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 de ned 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
%0 Journal Article
%1 Hugh2002
%A ?,
%D 2002
%J Neurocomputing
%K areas, associative, computational control, cortex cortex, cortical model, motor premotor, somatosensory, visual
%P 847?854
%T A simulator for the analysis of neuronal ensemble activity: application
to reaching tasks
%V 44?46
%X 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 de ned 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
@article{Hugh2002,
abstract = {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 de ned 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},
added-at = {2009-06-26T15:25:19.000+0200},
author = {?},
biburl = {https://www.bibsonomy.org/bibtex/24669a0e38f0fd0e6cf05d340cab317c0/butz},
description = {diverse cognitive systems bib},
interhash = {a5ac5481071c0d624bc379f9fd165ad3},
intrahash = {4669a0e38f0fd0e6cf05d340cab317c0},
journal = {Neurocomputing},
keywords = {areas, associative, computational control, cortex cortex, cortical model, motor premotor, somatosensory, visual},
owner = {martin},
pages = {847?854},
timestamp = {2009-06-26T15:25:35.000+0200},
title = {A simulator for the analysis of neuronal ensemble activity: application
to reaching tasks},
volume = {44?46},
year = 2002
}