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dc.contributor.author
Heng, Joseph A.
dc.contributor.author
Woodford, Michael
dc.contributor.author
Polania, Rafael
dc.date.accessioned
2020-09-24T11:17:04Z
dc.date.available
2020-09-24T06:18:39Z
dc.date.available
2020-09-24T11:17:04Z
dc.date.issued
2020
dc.identifier.other
10.7554/eLife.54962
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/442196
dc.identifier.doi
10.3929/ethz-b-000442196
dc.description.abstract
Human decisions are based on finite information, which makes them inherently imprecise. But what determines the degree of such imprecision? Here, we develop an efficient coding framework for higher-level cognitive processes in which information is represented by a finite number of discrete samples. We characterize the sampling process that maximizes perceptual accuracy or fitness under the often-adopted assumption that full adaptation to an environmental distribution is possible, and show how the optimal process differs when detailed information about the current contextual distribution is costly. We tested this theory on a numerosity discrimination task, and found that humans efficiently adapt to contextual distributions, but in the way predicted by the model in which people must economize on environmental information. Thus, understanding decision behavior requires that we account for biological restrictions on information coding, challenging the often-adopted assumption of precise prior knowledge in higher-level decision systems.
en_US
dc.format
application/pdf
en_US
dc.language.iso
en
en_US
dc.publisher
eLife Sciences Publications
en_US
dc.rights.uri
http://creativecommons.org/licenses/by/4.0/
dc.title
Efficient sampling and noisy decisions
en_US
dc.type
Journal Article
dc.rights.license
Creative Commons Attribution 4.0 International
dc.date.published
2020-09-15
ethz.journal.title
eLife
ethz.journal.volume
9
en_US
ethz.pages.start
e54962
en_US
ethz.size
49 p.
en_US
ethz.version.deposit
publishedVersion
en_US
ethz.identifier.wos
ethz.identifier.scopus
ethz.publication.place
Cambridge
en_US
ethz.publication.status
published
en_US
ethz.date.deposited
2020-09-24T06:19:03Z
ethz.source
SCOPUS
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2020-09-24T11:17:15Z
ethz.rosetta.lastUpdated
2020-09-24T11:17:15Z
ethz.rosetta.exportRequired
true
ethz.rosetta.versionExported
true
ethz.COinS
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