Activities and Seminars

Roger Ratcliff, Ohio State University
Date: Jul 05, 2011

What: Prof. Roger Ratcliff will give two short talks.

What: Prof. Roger Ratcliff will give two short talks.

When: Tuesday, July 5th. Time: 10:15am

Who:Prof. Roger Ratcliff, Ohio State University

Where: BCBL, Paseo Mikeletegi 69, Floor 2.


Talk one. “Modeling Confidence and Response Time” Summary: I describe a model for confidence judgments in perception and memory that deals with response confidence and response time distributions. The model assumes a distributed representation of memory strength and the areas between confidence criteria drive diffusion processes, one process for each confidence category. The new model updates an earlier model (Ratcliff & Starns, 2009, Psychological Review) with a new decision mechanism. The model is fit to recognition memory data including quantiles of RT distributions and ROC functions. The model fits data from individual subjects and accounts for puzzling nonlinear z-ROC functions.

Talk two. “A Diffusion Model for Simple Reaction Time” One of the simplest cognitive tasks is the simple reaction time (RT) one-choice task. This kind of task is used in a number of domains including motor vehicle driving and assessment of the cognitive/behavioral conseqeunces of sleep deprivation. In implementations of the task, a stimulus is presented and the subject has to respond when they detect the stimulus. We present a model for one-choice tasks that uses a one boundary diffusion process to represent the accumulation of stimulus information. When the accumulated evidence reaches a decision criterion, a response is initiated. This model is capable of fitting both short-tailed and long-tailed RT distributions, something that has eluded prior modeling. The model assumes that the rate of evidence accumulation varies from trial to trial as in previous two-choice diffusion models. We present fits of the model to data from two one-choice tasks, a brightness detection task and the psychomotor vigilance test (PVT), a task used in assessing the clinical and behavioral effects of sleep deprivation. For the PVT, the model accounts for lapses in performance under sleep deprivation and accounts for the change in the shape of RT distributions going from no deprivation to deprivation with only evidence accumulation rate changing. The model also reveals a relationship between how alertness (independently derived) and evidence accumulation rates change over hours of wakefulness.