A deep active inference model of the rubber-hand illusion

TL;DR

This paper presents a deep active inference model that simulates the rubber-hand illusion, reproducing human-like perceptual shifts and involuntary forces in a virtual environment, advancing understanding of sensorimotor integration.

Contribution

The study introduces a novel deep active inference model capable of replicating human responses to the rubber-hand illusion, including perceptual and force patterns.

Findings

Model reproduces human-like perceptual shifts.

Model generates involuntary forces similar to humans.

Demonstrates effective handling of high-dimensional visual inputs.

Abstract

Understanding how perception and action deal with sensorimotor conflicts, such as the rubber-hand illusion (RHI), is essential to understand how the body adapts to uncertain situations. Recent results in humans have shown that the RHI not only produces a change in the perceived arm location, but also causes involuntary forces. Here, we describe a deep active inference agent in a virtual environment, which we subjected to the RHI, that is able to account for these results. We show that our model, which deals with visual high-dimensional inputs, produces similar perceptual and force patterns to those found in humans.