Work

Divisive attenuation based on noisy sensorimotor predictions accounts for excess variability in self-touch

Year: 2025

Type: article

Abstract: We formulate a detailed computational account of sensory attenuation in force-matching tasks that disambiguates contributions of perceptual, memory, and prediction noise to isolate a pure measure of attenuation strength. Analysis of data from nearly 500 participants shows that attenuated sensations display increased trial-to-trial variability, consistent with incorporating additional noise inherent to motor prediction. These results support a divisive, rather than subtractive, reduction in the sensation of self-generated forces based on predicted reafference.

Source: Journal of Neurophysiology

DOI: 10.1152/jn.00055.2025

Authors: Nicola Valè, Ivan Tomić, Zahara Gironés, Daniel M. Wolpert, Konstantina Kilteni, Paul M. Bays