Hostname: page-component-cd9895bd7-lnqnp Total loading time: 0 Render date: 2024-12-27T08:10:11.669Z Has data issue: false hasContentIssue false
  • English
  • Français

population lateralization arises in simulated evolution of non-interacting neural networks

Published online by Cambridge University Press:  26 September 2005

james a. reggia  and
alexander grushin
james a. reggia
Affiliation:
department of computer science, university of maryland, college park, md 20742 [email protected]@cs.umd.edu http://www.cs.umd.edu/~reggia/ http://www.cs.umd.edu/~agrushin/
alexander grushin
Affiliation:
department of computer science, university of maryland, college park, md 20742 [email protected]@cs.umd.edu http://www.cs.umd.edu/~reggia/ http://www.cs.umd.edu/~agrushin/
Get access Rights & Permissions [Opens in a new window]

Abstract

recent computer simulations of evolving neural networks have shown that population-level behavioral asymmetries can arise without social interactions. although these models are quite limited at present, they support the hypothesis that social pressures can be sufficient but are not necessary for population lateralization to occur, and they provide a framework for further theoretical investigation of this issue.

Type
open peer commentary
Information
Behavioral and Brain Sciences , Volume 28 , Issue 4 , August 2005 , pp. 609 - 611
Copyright
2005 cambridge university press

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.)