Sequential sampling models assume that people make speeded decisions by gradually
accumulating noisy information until a threshold of evidence is reached. In cognitive …

There is growing interest in diffusion models to represent the cognitive and neural processes
of speeded decision making. Sequential-sampling models like the diffusion model have a …

Most current sequential sampling models have random between-trial variability in their
parameters. These sources of variability make the models more complex in order to fit …

The diffusion decision model allows detailed explanations of behavior in two-choice
discrimination tasks. In this article, the model is reviewed to show how it translates …

Behavioral data obtained with perceptual decision making experiments are typically
analyzed with the drift-diffusion model. This parsimonious model accumulates noisy pieces …

The marriage of cognitive neurophysiology and mathematical psychology to understand
decision-making has been exceptionally productive. This interdisciplinary area is based on …

Abstract Stochastic diffusion models (Ratcliff, 1978) can be used to analyze response time
data from binary decision tasks. They provide detailed information about cognitive …

Reinforcement learning models of error-driven learning and sequential-sampling models of
decision making have provided significant insight into the neural basis of a variety of …

Diffusion models for simple two-choice decision making have achieved prominence in
psychology and neuroscience. The standard model views decision making as a process in …

Decision making often involves the accumulation of information over time, but acquiring
information typically comes at a cost. Little is known about the cost incurred by animals and …