Dynamic Formation of a Posterior-to-Anterior Peak-Alpha-Frequency Gradient Driven by Two Distinct Processes.

IF 2.7 3区 医学 Q3 NEUROSCIENCES eNeuro Pub Date : 2024-08-29 Print Date: 2024-08-01 DOI:10.1523/ENEURO.0273-24.2024
Max Kailler Smith, Marcia Grabowecky, Satoru Suzuki
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Abstract

Peak-alpha frequency varies across individuals and mental states, but it also forms a negative gradient from posterior to anterior regions in association with increases in cortical thickness and connectivity, reflecting a cortical hierarchy in temporal integration. Tracking the spatial standard deviation of peak-alpha frequency in scalp EEG, we observed that a posterior-to-anterior gradient dynamically formed and dissolved. Periods of high spatial standard deviation yielded robustly negative posterior-to-anterior gradients-the "gradient state"-while periods of low spatial standard deviation yielded globally converged peak-alpha frequency-the "uniform state." The state variations were characterized by a combination of slow (0.3-0.5 Hz) oscillations and random-walk-like fluctuations. They were relatively independently correlated with peak-alpha frequency variations in anterior regions and peak-alpha power variations in central regions driven by posterior regions (together accounting for ∼50% of the state variations), suggesting that two distinct mechanisms modulate the state variations: an anterior mechanism that directly adjusts peak-alpha frequencies and a posterior-central mechanism that indirectly adjusts them by influencing synchronization. The state variations likely reflect general operations as their spatiotemporal characteristics remained unchanged while participants engaged in a variety of tasks (breath focus, vigilance, working memory, mental arithmetic, and generative thinking) with their eyes closed or watched a silent nature video. The ongoing state variations may dynamically balance two global processing modes, one that facilitates greater temporal integration (and potentially also information influx) toward anterior regions in the gradient state and the other that facilitates flexible global communication (via phase locking) in the uniform state.

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在两个不同过程的驱动下,后向前方的峰值-α-频率梯度动态形成。
阿尔法峰值频率因个体和精神状态而异,但它也会随着皮层厚度和连接性的增加而形成从后部到前部的负梯度,这反映了皮层在时间整合方面的层次结构。通过追踪头皮脑电图中阿尔法峰值频率的空间标准偏差,我们观察到后部到前部梯度的动态形成和消解。高空间标准偏差时期会产生强烈的负后向前方梯度--"梯度状态",而低空间标准偏差时期则会产生全球趋同的阿尔法峰值频率--"均匀状态"。状态变化的特点是缓慢(0.3 Hz-0.5 Hz)振荡和随机漫步式波动的结合。它们与前部区域的阿尔法峰频率变化和由后部区域驱动的中部区域的阿尔法峰功率变化(共占状态变化的 50%)相对独立相关,这表明有两种不同的机制调节状态变化:前部机制直接调整阿尔法峰频率,而后部-中部机制则通过影响同步性间接调整阿尔法峰频率。当参与者闭眼完成各种任务(呼吸专注、警觉、工作记忆、心算和生成性思维)或观看无声自然视频时,状态变化的时空特征保持不变,因此状态变化很可能反映了一般操作。持续的状态变化可能会动态地平衡两种全局处理模式,一种是在梯度状态下促进更多的时间整合(也可能是信息流入)到前部区域,另一种是在均匀状态下促进灵活的全局交流(通过相位锁定)。我们的脑电图研究发现,α振荡频率的空间模式在形成负的后向前方梯度(即 "梯度状态")和全局汇聚(即 "均匀状态")之间动态变化。梯度状态可能有利于向前部区域的时间整合(也可能是信息流入),而均匀状态则可能通过相位锁定促进灵活的全球交流。我们的研究结果进一步表明,梯度状态和均匀状态之间的变化是由两种不同的机制控制的:一种是直接调整阿尔法振荡频率的前部机制,另一种是通过增加或减少上阿尔法波段的全球振荡夹带来间接调整频率的后部机制。
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来源期刊
eNeuro
eNeuro Neuroscience-General Neuroscience
CiteScore
5.00
自引率
2.90%
发文量
486
审稿时长
16 weeks
期刊介绍: An open-access journal from the Society for Neuroscience, eNeuro publishes high-quality, broad-based, peer-reviewed research focused solely on the field of neuroscience. eNeuro embodies an emerging scientific vision that offers a new experience for authors and readers, all in support of the Society’s mission to advance understanding of the brain and nervous system.
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