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.

Download full-text PDF

Source
http://dx.doi.org/10.1037/0033-295X.114.2.376DOI Listing

Publication Analysis

Top Keywords

race model
8
network interacting
8
inhibitory control
4
control mind
4
mind brain
4
brain interactive
4
interactive race
4
model
4
model countermanding
4
countermanding saccades
4

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!