Abstract:
: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.
journal_name
Neural Computjournal_title
Neural computationauthors
Friedrich J,Urbanczik R,Senn Wdoi
10.1162/neco.2010.05-09-1010subject
Has Abstractpub_date
2010-07-01 00:00:00pages
1698-717issue
7eissn
0899-7667issn
1530-888Xjournal_volume
22pub_type
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