Huang Ruey-Song, Jung Tzyy-Ping, Delorme Arnaud, Makeig Scott
Swartz Center for Computational Neuroscience, Institute for Neural Computation, University of California San Diego, La Jolla, CA 92093-0961, USA.
Neuroimage. 2008 Feb 15;39(4):1896-909. doi: 10.1016/j.neuroimage.2007.10.036. Epub 2007 Nov 7.
Tonic and phasic dynamics of electroencephalographic (EEG) activities during a continuous compensatory tracking task (CTT) were analyzed using time-frequency analysis of EEG sources identified by independent component analysis (ICA). In 1-hour sessions, 70-channel EEG data were recorded while participants attempted to use frequent compensatory trackball movements to maintain a drifting disc close to a bulls-eye at screen center. Disc trajectories were converted into two moving-average performance measures, root mean square distance of the disc from screen center in 4-s ('local') and in 20-s ('global') moving time windows. Maximally independent EEG processes and their equivalent dipole source locations were obtained using the EEGLAB toolbox (http://sccn.ucsd.edu/eeglab). Across subjects and sessions, independent EEG processes in occipital, somatomotor, and supplementary motor cortices exhibited tonic power increases during periods of high tracking error, plus additional phasic power increases in several frequency bands before and after trackball movements following disc 'perigees' (moments at which the disc began to drift away from the bulls-eye). These phasic activity increases, which were larger during high-error periods, reveal an intimate relation between EEG dynamics and top-down recognition of responding to threatening events. Thus during a continuous tracking task without impulsive stimulus onsets, sub-second scale EEG dynamics related to visuomotor task could be dissociated from slower spectral modulations linked to changes in performance and arousal. We tentatively interpret the observed EEG signal increases as indexing tonic and phasic modulations of the levels of task attention and engagement required to maintain visuomotor performance during sustained performance.
使用独立成分分析(ICA)识别的脑电图(EEG)源的时频分析,分析了连续补偿跟踪任务(CTT)期间EEG活动的强直和相位动力学。在1小时的实验中,记录了70通道的EEG数据,参与者试图通过频繁的补偿轨迹球运动,将一个漂移的圆盘保持在屏幕中心的靶心附近。圆盘轨迹被转换为两种移动平均性能指标,即圆盘在4秒(“局部”)和20秒(“全局”)移动时间窗口内与屏幕中心的均方根距离。使用EEGLAB工具箱(http://sccn.ucsd.edu/eeglab)获得最大独立的EEG过程及其等效偶极子源位置。在不同受试者和实验中,枕叶、躯体运动和辅助运动皮层的独立EEG过程在高跟踪误差期间表现出强直功率增加,并且在圆盘“近心点”(圆盘开始偏离靶心的时刻)之后轨迹球运动之前和之后的几个频段中,相位功率进一步增加。这些相位活动增加在高误差期间更大,揭示了EEG动力学与对威胁事件反应的自上而下识别之间的密切关系。因此,在没有冲动刺激发作的连续跟踪任务期间,与视觉运动任务相关的亚秒级EEG动力学可以与与性能和唤醒变化相关的较慢频谱调制区分开来。我们初步将观察到的EEG信号增加解释为在持续表现期间维持视觉运动性能所需的任务注意力和参与水平的强直和相位调制指标。