Perceptual learning shapes multisensory causal inference via two distinct mechanisms

29Citations
Citations of this article
99Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

To accurately represent the environment, our brains must integrate sensory signals from a common source while segregating those from independent sources. A reasonable strategy for performing this task is to restrict integration to cues that coincide in space and time. However, because multisensory signals are subject to differential transmission and processing delays, the brain must retain a degree of tolerance for temporal discrepancies. Recent research suggests that the width of this 'temporal binding window' can be reduced through perceptual learning, however, little is known about the mechanisms underlying these experience-dependent effects. Here, in separate experiments, we measure the temporal and spatial binding windows of human participants before and after training on an audiovisual temporal discrimination task. We show that training leads to two distinct effects on multisensory integration in the form of (i) a specific narrowing of the temporal binding window that does not transfer to spatial binding and (ii) a general reduction in the magnitude of crossmodal interactions across all spatiotemporal disparities. These effects arise naturally from a Bayesian model of causal inference in which learning improves the precision of audiovisual timing estimation, whilst concomitantly decreasing the prior expectation that stimuli emanate from a common source.

Cite

CITATION STYLE

APA

McGovern, D. P., Roudaia, E., Newell, F. N., & Roach, N. W. (2016). Perceptual learning shapes multisensory causal inference via two distinct mechanisms. Scientific Reports, 6. https://doi.org/10.1038/srep24673

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free