Schyns, P.G. and Gosselin, F. and Smith, Marie L. (2008) Information processing algorithms in the brain. Trends in Cognitive Sciences 13 (1), pp. 20-26. ISSN 1364-6613.
Abstract
If the brain is a machine that processes information, then its cognitive activity can be interpreted as a set of information processing states linking stimulus to response (i.e. as a mechanism or an algorithm). The cornerstone of this research agenda is the existence of a method to translate the measurable states of brain activity into the information processing states of a cognitive theory. Here, we contend that reverse correlation methods can provide this translation and we frame the transitions between information processing states in the context of automata theory. We illustrate, using examples from visual cognition, how this novel framework can be applied to understand the information processing algorithms of the brain in cognitive neuroscience.
Metadata
| Item Type: | Article |
|---|---|
| School: | Birkbeck Faculties and Schools > Faculty of Science > School of Psychological Sciences |
| Research Centres and Institutes: | Brain and Cognitive Development, Centre for (CBCD) |
| Depositing User: | Administrator |
| Date Deposited: | 29 May 2013 16:09 |
| Last Modified: | 02 Aug 2023 17:04 |
| URI: | https://eprints.bbk.ac.uk/id/eprint/7059 |
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