduced in networks of schizophrenia patients and was correlated with psychological measures of delusions. Patients' semantic networks were partitioned into more distinct categories and had more random within-category structures than those of controls.

CONCLUSIONS

The differences in conceptual representations manifest altered semantic clustering and associative intrusions that underlie thought disorders. This is the first study to provide pathophysiological evidence for the loosening of associations as reflected in randomization of semantic networks in schizophrenia. Our method provides a promising approach for understanding the neural basis of altered or creative inner experiences of individuals with mental illness or exceptional abilities, respectively.

摘要

目的

精神分裂症是一种以思维障碍为特征的精神疾病,包括妄想和言语紊乱。自 Bleuler 首次提出“精神分裂症”一词以来,思维障碍一直被认为是语义概念之间联想松弛的结果。然而,对于这种功能连接失调的核心紊乱,缺乏一种机械论的解释。为了评估异常语义连接如何通过大脑活动表达,我们使用功能磁共振成像 (fMRI) 来描述概念表示的大规模网络结构。

研究设计

我们使用编码模型从电影场景引发的 fMRI 活动中量化了患者大脑中的各种概念表示。然后,我们通过评估这些语义表示的相似性来构建语义大脑网络,并进行基于图论的网络分析。

研究结果

神经典型网络具有类似于自然语言的小世界特性,这表明小世界是语义知识网络的普遍特性。相反,精神分裂症患者的小世界特性显著降低,并且与妄想的心理测量值相关。与对照组相比,患者的语义网络被分为更独特的类别,并且具有更多的随机类别内结构。

结论

概念表示的差异表现出改变的语义聚类和联想干扰,这是思维障碍的基础。这是第一项提供精神分裂症中语义网络随机化反映的联想松弛的病理生理学证据的研究。我们的方法为理解个体的改变或创造性的内在体验提供了一种有前途的方法,分别为精神疾病或特殊能力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c257/10016409/ae9e3dd3de01/sbac157f0001.jpg

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