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Control of entropy in neural models of environmental state

Abstract:

Humans and animals construct internal models of their environment in order to select appropriate courses of action. The representation of uncertainty about the current state of the environment is a key feature of these models that controls the rate of learning as well as directly affecting choice behaviour. To maintain flexibility, given that uncertainty naturally decreases over time, most theoretical inference models include a dedicated mechanism to drive up model uncertainty. Here we probe ...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.7554/eLife.39404

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Role:
Author
ORCID:
0000-0002-5817-4949
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Institution:
University of Oxford
Division:
MSD
Department:
Clinical Neurosciences
Role:
Author
ORCID:
0000-0003-0048-1177
Publisher:
eLife Sciences Publications Publisher's website
Journal:
eLife Journal website
Volume:
8
Publication date:
2019-02-28
Acceptance date:
2019-02-06
DOI:
EISSN:
2050-084X
ISSN:
2050-084X
Pmid:
30816090
Language:
English
Keywords:
Pubs id:
pubs:980910
UUID:
uuid:521e59c5-61d0-45b3-86c0-e7b5cb9d3345
Local pid:
pubs:980910
Deposit date:
2019-04-09

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