Topic: drift diffusion model

Background and Objectives. Predictive coding theory proposes that perceptual experience arises from the integrations between subjective (e.g., prior) and objective reality (e.g., visual input). The purpose of the present work was to map the behavioural and electrophysiological mechanisms behind the integration of prior knowledge into human perceptual decision-making. Methods. We employed computational (signal detection theory, drift diffusion model) and electrophysiological (time-frequency decomposition) analyses to explore the impact that prior information has on perceptual decision. To this

A key function of the brain is to process noisy sensory stimuli to make fast and accurate decisions. Canonical studies manipulate average noise to study stimulus effects on decision parameters, but how processing of exact stochastic fluctuations impacts the decision outcome, has remained largely unexplored. We conducted behavioral experiments with stimuli following physical motion equations under nonequilibrium processes to define the stimulus dynamics in detail. In experiment I, participants (N=21) judged the motion direction of a visual stimulus with a given drift velocity (v) and diffusion