Abstract
Alpha rhythms (∼10Hz) in the human brain are classically associated with idling activities, being predominantly observed during quiet restfulness with closed eyes. However, recent studies demonstrated that alpha (∼10Hz) rhythms can directly relate to visual stimulation, resulting in oscillations, which can last for as long as one second. This alpha reverberation, dubbed perceptual echoes (PE), suggests that the visual system actively samples and processes visual information within the alpha-band frequency. Although PE have been linked to various visual functions, their underlying mechanisms and functional role are not completely understood. In this study, we investigated the relationship between conscious perception and the generation and the amplitude of PE. Specifically, we displayed two coloured Gabor patches with different orientations on opposite sides of the screen, and using a set of dichoptic mirrors, we induced a binocular rivalry between the two stimuli. We asked participants to continuously report which one of two Gabor patches they consciously perceived, while recording their EEG signals. Importantly, the luminance of each patch fluctuated randomly over time, generating random sequences from which we estimated two impulse-response functions (IRFs) reflecting the PE generated by the perceived (dominant) and non-perceived (suppressed) stimulus, respectively. We found that the alpha power of the PE generated by the consciously perceived stimulus was comparable with that of the PE generated during monocular vision (control condition) and higher than the PE induced by the suppressed stimulus. Moreover, confirming previous findings, we found that all PEs propagated as a travelling wave from posterior to frontal brain regions, irrespective of conscious perception. All in all our results demonstrate a correlation between conscious perception and PE, suggesting that the synchronization of neural activity plays an important role in visual sampling and conscious perception.
Tagged MEG measures binocular rivalry in a cortical network that predicts alternation rate
