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Electrophysiological indicators of gesture perception

机译:姿态感知的电生理指标

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摘要

Electroencephalography (EEG) activity in the mu frequency band (8-13 Hz) is suppressed during both gesture performance and observation. However, it is not clear if or how particular characteristics within the kinematic execution of gestures map onto dynamic changes in mu activity. Mapping the time course of gesture kinematics onto that of mu activity could help understand which aspects of gestures capture attention and aid in the classification of communicative intent. In this work, we test whether the timing of inflection points within gesture kinematics predicts the occurrence of oscillatory mu activity during passive gesture observation. The timing for salient features of performed gestures in video stimuli was determined by isolating inflection points in the hands' motion trajectories. Participants passively viewed the gesture videos while continuous EEG data was collected. We used wavelet analysis to extract mu oscillations at 11 Hz and at central electrodes and occipital electrodes. We used linear regression to test for associations between the timing of inflection points in motion trajectories and mu oscillations that generalized across gesture stimuli. Separately, we also tested whether inflection point occurrences evoked mu/alpha responses that generalized across participants. Across all gestures and inflection points, and pooled across participants, peaks in 11 Hz EEG waveforms were detected 465 and 535 ms after inflection points at occipital and central electrodes, respectively. A regression model showed that inflection points in the motion trajectories strongly predicted subsequent mu oscillations (R2=0.921,p<0.01); effects were weaker and non-significant for low (17 Hz) and high (21 Hz) beta activity. When segmented by inflection point occurrence rather than stimulus onset and testing participants as a random effect, inflection points evoked mu and beta activity from 308 to 364 ms at central electrodes, and broad activity from 226 to 800 ms at occipital electrodes. The results suggest that inflection points in gesture trajectories elicit coordinated activity in the visual and motor cortices, with prominent activity in the mu/alpha frequency band and extending into the beta frequency band. The time course of activity indicates that visual processing drives subsequent activity in the motor cortex during gesture processing, with a lag of approximately 80 ms.
机译:在手势性能和观察期间,MU频带(8-13Hz)中的脑电图(EEG)活动被抑制。然而,不明确或者在手势地图的运动映射中的特定特征在MU活动中的动态变化上。将手势运动学的时间过程映射到MU活动中的时间,可以帮助了解手势的哪个方面捕获关注和援助通信意图的分类。在这项工作中,我们测试手势运动学中拐点的时间是否预测被动手势观察期间振荡μ活性的发生。通过隔离手中的运动轨迹中的拐点来​​确定视频刺激中所执行手势的显着特征的定时。参与者在收集连续EEG数据时被动地查看了手势视频。我们使用小波分析以在11Hz和中央电极和枕骨电极处提取MU振荡。我们使用线性回归来测试运动轨迹中拐点的时序与横跨手势刺激的MU振荡之间的关联。另外,我们还测试了扇形点是否发生越过跨参与者广泛的MU / Alpha响应。在所有手势和拐点上,并跨参与者汇集,分别检测了11 Hz EEG波形中的峰值,分别在枕骨和中心电极的拐点后检测到465和535ms。回归模型显示运动轨迹中的拐点强烈预测后续μ振荡(R2 = 0.921,P <0.01);对低(17Hz)和高(21Hz)β活性的影响较弱和非显着性。当被拐点发生而不是刺激发作和测试参与者作为随机效应,拐点在中央电极在中央电极308至364ms中诱发MU和β活性,并且在枕部电极的宽度为226至800ms。结果表明,姿势轨迹的拐点在视觉和电机皮质中引起协调活动,在MU / alpha频带中具有突出的活动,并延伸到β频带中。活动时间过程指示在手势处理期间,视觉处理驱动电机皮层中的后续活动,滞后约为80毫秒。

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