Workshop: Drift Diffusion Models (Part II)

Yunshu Fan, from the Ding and Gold Labs, is presenting a 2-part workshop to introduce the drift-diffusion model (DDM), a model that is commonly used in modeling decision behavior. The goals are to familiarize participants with the model enough to (1) start to think about whether and when the model can be usedful, and (2) feel less confused when reading about it in literature and talks.

To make the learning process more interactive and relevant please bring your computer to the sessions, as there will be code provided to play with the model.

This second session will cover:

• Optimality analyses: What you can do once you fit behavior to the model

• DDM's relationship to signal detection theory, Bayesian inference and sequential probability ratio test

• Neural correlates of DDM components

• Evidence accumulation vs non-accumulation models.