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An Accumulating Neural Signal Underlying Binocular Rivalry Dynamics.

Shaozhi Nie, Sucharit Katyal, Stephen A Engel

The Journal of neuroscience : the official journal of the Society for Neuroscience December 13, 2023 DOI: 10.1523/jneurosci.1325-23.2023 via PubMed

Summary

AI-generated from the abstract

During binocular rivalry, when each eye sees a different image, perception alternates unpredictably between them. Models propose that neural signals for each image change gradually until reaching a threshold that triggers a switch, but direct evidence was lacking. Measuring steady-state visual evoked potentials (SSVEPs) via EEG in 84 human participants (62 females, 22 males) viewing orthogonal gratings flickering at different frequencies, the amplitude of the suppressed stimulus's signal increased and the dominant stimulus's signal decreased throughout each percept. Longer percepts corresponded to more gradual changes in these signals. The findings match a model where perceptual transitions arise from accumulating noisy signals, providing the first physiological evidence for such threshold-crossing dynamics in human visual cortex.

Study at a glance

Characteristics Observational cohort Peer reviewed
Sample size 84
Population Human participants (62 females, 22 males)
Keywords Ssvep Binocular rivalry Bistable perception Drift-diffusion Human
Key finding SSVEP amplitudes for the suppressed stimulus increase and for the dominant stimulus decrease throughout a percept, with longer percepts characterized by more gradual changes, matching predictions of a drift-diffusion model.

Abstract

During binocular rivalry, conflicting images are presented one to each eye and perception alternates stochastically between them. Despite stable percepts between alternations, modeling suggests that neural signals representing the two images change gradually, and that the duration of stable percepts are determined by the time required for these signals to reach a threshold that triggers an alternation. However, direct physiological evidence for such signals has been lacking. Here, we identify a neural signal in the human visual cortex that shows these predicted properties. We measured steady-state visual evoked potentials (SSVEPs) in 84 human participants (62 females, 22 males) who were presented with orthogonal gratings, one to each eye, flickering at different frequencies. Participants indicated their percept while EEG data were collected. The time courses of the SSVEP amplitudes at the two frequencies were then compared across different percept durations, within participants. For all durations, the amplitude of signals corresponding to the suppressed stimulus increased and the amplitude corresponding to the dominant stimulus decreased throughout the percept. Critically, longer percepts were characterized by more gradual increases in the suppressed signal and more gradual decreases of the dominant signal. Changes in signals were similar and rapid at the end of all percepts, presumably reflecting perceptual transitions. These features of the SSVEP time courses are well predicted by a model in which perceptual transitions are produced by the accumulation of noisy signals. Identification of this signal underlying binocular rivalry should allow strong tests of neural models of rivalry, bistable perception, and neural suppression.SIGNIFICANCE STATEMENT During binocular rivalry, two conflicting images are presented to the two eyes and perception alternates between them, with switches occurring at seemingly random times. Rivalry is an important and longstanding model system in neuroscience, used for understanding neural suppression, intrinsic neural dynamics, and even the neural correlates of consciousness. All models of rivalry propose that it depends on gradually changing neural activity that on reaching some threshold triggers the perceptual switches. This manuscript reports the first physiological measurement of neural signals with that set of properties in human participants. The signals, measured with EEG in human observers, closely match the predictions of recent models of rivalry, and should pave the way for much future work.

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