Rong Yao, Meirong Song, Langhua Shi, Yan Pei, Haifang Li, Shuping Tan, Bin Wang
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引用次数: 0
Abstract
Objectives. There is a significant correlation between EEG microstate and the neurophysiological basis of mental illness, brain state, and cognitive function. Given that the unclear relationship between network dynamics and different microstates, this paper utilized microstate, brain network, and control theories to understand the microstate characteristics of short-term memory task, aiming to mechanistically explain the most influential microstates and brain regions driving the abnormal changes in brain state transitions in patients with schizophrenia. Methods. We identified each microstate and analyzed the microstate abnormalities in schizophrenia patients during short-term memory tasks. Subsequently, the network dynamics underlying the primary microstates were studied to reveal the relationships between network dynamics and microstates. Finally, using control theory, we confirmed that the abnormal changes in brain state transitions in schizophrenia patients are driven by specific microstates and brain regions. Results. The frontal-occipital lobes activity of microstate D decreased significantly, but the left frontal lobe of microstate B increased significantly in schizophrenia, when the brain was moving toward the easy-to-reach states. However, the frontal-occipital lobes activity of microstate D decreased significantly in schizophrenia, when the brain was moving toward the hard-to-reach states. Microstate D showed that the right-frontal activity had a higher priority than the left-frontal, but microstate B showed that the left-frontal priority decreased significantly in schizophrenia, when changes occur in the synchronization state of the brain. Conclusions. In conclusion, microstate D may be a biomarker candidate of brain abnormal activity during the states transitions in schizophrenia, and microstate B may represent a compensatory mechanism that maintains brain function and exchanges information with other brain regions. Microstate and brain network provide complementary perspectives on the neurodynamics, offering potential insights into brain function in health and disease.
目的。脑电图微状态与精神疾病的神经生理基础、大脑状态和认知功能之间存在着明显的相关性。鉴于网络动力学与不同微状态之间的关系尚不明确,本文利用微状态、脑网络和控制理论来理解短时记忆任务的微状态特征,旨在从机理上解释驱动精神分裂症患者脑状态转换异常变化的最有影响力的微状态和脑区。研究方法我们识别了精神分裂症患者在短时记忆任务中的每个微状态,并分析了微状态的异常。随后,我们研究了主要微状态背后的网络动力学,以揭示网络动力学与微状态之间的关系。最后,我们利用控制理论证实,精神分裂症患者大脑状态转换的异常变化是由特定微状态和脑区驱动的。研究结果精神分裂症患者大脑向易达状态转变时,微状态 D 的额叶-枕叶活动明显减少,但微状态 B 的左额叶活动明显增加。然而,当精神分裂症患者的大脑进入难以达到的状态时,微状态 D 的额叶-枕叶活动明显减少。微状态 D 显示右额叶活动的优先级高于左额叶,但微状态 B 显示在精神分裂症中,当大脑同步状态发生变化时,左额叶的优先级明显降低。结论总之,微状态 D 可能是精神分裂症患者在状态转换过程中大脑异常活动的候选生物标志物,而微状态 B 可能代表了一种维持大脑功能并与其他脑区交换信息的补偿机制。微状态和脑网络为神经动力学提供了互补的视角,为洞察健康和疾病中的脑功能提供了可能。
期刊介绍:
Brain Sciences (ISSN 2076-3425) is a peer-reviewed scientific journal that publishes original articles, critical reviews, research notes and short communications in the areas of cognitive neuroscience, developmental neuroscience, molecular and cellular neuroscience, neural engineering, neuroimaging, neurolinguistics, neuropathy, systems neuroscience, and theoretical and computational neuroscience. Our aim is to encourage scientists to publish their experimental and theoretical results in as much detail as possible. There is no restriction on the length of the papers. The full experimental details must be provided so that the results can be reproduced. Electronic files or software regarding the full details of the calculation and experimental procedure, if unable to be published in a normal way, can be deposited as supplementary material.