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

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.