Cortico-striatal circuits and interval timing: coincidence detection of oscillatory processes.

Published

Journal Article (Review)

Humans and other animals demonstrate the ability to perceive and respond to temporally relevant information with characteristic behavioral properties. For example, the response time distributions in peak-interval timing tasks are well described by Gaussian functions, and superimpose when scaled by the criterion duration. This superimposition has been referred to as the scalar property and results from the fact that the standard deviation of a temporal estimate is proportional to the duration being timed. Various psychological models have been proposed to account for such responding. These models vary in their success in predicting the temporal control of behavior as well as in the neurobiological feasibility of the mechanisms they postulate. A review of the major interval timing models reveals that no current model is successful on both counts. The neurobiological properties of the basal ganglia, an area known to be necessary for interval timing and motor control, suggests that this set of structures act as a coincidence detector of cortical and thalamic input. The hypothesized functioning of the basal ganglia is similar to the mechanisms proposed in the beat frequency timing model [R.C. Miall, Neural Computation 1 (1989) 359-371], leading to a reevaluation of its capabilities in terms of behavioral prediction. By implementing a probabilistic firing rule, a dynamic response threshold, and adding variance to a number of its components, simulations of the striatal beat frequency model were able to produce output that is functionally equivalent to the expected behavioral response form of peak-interval timing procedures.

Full Text

Duke Authors

Cited Authors

  • Matell, MS; Meck, WH

Published Date

  • October 2004

Published In

Volume / Issue

  • 21 / 2

Start / End Page

  • 139 - 170

PubMed ID

  • 15464348

Pubmed Central ID

  • 15464348

International Standard Serial Number (ISSN)

  • 0926-6410

Digital Object Identifier (DOI)

  • 10.1016/j.cogbrainres.2004.06.012

Language

  • eng