Neural Mechanisms for Integrating Prior Knowledge and Likelihood in Value-Based Probabilistic Inference
Identifieur interne : 000706 ( Main/Exploration ); précédent : 000705; suivant : 000707Neural Mechanisms for Integrating Prior Knowledge and Likelihood in Value-Based Probabilistic Inference
Auteurs : Chih-Chung Ting ; Chia-Chen Yu [Taïwan] ; Laurence T. Maloney [États-Unis] ; Shih-Wei Wu [Taïwan, États-Unis]Source :
- The Journal of Neuroscience [ 0270-6474 ] ; 2015.
Abstract
In Bayesian decision theory, knowledge about the probabilities of possible outcomes is captured by a prior distribution and a likelihood function. The prior reflects past knowledge and the likelihood summarizes current sensory information. The two combined (integrated) form a posterior distribution that allows estimation of the probability of different possible outcomes. In this study, we investigated the neural mechanisms underlying Bayesian integration using a novel lottery decision task in which both prior knowledge and likelihood information about reward probability were systematically manipulated on a trial-by-trial basis. Consistent with Bayesian integration, as sample size increased, subjects tended to weigh likelihood information more compared with prior information. Using fMRI in humans, we found that the medial prefrontal cortex (mPFC) correlated with the mean of the posterior distribution, a statistic that reflects the integration of prior knowledge and likelihood of reward probability. Subsequent analysis revealed that both prior and likelihood information were represented in mPFC and that the neural representations of prior and likelihood in mPFC reflected changes in the behaviorally estimated weights assigned to these different sources of information in response to changes in the environment. Together, these results establish the role of mPFC in prior-likelihood integration and highlight its involvement in representing and integrating these distinct sources of information.
Url:
DOI: 10.1523/JNEUROSCI.3161-14.2015
PubMed: 25632152
PubMed Central: 4308614
Affiliations:
Links toward previous steps (curation, corpus...)
- to stream Pmc, to step Corpus: 001464
- to stream Pmc, to step Curation: 001464
- to stream Pmc, to step Checkpoint: 000436
- to stream Ncbi, to step Merge: 003659
- to stream Ncbi, to step Curation: 003659
- to stream Ncbi, to step Checkpoint: 003659
- to stream Main, to step Merge: 000706
- to stream Main, to step Curation: 000706
Le document en format XML
<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Neural Mechanisms for Integrating Prior Knowledge and Likelihood in Value-Based Probabilistic Inference</title>
<author><name sortKey="Ting, Chih Chung" sort="Ting, Chih Chung" uniqKey="Ting C" first="Chih-Chung" last="Ting">Chih-Chung Ting</name>
<affiliation><nlm:aff wicri:cut=" and" id="aff1">Institute of Neuroscience</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Yu, Chia Chen" sort="Yu, Chia Chen" uniqKey="Yu C" first="Chia-Chen" last="Yu">Chia-Chen Yu</name>
<affiliation wicri:level="1"><nlm:aff wicri:cut=", and" id="aff3">School of Medicine, Taipei Medical University, Taipei, 110 Taiwan</nlm:aff>
<country xml:lang="fr">Taïwan</country>
<wicri:regionArea>School of Medicine, Taipei Medical University, Taipei</wicri:regionArea>
<wicri:noRegion>Taipei</wicri:noRegion>
</affiliation>
</author>
<author><name sortKey="Maloney, Laurence T" sort="Maloney, Laurence T" uniqKey="Maloney L" first="Laurence T." last="Maloney">Laurence T. Maloney</name>
<affiliation><nlm:aff id="aff4">Department of Psychology,</nlm:aff>
</affiliation>
<affiliation><nlm:aff wicri:cut=", and" id="aff5">Center for Neural Science</nlm:aff>
</affiliation>
<affiliation wicri:level="2"><nlm:aff id="aff6">Institute for the Interdisciplinary Study of Decision Making, New York University, New York, New York 10003</nlm:aff>
<country xml:lang="fr">États-Unis</country>
<placeName><region type="state">État de New York</region>
</placeName>
<wicri:cityArea>Institute for the Interdisciplinary Study of Decision Making, New York University, New York</wicri:cityArea>
</affiliation>
</author>
<author><name sortKey="Wu, Shih Wei" sort="Wu, Shih Wei" uniqKey="Wu S" first="Shih-Wei" last="Wu">Shih-Wei Wu</name>
<affiliation><nlm:aff wicri:cut=" and" id="aff1">Institute of Neuroscience</nlm:aff>
</affiliation>
<affiliation wicri:level="1"><nlm:aff id="aff2">Brain Research Center, National Yang-Ming University, Taipei, 112 Taiwan,</nlm:aff>
<country xml:lang="fr">Taïwan</country>
<wicri:regionArea>Brain Research Center, National Yang-Ming University, Taipei</wicri:regionArea>
<wicri:noRegion>Taipei</wicri:noRegion>
</affiliation>
<affiliation wicri:level="2"><nlm:aff id="aff6">Institute for the Interdisciplinary Study of Decision Making, New York University, New York, New York 10003</nlm:aff>
<country xml:lang="fr">États-Unis</country>
<placeName><region type="state">État de New York</region>
</placeName>
<wicri:cityArea>Institute for the Interdisciplinary Study of Decision Making, New York University, New York</wicri:cityArea>
</affiliation>
</author>
</titleStmt>
<publicationStmt><idno type="wicri:source">PMC</idno>
<idno type="pmid">25632152</idno>
<idno type="pmc">4308614</idno>
<idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4308614</idno>
<idno type="RBID">PMC:4308614</idno>
<idno type="doi">10.1523/JNEUROSCI.3161-14.2015</idno>
<date when="2015">2015</date>
<idno type="wicri:Area/Pmc/Corpus">001464</idno>
<idno type="wicri:Area/Pmc/Curation">001464</idno>
<idno type="wicri:Area/Pmc/Checkpoint">000436</idno>
<idno type="wicri:Area/Ncbi/Merge">003659</idno>
<idno type="wicri:Area/Ncbi/Curation">003659</idno>
<idno type="wicri:Area/Ncbi/Checkpoint">003659</idno>
<idno type="wicri:doubleKey">0270-6474:2015:Ting C:neural:mechanisms:for</idno>
<idno type="wicri:Area/Main/Merge">000706</idno>
<idno type="wicri:Area/Main/Curation">000706</idno>
<idno type="wicri:Area/Main/Exploration">000706</idno>
</publicationStmt>
<sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Neural Mechanisms for Integrating Prior Knowledge and Likelihood in Value-Based Probabilistic Inference</title>
<author><name sortKey="Ting, Chih Chung" sort="Ting, Chih Chung" uniqKey="Ting C" first="Chih-Chung" last="Ting">Chih-Chung Ting</name>
<affiliation><nlm:aff wicri:cut=" and" id="aff1">Institute of Neuroscience</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Yu, Chia Chen" sort="Yu, Chia Chen" uniqKey="Yu C" first="Chia-Chen" last="Yu">Chia-Chen Yu</name>
<affiliation wicri:level="1"><nlm:aff wicri:cut=", and" id="aff3">School of Medicine, Taipei Medical University, Taipei, 110 Taiwan</nlm:aff>
<country xml:lang="fr">Taïwan</country>
<wicri:regionArea>School of Medicine, Taipei Medical University, Taipei</wicri:regionArea>
<wicri:noRegion>Taipei</wicri:noRegion>
</affiliation>
</author>
<author><name sortKey="Maloney, Laurence T" sort="Maloney, Laurence T" uniqKey="Maloney L" first="Laurence T." last="Maloney">Laurence T. Maloney</name>
<affiliation><nlm:aff id="aff4">Department of Psychology,</nlm:aff>
</affiliation>
<affiliation><nlm:aff wicri:cut=", and" id="aff5">Center for Neural Science</nlm:aff>
</affiliation>
<affiliation wicri:level="2"><nlm:aff id="aff6">Institute for the Interdisciplinary Study of Decision Making, New York University, New York, New York 10003</nlm:aff>
<country xml:lang="fr">États-Unis</country>
<placeName><region type="state">État de New York</region>
</placeName>
<wicri:cityArea>Institute for the Interdisciplinary Study of Decision Making, New York University, New York</wicri:cityArea>
</affiliation>
</author>
<author><name sortKey="Wu, Shih Wei" sort="Wu, Shih Wei" uniqKey="Wu S" first="Shih-Wei" last="Wu">Shih-Wei Wu</name>
<affiliation><nlm:aff wicri:cut=" and" id="aff1">Institute of Neuroscience</nlm:aff>
</affiliation>
<affiliation wicri:level="1"><nlm:aff id="aff2">Brain Research Center, National Yang-Ming University, Taipei, 112 Taiwan,</nlm:aff>
<country xml:lang="fr">Taïwan</country>
<wicri:regionArea>Brain Research Center, National Yang-Ming University, Taipei</wicri:regionArea>
<wicri:noRegion>Taipei</wicri:noRegion>
</affiliation>
<affiliation wicri:level="2"><nlm:aff id="aff6">Institute for the Interdisciplinary Study of Decision Making, New York University, New York, New York 10003</nlm:aff>
<country xml:lang="fr">États-Unis</country>
<placeName><region type="state">État de New York</region>
</placeName>
<wicri:cityArea>Institute for the Interdisciplinary Study of Decision Making, New York University, New York</wicri:cityArea>
</affiliation>
</author>
</analytic>
<series><title level="j">The Journal of Neuroscience</title>
<idno type="ISSN">0270-6474</idno>
<idno type="eISSN">1529-2401</idno>
<imprint><date when="2015">2015</date>
</imprint>
</series>
</biblStruct>
</sourceDesc>
</fileDesc>
<profileDesc><textClass></textClass>
</profileDesc>
</teiHeader>
<front><div type="abstract" xml:lang="en"><p>In Bayesian decision theory, knowledge about the probabilities of possible outcomes is captured by a prior distribution and a likelihood function. The prior reflects past knowledge and the likelihood summarizes current sensory information. The two combined (integrated) form a posterior distribution that allows estimation of the probability of different possible outcomes. In this study, we investigated the neural mechanisms underlying Bayesian integration using a novel lottery decision task in which both prior knowledge and likelihood information about reward probability were systematically manipulated on a trial-by-trial basis. Consistent with Bayesian integration, as sample size increased, subjects tended to weigh likelihood information more compared with prior information. Using fMRI in humans, we found that the medial prefrontal cortex (mPFC) correlated with the mean of the posterior distribution, a statistic that reflects the integration of prior knowledge and likelihood of reward probability. Subsequent analysis revealed that both prior and likelihood information were represented in mPFC and that the neural representations of prior and likelihood in mPFC reflected changes in the behaviorally estimated weights assigned to these different sources of information in response to changes in the environment. Together, these results establish the role of mPFC in prior-likelihood integration and highlight its involvement in representing and integrating these distinct sources of information.</p>
</div>
</front>
</TEI>
<affiliations><list><country><li>Taïwan</li>
<li>États-Unis</li>
</country>
<region><li>État de New York</li>
</region>
</list>
<tree><noCountry><name sortKey="Ting, Chih Chung" sort="Ting, Chih Chung" uniqKey="Ting C" first="Chih-Chung" last="Ting">Chih-Chung Ting</name>
</noCountry>
<country name="Taïwan"><noRegion><name sortKey="Yu, Chia Chen" sort="Yu, Chia Chen" uniqKey="Yu C" first="Chia-Chen" last="Yu">Chia-Chen Yu</name>
</noRegion>
<name sortKey="Wu, Shih Wei" sort="Wu, Shih Wei" uniqKey="Wu S" first="Shih-Wei" last="Wu">Shih-Wei Wu</name>
</country>
<country name="États-Unis"><region name="État de New York"><name sortKey="Maloney, Laurence T" sort="Maloney, Laurence T" uniqKey="Maloney L" first="Laurence T." last="Maloney">Laurence T. Maloney</name>
</region>
<name sortKey="Wu, Shih Wei" sort="Wu, Shih Wei" uniqKey="Wu S" first="Shih-Wei" last="Wu">Shih-Wei Wu</name>
</country>
</tree>
</affiliations>
</record>
Pour manipuler ce document sous Unix (Dilib)
EXPLOR_STEP=$WICRI_ROOT/Ticri/CIDE/explor/HapticV1/Data/Main/Exploration
HfdSelect -h $EXPLOR_STEP/biblio.hfd -nk 000706 | SxmlIndent | more
Ou
HfdSelect -h $EXPLOR_AREA/Data/Main/Exploration/biblio.hfd -nk 000706 | SxmlIndent | more
Pour mettre un lien sur cette page dans le réseau Wicri
{{Explor lien |wiki= Ticri/CIDE |area= HapticV1 |flux= Main |étape= Exploration |type= RBID |clé= PMC:4308614 |texte= Neural Mechanisms for Integrating Prior Knowledge and Likelihood in Value-Based Probabilistic Inference }}
Pour générer des pages wiki
HfdIndexSelect -h $EXPLOR_AREA/Data/Main/Exploration/RBID.i -Sk "pubmed:25632152" \ | HfdSelect -Kh $EXPLOR_AREA/Data/Main/Exploration/biblio.hfd \ | NlmPubMed2Wicri -a HapticV1
This area was generated with Dilib version V0.6.23. |