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Selective integration during sequential sampling in posterior neural signals

Abstract:

Decisions are typically made after integrating information about multiple attributes of alternatives in a choice set. Where observers are obliged to consider attributes in turn, a computational framework known as “selective integration” can capture salient biases in human choices. The model proposes that successive attributes compete for processing resources and integration is biased towards the alternative with the locally preferred attribute. Quantitative analysis shows that this model, alt...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1093/cercor/bhaa039

Authors


More by this author
Institution:
University of Oxford
Division:
MSD
Department:
Experimental Psychology
Role:
Author
ORCID:
0000-0003-0656-538X
More by this author
Institution:
University of Oxford
Division:
MSD
Department:
Experimental Psychology
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MSD
Department:
Experimental Psychology
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MSD
Department:
Experimental Psychology
Role:
Author
Publisher:
Oxford University Press
Journal:
Cerebral Cortex More from this journal
Volume:
30
Issue:
8
Pages:
4454-4464
Publication date:
2020-03-07
Acceptance date:
2020-01-30
DOI:
EISSN:
1460-2199
ISSN:
1047-3211
Language:
English
Keywords:
Pubs id:
1092412
Local pid:
pubs:1092412
Deposit date:
2020-03-11

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