Prospective decision making for randomly moving visual stimuli

Humans persist in their attempts to predict the future in spite of the fact that natural events often involve a fundamental element of uncertainty. The present study explored computational mechanisms underlying biases in prospective decision making by using a simple psychophysical task. Observers viewed a randomly moving Gabor target for T sec and anticipated its future position ΔT sec following stimulus offset. Applying reverse correlation analysis, we found that observer decisions focused heavily on the last part of target velocity and especially on velocity information following the last several direction reversals. If target random motion explicitly contained an additional linear trend, observers tended to utilize information of the linear trend as well. These behavioral data are well explained by a leaky-integrator model of perceptual decision making based on evidence accumulation with adaptive gain control. The results raise the possibility that prospective decision making toward future events follows principles similar to those involved in retrospective decision making toward past events.