Hostname: page-component-cd9895bd7-dzt6s Total loading time: 0 Render date: 2024-12-22T14:25:12.247Z Has data issue: false hasContentIssue false
  • English
  • Français

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. [email protected]@[email protected]://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. [email protected]@[email protected]://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. [email protected]@[email protected]://vinelab.na.infn.it
Get access Rights & Permissions [Opens in a new window]

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.

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

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

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