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How and over what timescales does neural reuse actually occur?

Published online by Cambridge University Press:  22 October 2010

Francesco Donnarumma ,
Roberto Prevete  and
Giuseppe Trautteur
Francesco Donnarumma
Affiliation:
Dipartimento di Scienze Fisiche, Università di Napoli Federico II, Complesso Universitario Monte Sant'Angelo, I-80126 Napoli, Italy. donnarumma@na.infn.it prevete@na.infn.it trau@na.infn.it http://vinelab.na.infn.it
Roberto Prevete
Affiliation:
Dipartimento di Scienze Fisiche, Università di Napoli Federico II, Complesso Universitario Monte Sant'Angelo, I-80126 Napoli, Italy. donnarumma@na.infn.it prevete@na.infn.it trau@na.infn.it http://vinelab.na.infn.it
Giuseppe Trautteur
Affiliation:
Dipartimento di Scienze Fisiche, Università di Napoli Federico II, Complesso Universitario Monte Sant'Angelo, I-80126 Napoli, Italy. donnarumma@na.infn.it prevete@na.infn.it trau@na.infn.it http://vinelab.na.infn.it
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Abstract

We isolate some critical aspects of the reuse notion in Anderson's massive redeployment hypothesis (MRH). We notice that the actual rearranging of local neural circuits at a timescale comparable with the reactivity timescale of the organism is left open. We propose the concept of programmable neural network as a solution.

Information

Type
Open Peer Commentary
Information
Behavioral and Brain Sciences , Volume 33 , Issue 4 , August 2010 , pp. 272 - 273
Copyright
Copyright © Cambridge University Press 2010

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References

Donnarumma, F. (2010) A model for programmability and virtuality in dynamical neural networks. Doctoral dissertation in Scienze Computazionali ed Informatiche (Computational and Information Sciences), Dipartimento di Matematica e Applicazioni “R. Caccioppoli,” Università di Napoli Federico II. Available at: http://people.na.infn.it/~donnarumma/files/donnarumma09model.pdf.Google Scholar
Donnarumma, F., Prevete, R. & Trautteur, G. (2007) Virtuality in neural dynamical systems. Poster presented at the International Conference on Morphological Computation, ECLT, Venice, Italy, March 26–28, 2007. Available at: http://vinelab.na.infn.it/research/pubs/donnarumma07virtuality.pdf.Google Scholar
Dunn, N. A., Lockery, S. R., Pierce-Shimomura, J. T. & Conery, J. S. (2004) A neural network model of chemotaxis predicts functions of synaptic connections in the nematode Caenorhabditis elegans . Journal of Computational Neuroscience. 17(2):137–47.CrossRefGoogle ScholarPubMed
Garzillo, C. & Trautteur, G. (2009) Computational virtuality in biological systems. Theoretical Computer Science 410:323–31.Google Scholar
Tamburrini, G. & Trautteur, G. (2007) A note on discreteness and virtuality in analog computing. Theoretical Computer Science 371:106–14.Google Scholar