Time-varying perturbations can distinguish among integrate-to-threshold models for perceptual decision making in reaction time tasks.
Several integrate-to-threshold models with differing temporal integration mechanisms have been proposed to describe the accumulation of sensory evidence to a prescribed level prior to motor response in perceptual decision-making tasks. An experiment and simulation studies have shown that the introduction of time-varying perturbations during integration may distinguish among some of these models. Here, we present computer simulations and mathematical proofs that provide more rigorous comparisons among one-dimensional stochastic differential equation models. Using two perturbation protocols and focusing on the resulting changes in the means and standard deviations of decision times, we show that for high signal-to-noise ratios, drift-diffusion models with constant and time-varying drift rates can be distinguished from Ornstein-Uhlenbeck processes, but not necessarily from each other. The protocols can also distinguish stable from unstable Ornstein-Uhlenbeck processes, and we show that a nonlinear integrator can be distinguished from these linear models by changes in standard deviations. The protocols can be implemented in behavioral experiments.
Zhou
Xiang
X
Program in Applied and Computational Mathematics, Princeton University, Princeton, NJ 08544, USA. xiangz@math.princeton.edu
Wong-Lin
Kongfatt
K
Philip
Holmes
H
D003657:Decision Making / Q000502:physiology*; D006801:Humans; D016014:Linear Models; D008960:Models, Psychological; D016571:Neural Networks, Computer; D009483:Neuropsychological Tests; D017711:Nonlinear Dynamics; D010465:Perception / Q000502:physiology*; D055656:Prescriptions; D011930:Reaction Time / Q000502:physiology*; D013997:Time Factors