| Literature DB >> 17500631 |
Leanne Boucher1, Thomas J Palmeri, Gordon D Logan, Jeffrey D Schall.
Abstract
The stop-signal task has been used to study normal cognitive control and clinical dysfunction. Its utility is derived from a race model that accounts for performance and provides an estimate of the time it takes to stop a movement. This model posits a race between go and stop processes with stochastically independent finish times. However, neurophysiological studies demonstrate that the neural correlates of the go and stop processes produce movements through a network of interacting neurons. The juxtaposition of the computational model with the neural data exposes a paradox-how can a network of interacting units produce behavior that appears to be the outcome of an independent race? The authors report how a simple, competitive network can solve this paradox and provide an account of what is measured by stop-signal reaction time. (c) 2007 APA, all rights reserved.Mesh:
Year: 2007 PMID: 17500631 DOI: 10.1037/0033-295X.114.2.376
Source DB: PubMed Journal: Psychol Rev ISSN: 0033-295X Impact factor: 8.934