A simulator for the analysis of neuronal ensemble activity: Application to reaching tasks

Published

Journal Article

A biologically based, multi-cortical computational model was developed to investigate how ensembles of neurons learn to execute a three-dimensional reaching task. The model produces outputs of spike trains that can be analyzed using a variety of multivariate analysis tools. Simulations show that after learning, the model neurons exhibit broad directional tuning that depend on the defined muscle directions of the simulated arm, and that these neurons form functional clusters within cortical areas. The utility of the model is demonstrated by testing arm movement prediction strategies using ensemble activity. © 2002 Published by Elsevier Science B.V.

Full Text

Duke Authors

Cited Authors

  • Hugh, GS; Laubach, M; Nicolelis, MAL; Henriquez, CS

Published Date

  • July 27, 2002

Published In

Volume / Issue

  • 44-46 /

Start / End Page

  • 847 - 854

International Standard Serial Number (ISSN)

  • 0925-2312

Digital Object Identifier (DOI)

  • 10.1016/S0925-2312(02)00482-4

Citation Source

  • Scopus