The Brain Uses Reliability of Stimulus Information when Making Perceptual Decisions

TL;DR

This paper demonstrates that the brain incorporates stimulus reliability estimates into perceptual decision making, aligning with neurophysiological evidence and emphasizing rapid, stimulus-specific reliability assessments within the drift diffusion model framework.

Contribution

It shows that the drift diffusion model implicitly uses stimulus reliability and that only models accounting for stimulus-specific reliability match neurophysiological data.

Findings

Drift diffusion models rely on stimulus reliability estimates.

Models with stimulus-specific reliabilities align with neurophysiological findings.

The brain estimates stimulus reliability within a few hundred milliseconds.

Abstract

In simple perceptual decisions the brain has to identify a stimulus based on noisy sensory samples from the stimulus. Basic statistical considerations state that the reliability of the stimulus information, i.e., the amount of noise in the samples, should be taken into account when the decision is made. However, for perceptual decision making experiments it has been questioned whether the brain indeed uses the reliability for making decisions when confronted with unpredictable changes in stimulus reliability. We here show that even the basic drift diffusion model, which has frequently been used to explain experimental findings in perceptual decision making, implicitly relies on estimates of stimulus reliability. We then show that only those variants of the drift diffusion model which allow stimulus-specific reliabilities are consistent with neurophysiological findings. Our analysis suggests that the brain estimates the reliability of the stimulus on a short time scale of at most a few hundred milliseconds.