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精神分裂症患者认知和临床症状的基础是静息态功能连接异常。

Abnormal resting-state functional connectivity underlies cognitive and clinical symptoms in patients with schizophrenia.

作者信息

Jia Yingxin, Jariwala Namasvi, Hinkley Leighton B N, Nagarajan Srikantan, Subramaniam Karuna

机构信息

Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, United States.

Department of Psychiatry, University of California, San Francisco, San Francisco, CA, United States.

出版信息

Front Hum Neurosci. 2023 Feb 15;17:1077923. doi: 10.3389/fnhum.2023.1077923. eCollection 2023.

Abstract

INTRODUCTION

The cognitive and psychotic symptoms in patients with schizophrenia (SZ) are thought to result from disrupted brain network connectivity.

METHODS

We capitalize on the high spatiotemporal resolution of magnetoencephalography imaging (MEG) to record spontaneous neuronal activity in resting state networks in 21 SZ compared with 21 healthy controls (HC).

RESULTS

We found that SZ showed significant global disrupted functional connectivity in delta-theta (2-8 Hz), alpha (8-12 Hz), and beta (12-30 Hz) frequencies, compared to HC. Disrupted global connectivity in alpha frequencies with bilateral frontal cortices was associated with more severe clinical psychopathology (i.e., positive psychotic symptoms). Specifically, aberrant connectivity in beta frequencies between the left primary auditory cortex and cerebellum, was linked to greater hallucination severity in SZ. Disrupted connectivity in delta-theta frequencies between the medial frontal and left inferior frontal cortex was associated with impaired cognition.

DISCUSSION

The multivariate techniques employed in the present study highlight the importance of applying our source reconstruction techniques which leverage the high spatial localization abilities of MEG for estimating neural source activity using beamforming methods such as SAM (synthetic aperture morphometry) to reconstruct the source of brain activity, together with functional connectivity assessments, assayed with imaginary coherence metrics, to delineate how neurophysiological dysconnectivity in specific oscillatory frequencies between distinct regions underlie the cognitive and psychotic symptoms in SZ. The present findings employ powerful techniques in spatial and time-frequency domains to provide potential neural biomarkers underlying neuronal network dysconnectivity in SZ that will inform the development of innovations in future neuromodulation treatment development.

摘要

引言

精神分裂症(SZ)患者的认知和精神症状被认为是由大脑网络连接中断所致。

方法

我们利用脑磁图成像(MEG)的高时空分辨率,记录了21例SZ患者与21名健康对照者(HC)静息态网络中的自发神经元活动。

结果

我们发现,与HC相比,SZ患者在δ-θ(2-8赫兹)、α(8-12赫兹)和β(12-30赫兹)频率下表现出显著的整体功能连接中断。α频率下与双侧额叶皮质的整体连接中断与更严重的临床精神病理学症状(即阳性精神症状)相关。具体而言,左侧初级听觉皮层与小脑之间β频率的异常连接与SZ患者更严重的幻觉严重程度相关。内侧额叶与左侧额下回皮质之间δ-θ频率的连接中断与认知障碍有关。

讨论

本研究中采用的多变量技术突出了应用我们的源重建技术的重要性,该技术利用MEG的高空间定位能力,使用诸如SAM(合成孔径形态测量)等波束形成方法来估计神经源活动,以重建大脑活动的源,同时结合功能连接评估,用虚相干度量进行测定,以描绘不同区域之间特定振荡频率的神经生理连接障碍如何构成SZ患者认知和精神症状的基础。本研究结果在空间和时频域采用了强大的技术,以提供SZ患者神经元网络连接障碍潜在的神经生物标志物,这将为未来神经调节治疗发展中的创新提供信息。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d883/9976937/96daa5ee4a32/fnhum-17-1077923-g001.jpg

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