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个体功能脑网络拓扑的差异与精神分裂症症状有关。

Individual Variation in Functional Brain Network Topography is Linked to Schizophrenia Symptomatology.

机构信息

Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, Massachusetts.

Department of Psychiatry, Harvard Medical School, Boston, Massachusetts.

出版信息

Schizophr Bull. 2021 Jan 23;47(1):180-188. doi: 10.1093/schbul/sbaa088.

Abstract

Resting-state fMRI (rsfMRI) demonstrates that the brain is organized into distributed networks. Numerous studies have examined links between psychiatric symptomatology and network functional connectivity. Traditional rsfMRI analyses assume that the spatial organization of networks is invariant between individuals. This dogma has recently been overturned by the demonstration that networks show significant variation between individuals. We tested the hypothesis that previously observed relationships between schizophrenia-negative symptom severity and network connectivity are actually due to individual differences in network spatial organization. Forty-four participants diagnosed with schizophrenia underwent rsfMRI scans and clinical assessments. A multivariate pattern analysis determined how whole-brain functional connectivity correlates with negative symptom severity at the individual voxel level. Brain connectivity to a region of the right dorsolateral prefrontal cortex correlates with negative symptom severity. This finding results from individual differences in the topographic distribution of 2 networks: the default mode network (DMN) and the task-positive network (TPN). Both networks demonstrate strong (r = ~0.49) and significant (P < .001) relationships between topography and symptom severity. For individuals with low symptom severity, this critical region is part of the DMN. In highly symptomatic individuals, this region is part of the TPN. Previously overlooked individual variation in brain organization is tightly linked to differences in schizophrenia symptom severity. Recognizing critical links between network topography and pathological symptomology may identify key circuits that underlie cognitive and behavioral phenotypes. Individual variation in network topography likely guides different responses to clinical interventions that rely on anatomical targeting (eg, transcranial magnetic stimulation [TMS]).

摘要

静息态功能磁共振成像 (rsfMRI) 表明大脑组织成分布式网络。许多研究都检查了精神症状与网络功能连接之间的联系。传统的 rsfMRI 分析假设网络的空间组织在个体之间是不变的。最近的研究推翻了这一教条,证明网络在个体之间存在显著的差异。我们测试了这样一个假设,即先前观察到的精神分裂症阴性症状严重程度与网络连接之间的关系实际上是由于网络空间组织的个体差异造成的。44 名被诊断为精神分裂症的参与者接受了 rsfMRI 扫描和临床评估。多元模式分析确定了全脑功能连接与个体体素水平阴性症状严重程度的关系。大脑与右侧背外侧前额叶皮质的连接与阴性症状的严重程度相关。这一发现源于两个网络的拓扑分布个体差异:默认模式网络 (DMN) 和任务正性网络 (TPN)。这两个网络都显示出拓扑结构和症状严重程度之间的强(r = ~0.49)和显著(P <.001)关系。对于症状严重程度低的个体,这个关键区域是 DMN 的一部分。对于症状严重程度高的个体,这个区域是 TPN 的一部分。以前被忽视的大脑组织个体差异与精神分裂症症状严重程度的差异密切相关。认识到网络拓扑结构和病理性症状之间的关键联系,可能有助于确定认知和行为表型的关键回路。网络拓扑结构的个体差异可能会指导基于解剖靶点(例如,经颅磁刺激 [TMS])的不同临床干预措施的反应。

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