MEG Reveals Distinct Dorsal and Ventral Streams for Binocular Rivalry Dominance and Suppression

Abstract

Binocular rivalry is an example of bistable visual perception extensively examined in neuroimaging. Magneto-encephalography (MEG) can track brain responses to phasic visual stimulations of pre-determined frequency and phase to advance our understanding of perceptual dominance and suppression in binocular rivalry. We used left and right eye stimuli (red and green orthogonal gratings) that flickered at two tagging frequencies (5 and 7.5 Hz) to track their respective oscillatory cortical evoked responses. We computed time-resolved measures of coherence to track the brain responses phase-locked with stimulus frequencies, and with respect to the participants’ indications of alternations of visual rivalry they experienced. Using Brainstorm software, we compared the brain maps obtained to those from a non-rivalrous control replay condition that used physically changing stimuli to mimic rivalry. We found stronger coherence within a posterior cortical network of visual areas during rivalry dominance compared to rivalry suppression and replay control. This network extended beyond the primary visual cortex (V1) to several retinotopic visual areas. In addition, network coherence with dominant percepts in V1 peaked at least 50 ms prior to the suppressed percept nadir; consistent with Wilson’s (2003) escape theory of alternations. Moreover, individual alternation rates were correlated with the rate of change (slope) in dominant evoked peaks, but not for the slope of response to suppressed percepts. This further supports the (escape) theory that a perceptual switch occurs when the suppressed-to-dominant tag increases sufficiently. Finally, an effective connectivity measure (Phase Transfer Entropy) revealed that dominant or suppressed percepts were preferentially expressed in dorsal or ventral stream streams, respectively. We thus demonstrate that binocular rivalry dominance and suppression engage distinct mechanisms and brain networks. These findings advance neural models of rivalry and may relate to more general aspects of selection and suppression in natural vision.