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Psychiatry Clin Neurosci:清醒状态下精神分裂症患者的多变量尖锐波

2024-07-02 xiongjy MedSci原创 发表于上海

本研究发现精神分裂症患者的尖锐波纹(SPW-Rs)事件发生频率增加,耦合相位延迟,且在脑状态转变中的参与度较低,提示SPW-Rs异常可能是精神分裂症病理生理学的重要方面。

精神分裂症(SZ)是一种以精神病性症状和认知功能障碍为特征的脑部疾病。近年来,研究表明,精神分裂症患者的尖锐波纹(SPW-Rs)存在异常。这些SPW-Rs在记忆巩固中起着关键作用,其异常可能导致精神病性症状和认知功能障碍。本研究旨在通过对精神分裂症患者在清醒状态下的全脑活动进行多变量分析,探讨这些异常SPW-Rs的特征及其与脑状态转变的关系。

本研究在群马大学医院招募了20名精神分裂症患者(SZ)和20名性别和年龄匹配的健康对照组(HC)。使用脑磁图(MEG)在清醒状态下测量参与者的全脑活动。参与者被要求在测量期间睁眼放松,注视固定点。

使用306通道的Elekta NeuroMag设备采集数据,采样率设为1002 Hz。同时使用电极记录心电图(ECG)和眼电图(EOG),以测量生物伪影的影响。通过使用自动检测算法检测SPW-Rs事件,并通过复杂Morlet小波卷积(CMW)进行时间序列分析。

此外,作者开发了一种新的多变量分析方法,称为“ripple-gedMEG”,以提取SPW-Rs的全局特征,并研究SPW-Rs与脑状态转变之间的关系。

图1 精神分裂症和健康对照组中自动检测的尖锐波纹事件的传感器位置及基本特征

在数据预处理过程中,使用Max filter 2.0和独立成分分析(ICA)移除系统噪音和生物伪影,并将采样率从1002 Hz降至1000 Hz。

随后,使用MATLAB R2021a和Brainstorm软件包进行离线数据处理。通过复杂Morlet小波卷积(CMW)计算30至250 Hz频段的时间序列功率,并通过带通滤波提取振幅波动和包络线。采用Wasserstein调制指数(wMI)量化SPW-Rs的相位-振幅耦合(PAC)。

图2 尖锐波纹的时间频率分解

结果显示,精神分裂症患者的SPW-Rs事件发生频率显著增加,耦合相位延迟,并且出现在不同的脑区。SPW-Rs在精神分裂症患者中的时空模式较为无序,且在脑状态转变中的参与度较低。

此外,通过广义线性模型(GLM)发现,这些SPW-Rs的神经特征与精神分裂症的阳性和阴性症状量表(PANSS)得分显著相关。多变量分析表明,精神分裂症患者的SPW-Rs网络模式与健康对照组相似,但其网络形成较弱。

图3 使用Wasserstein调制指数(wMI)分析的相位振幅耦合(PAC)

在脑状态转变分析中,通过能量景观分析(ELA)发现,SPW-Rs的发生与脑状态的转变有显著关联。

精神分裂症患者的脑状态转变模式与健康对照组不同,且在SPW-Rs发生时,脑状态的转变概率显著降低。这些结果表明,SPW-Rs异常可能是精神分裂症病理生理学的一个重要方面。

图4 通过广义特征分解(GED)分析的多变量尖锐波纹(ripple-gedMEG)

本研究确定了精神分裂症患者在清醒状态下SPW-Rs的异常特征,并证实这些异常与精神分裂症的神经病理学密切相关。这些发现为人类精神分裂症研究提供了新的方向,可能有助于开发新的治疗策略。

图5 尖锐波纹对脑状态转变概率的影响

原始出处:
Ohki T, Chao ZC, Takei Y, Kato Y, Sunaga M, Suto T, et al. Multivariate sharp‐wave ripples in schizophrenia during awake state. Psychiatry Clin Neurosci 2024. https://doi.org/10.1111/pcn.13702.

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    2024-07-03 屋顶瞄爱赏月 来自贵州省

    签到学习

    0

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    2024-07-02 1209e435m98(暂无昵称) 来自浙江省

    学习了,谢谢分享

    0

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    2024-07-02 医鸣惊人 来自山西省

    认真学习了

    0

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