Friedrich, Johannes; Urbanczik, Robert; Senn, Walter (2010). Learning Spike-Based Population Codes by Reward and Population Feedback. Neural computation, 22(1698-1717), pp. 1698-1717. Cambridge, Mass.: MIT Press 10.1162/neco.2010.05-09-1010
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We investigate a recently proposed model for decision learning in a population of spiking neurons where synaptic plasticity is modulated by a population signal in addition to reward feedback. For the basic model, binary population decision making based on spike/no-spike coding, a detailed computational analysis is given about how learning performance depends on population size and task complexity. Next, we extend the basic model to n-ary decision making and show that it can also be used in conjunction with other population codes such as rate or even latency coding.
Item Type: |
Journal Article (Original Article) |
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Division/Institute: |
04 Faculty of Medicine > Pre-clinic Human Medicine > Institute of Physiology |
UniBE Contributor: |
Friedrich, Johannes, Urbanczik, Robert, Senn, Walter |
Subjects: |
600 Technology > 610 Medicine & health |
ISSN: |
0899-7667 |
Publisher: |
MIT Press |
Language: |
English |
Submitter: |
Factscience Import |
Date Deposited: |
04 Oct 2013 14:10 |
Last Modified: |
05 Dec 2022 14:00 |
Publisher DOI: |
10.1162/neco.2010.05-09-1010 |
PubMed ID: |
20235820 |
Web of Science ID: |
000278530200002 |
BORIS DOI: |
10.7892/boris.1258 |
URI: |
https://boris.unibe.ch/id/eprint/1258 (FactScience: 202453) |
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