Department of Psychology, Northwestern University, Evanston, Illinois 60208.
Department of Psychology and Interdepartmental Neuroscience, Northwestern University, Evanston, Illinois 60208.
eNeuro. 2024 Aug 29;11(8). doi: 10.1523/ENEURO.0273-24.2024. Print 2024 Aug.
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.
峰 alpha 频率在个体和心理状态之间存在差异,但它也在后脑区域到前脑区域形成负梯度,与皮质厚度和连通性的增加有关,反映了时间整合的皮质层次结构。通过跟踪头皮 EEG 中峰 alpha 频率的空间标准差,我们观察到从后向前的梯度动态形成和溶解。高空间标准差的周期产生了稳健的负后向前梯度——“梯度状态”,而低空间标准差的周期产生了全局收敛的峰 alpha 频率——“均匀状态”。状态变化的特点是慢(0.3-0.5 Hz)振荡和随机游走样波动的组合。它们与前脑区域的峰 alpha 频率变化和后脑区域驱动的中央区域的峰 alpha 功率变化相对独立相关(共占状态变化的约 50%),这表明两种不同的机制调节了状态变化:一种是直接调节峰 alpha 频率的前脑机制,另一种是通过影响同步间接调节峰 alpha 频率的后脑-中央机制。状态变化可能反映了一般操作,因为它们的时空特征在参与者闭眼进行各种任务(呼吸专注、警觉、工作记忆、心算和生成思维)或观看无声自然视频时保持不变。持续的状态变化可能会动态平衡两种全局处理模式,一种模式在梯度状态下促进更大的时间整合(并且潜在地还促进信息流入)到前脑区域,另一种模式在均匀状态下促进灵活的全局通信(通过相位锁定)。