Hostname: page-component-78c5997874-s2hrs Total loading time: 0 Render date: 2024-11-14T18:53:27.124Z Has data issue: false hasContentIssue false
  • English
  • Français

Neural computation, architecture, and evolution

Published online by Cambridge University Press:  01 March 1997

Paul Skokowski
Paul Skokowski
Affiliation:
McDonnell-Pew Centre for Cognitive Neuroscience, Oxford University, Oxford, OX1 3UD, Englandpaul.skokowski@psy.ox.ac.uk
Get access Rights & Permissions [Opens in a new window]

Abstract

Biological neural computation relies a great deal on architecture, which constrains the types of content that can be processed by distinct modules in the brain. Though artificial neural networks are useful tools and give insight, they cannot be relied upon yet to give definitive answers to problems in cognition. Knowledge re-use may be driven more by architectural inheritance than by epistemological drives.

Type
Open Peer Commentary
Information
Behavioral and Brain Sciences , Volume 20 , Issue 1 , March 1997 , pp. 80
Copyright
© 1997 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.)