Alpha Power Modulates Perception Independently of Endogenous Factors

Abstract

Oscillations are ubiquitous in the brain. Alpha oscillations in particular have been proposed to play an important role in sensory perception. Past studies have shown that the power of ongoing EEG oscillations in the alpha band is negatively correlated with visual outcome. Moreover, it also co-varies with other endogenous factors such as attention, vigilance, or alertness. In turn, these endogenous factors influence visual perception. Therefore, it remains unclear how much of the relation between alpha and perception is indirectly mediated by such endogenous factors, and how much reflects a direct causal influence of alpha rhythms on sensory neural processing. We propose to disentangle the direct from the indirect causal routes by introducing modulations of alpha power, independently of any fluctuations in endogenous factors. To this end, we use white-noise sequences to constrain the brain activity of 20 participants. The cross-correlation between the white-noise sequences and the concurrently recorded EEG reveals the impulse response function (IRF), a model of the systematic relationship between stimulation and brain response. These IRFs are then used to reconstruct rather than record the brain activity linked with new random sequences (by convolution). Interestingly, this reconstructed EEG only contains information about oscillations directly linked to the white-noise stimulation; fluctuations in attention and other endogenous factors may still modulate brain alpha rhythms during the task, but our reconstructed EEG is immune to these factors. We found that the detection of near-perceptual threshold targets embedded within these new white-noise sequences depended on the power of the ~10 Hz reconstructed EEG over parieto-occipital channels. Around the time of presentation, higher power led to poorer performance. Thus, fluctuations in alpha power, induced here by random luminance sequences, can directly influence perception: the relation between alpha power and perception is not a mere consequence of fluctuations in endogenous factors.

Keywords: EEG; IRF; alpha oscillations; power; visual perception.

Figure 1

Dual route between the ongoing oscillation power and visual perception. The relationship between alpha oscillations and visual perception could be a direct causal one, or could be mediated by an indirect influence of endogenous factors on both ongoing oscillations and target detection. To disentangle the relative contribution of both routes, the state of the ongoing oscillations can be directly manipulated, e.g., by rhythmic brain or visual stimulation (flicker), to test their causal influence on perception. Here, we propose to use the “White Noise Paradigm”.

Figure 2

Illustration of the White-Noise Paradigm. The impulse response function (IRF) to white-noise sequences can be extracted by cross-correlating the stimuli sequence with the recorded EEG (done in session 1). Here, an example IRF from one subject on the parieto-central channel. This IRF can, in turn, be used to reconstruct the brain activity (reconstructed EEG) to any new white-noise sequence by convolution (done for session 2). Figure originally published in eNeuro in Brüers and VanRullen (2017).

Figure 3

Mean power difference (in dB [unseen-seen]) averaged across subjects (N = 20) and channels in the ROI (purple dots on the topography). The green outline represents the significant cluster after cluster correction (see Methods section). The black dot represents the peak power difference (11.68 Hz and −62.5 ms).

Figure 4

Power dependent performance. (A) Mean percent change averaged across all 22 channels in the ROI (black) and 20 subjects for each of 5 power bins. The bars represent the standard error of the mean. The red line represents the linear fit. (B) The mean power dependent performance was computed for each channel (averaged across subjects) and the coefficient of the linear fit was taken to represent the modulation of performance. The largest effects are found over the occipital channels. Shaded areas represent channels outside of the ROI.