Data_Sheet_2_Decoding the Temporal Dynamics of Covert Spatial Attention Using Multivariate EEG Analysis: Contributions of Raw Amplitude and Alpha Power.PDF

Attention can be oriented in space covertly without the need of eye movements. We used multivariate pattern classification analyses (MVPA) to investigate whether the time course of the deployment of covert spatial attention leading up to the observer’s perceptual decision can be decoded from both EEG alpha power and raw activity traces. Decoding attention from these signals can help determine whether raw EEG signals and alpha power reflect the same or distinct features of attentional selection. Using a classical cueing task, we showed that the orientation of covert spatial attention can be decoded by both signals. However, raw activity and alpha power may reflect different features of spatial attention, with alpha power more associated with the orientation of covert attention in space and raw activity with the influence of attention on perceptual processes.

无需眼球运动，即可在空间内隐蔽地定向注意力。本研究采用多变量模式分类分析（Multivariate Pattern Classification Analyses, MVPA），旨在探究能否从脑电α功率（EEG alpha power）与原始活动轨迹中，解码出观察者做出知觉决策前，隐蔽空间注意力部署的时间进程。从上述信号中解码注意力特征，有助于厘清原始脑电信号与α功率究竟反映了注意力选择的相同特征，还是不同特征。通过经典线索提示任务，本研究证实两类信号均可解码隐蔽空间注意力的定向信息。但原始活动轨迹与α功率所反映的空间注意力特征存在差异：α功率更多与空间内隐蔽注意力的定向相关，而原始活动轨迹则与注意力对知觉加工的影响相关。