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Aperiodic phase re-setting in scalp EEG of beta-gamma oscillations by state transitions at alpha-theta rates.

机译:β-γ振荡的头皮脑电图中的非周期性相位重置是通过以α-θ速率的状态跃迁进行的。

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We evaluated the rapid changes in regional scalp EEG synchronization in normal subjects with spatial and temporal resolution exceeding prior art 10-fold with a high spatial density array and the Hilbert transform. A curvilinear array of 64 electrodes 3 mm apart extending 18.9 cm across the scalp was used to record EEG at 200/sec. Analytic amplitude (AA) and phase (AP) were calculated at each time step for the 64 traces in the analog pass band of 0.5-120 Hz. AP differences approximated the AP derivative (instantaneous frequency). The AP from unfiltered EEG revealed no reproducible patterns. Filtering was necessary in the beta and gamma ranges according to a technique that optimized the correlation of the AP differences with the activity band pass filtered in the alpha range. The sizes of temporal AP differences were usually within +/-0.5 radian from the average step corresponding to the center frequency of the pass band. Large AP differences were often synchronized over distances of 6 to 19 cm. An optimal pass band to detect and measure these recurring jumps in AP in the beta and gamma ranges was found by maximizing the alpha peak in the cospectrum of the correlation between unfiltered EEG and the band pass AP differences. Synchronized AP jumps recurred in clusters (CAP) at alpha and theta rates in resting subjects and with EMG. Cortex functions by serial changes in state. The Hilbert transform of EEG from high-density arrays can visualize these state transitions with high temporal and spatial resolution and should be useful in relating EEG to cognition.
机译:我们评估了正常人的区域头皮脑电图同步的快速变化,其空间和时间分辨率超过了现有技术的10倍,具有高空间密度阵列和希尔伯特变换。使用间隔为3 mm且在头皮上延伸18.9 cm的64个电极的曲线阵列以200 / sec的速度记录EEG。在0.5-120 Hz的模拟通带中的64条迹线的每个时间步长处都计算了分析幅度(AA)和相位(AP)。 AP差异近似于AP导数(瞬时频率)。未经过滤的脑电图的AP显示没有可再现的模式。根据优化AP差异与在alpha范围内滤波的活动带通的相关性的技术,在beta和gamma范围内必须进行滤波。 AP时间差异的大小通常在与通带中心频率相对应的平均步距+/- 0.5弧度以内。较大的AP差异通常在6至19 cm的距离上同步。通过最大化未过滤的脑电图和带通AP差异之间的相关谱中的α峰,找到了检测和测量AP在β和γ范围内这些重复跳跃的最佳通带。同步AP跳跃在静息对象和EMG中以alpha和theta率重复出现在簇(CAP)中。皮质通过状态的串行变化起作用。来自高密度阵列的脑电信号的希尔伯特变换可以以高的时间和空间分辨率可视化这些状态转换,并且在将脑电信号与认知联系起来时应该是有用的。

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