Learning Spike-Based Population Codes by Reward and Population Feedback

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)

Division/Institute:

04 Faculty of Medicine > Pre-clinic Human Medicine > Institute of Physiology

UniBE Contributor:

Friedrich, Johannes; Urbanczik, Robert and 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:

20 Jun 2016 09:53

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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