Alpha and SSVEP power outperform Gamma power in capturing Attentional Modulation in Human EEG

Abstract

The effect of visual attention has been extensively studied using various techniques such as macaque neurophysiology that yields spikes and local field potential (LFP), and human electro/magneto encephalogram (EEG/MEG). Attention typically suppresses power at low frequencies such as alpha band (8-12 Hz) and increases power in gamma band (>30 Hz) in brain signals. In addition, EEG studies often use flickering stimuli that produce a specific measure called steady-state visually evoked potential (SSVEP), whose power also increases with attention. However, effectiveness of these various neural measures in capturing attentional modulation is unknown since the stimuli and task paradigms vary widely across these studies. In a recent macaque neurophysiology study with flickering stimuli, we found that the effect of attention was more salient in the gamma band and beyond of the LFP, compared to alpha or SSVEP. To compare this with human EEG, we designed an orientation change detection task where we presented both static and counterphasing stimuli of matched difficulty levels to male (N=15) and female (N=11) subjects, allowing us to compare attentional modulation of various measures under similar conditions. We report two main results. First, attentional modulation was comparable for SSVEP and alpha. Second, non-foveal stimuli produced weak gamma despite various stimulus optimizations and showed a negligible effect of attention although full-screen gratings showed robust gamma activity. Our results are useful for brain-machine-interfacing studies where suitable features depending on recording modality are used for decoding attention, and also provide clues about the spatial scales of neural mechanisms underlying attention. Significance StatementVarious neural measures such as alpha and gamma band power or SSVEP power capture signatures of visual attention. A systematic comparison of their effectiveness in capturing attentional modulation is important for understanding different neural computations underlying attention and for developing brain-machine-interfaces (BMIs) that can decode the focus of attention. Since stimulus configuration and task paradigms vary widely across visual attention studies, we recorded all the relevant neural signals during an attention task under similar stimulus and behavioral conditions in human EEG. In contrast to invasive recordings in which gamma outperforms other measures, our results show that in human EEG, attentional modulation of alpha and SSVEP are comparable, and non-foveal stimuli produce weak gamma which is not well modulated by attention.