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http://hdl.handle.net/1893/20493| Appears in Collections: | Psychology Book Chapters and Sections |
| Peer Review Status: | Refereed |
| Title: | How do neural systems use probabilistic inference that is context-sensitive to create and preserve organized complexity? |
| Author(s): | Phillips, William |
| Contact Email: | w.a.phillips@stir.ac.uk |
| Editor(s): | Simeonov, PL Smith, LS Ehresmann, AC |
| Citation: | Phillips W (2012) How do neural systems use probabilistic inference that is context-sensitive to create and preserve organized complexity?. In: Simeonov P, Smith L & Ehresmann A (eds.) Integral Biomathics: Tracing the Road to Reality. Berlin Heidelberg: Springer, pp. 63-69. http://link.springer.com/chapter/10.1007%2F978-3-642-28111-2_7; https://doi.org/10.1007/978-3-642-28111-2_7 |
| Keywords: | self-organization complexity probabilistic inference induction neural systems Coherent Infomax context-sensitivity |
| Issue Date: | 2012 |
| Date Deposited: | 19-Jun-2014 |
| Abstract: | This paper claims that biological systems will more effectively create organized complexity if they use probabilistic inference that is context-sensitive. It argues that neural systems combine local reliability with flexible, holistic, context-sensitivity, and a theory, Coherent Infomax, showing, in principle, how this can be done is outlined. Ways in which that theory needs further development are noted, and its relation to Friston’s theory of free energy reduction is discussed. |
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| URL: | http://link.springer.com/chapter/10.1007%2F978-3-642-28111-2_7 |
| DOI Link: | 10.1007/978-3-642-28111-2_7 |
| Licence URL(s): | http://www.rioxx.net/licenses/under-embargo-all-rights-reserved |
| File | Description | Size | Format | |
|---|---|---|---|---|
| Phillips ACIB2012.pdf | Fulltext - Accepted Version | 165.01 kB | Adobe PDF | Under Embargo until 3000-12-01 Request a copy |
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