Ganguly, Kanuresh and Torres, Elizabeth B. and José, Jorge V. and Carmena, Jose M. (2008) From multiple neural cortical networks to motor mechanical behavior: the importance of inherent learning over separable space-time length scales. BMC Neuroscience, 9 (Supple). P70. ISSN 1471-2202. doi:10.1186/1471-2202-9-S1-P70. https://resolver.caltech.edu/CaltechAUTHORS:GANbmcns08
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Abstract
We find that (1) several stable spatio-temporal representations co-exist in a given cell which permits identification and selection of different motor programs to operate the external device, and (2) these multiple representations can be extracted from the multi-electrode neuron spike patterns reflecting various spatial re-parameterizations compatible with the ones imposed by the external mechanical device. A neural theoretical formulation in terms of a Hodgkin-Huxley excitatory and inhibitory neural ring network is used [5] to model multi-electrode spiking statistics, explicitly considering the separation of different motor dynamical times.
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| Additional Information: | © 2008 Ganguly et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. This article is part of the supplement: Seventeenth Annual Computational Neuroscience Meeting: CNS*2008. Portland, OR, USA. 19–24 July 2008. BMC Neuroscience 9 (Supplement 1) http://www.biomedcentral.com/bmcneurosci/9?issue=S1 | |||||||||
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| Issue or Number: | Supple | |||||||||
| DOI: | 10.1186/1471-2202-9-S1-P70 | |||||||||
| Record Number: | CaltechAUTHORS:GANbmcns08 | |||||||||
| Persistent URL: | https://resolver.caltech.edu/CaltechAUTHORS:GANbmcns08 | |||||||||
| Official Citation: | BMC Neuroscience 2008, 9(Suppl 1):P70 doi:10.1186/1471-2202-9-S1-P70 | |||||||||
| Usage Policy: | This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. | |||||||||
| ID Code: | 11174 | |||||||||
| Collection: | CaltechAUTHORS | |||||||||
| Deposited By: | Archive Administrator | |||||||||
| Deposited On: | 21 Jul 2008 23:56 | |||||||||
| Last Modified: | 08 Nov 2021 21:33 |
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