Owl's behavior and neural representation predicted by Bayesian inference View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2011-08

AUTHORS

Brian J Fischer, José Luis Peña

ABSTRACT

The owl captures prey using sound localization. In the classical model, the owl infers sound direction from the position of greatest activity in a brain map of auditory space. However, this model fails to describe the actual behavior. Although owls accurately localize sources near the center of gaze, they systematically underestimate peripheral source directions. We found that this behavior is predicted by statistical inference, formulated as a Bayesian model that emphasizes central directions. We propose that there is a bias in the neural coding of auditory space, which, at the expense of inducing errors in the periphery, achieves high behavioral accuracy at the ethologically relevant range. We found that the owl's map of auditory space decoded by a population vector is consistent with the behavioral model. Thus, a probabilistic model describes both how the map of auditory space supports behavior and why this representation is optimal. More... »

PAGES

1061

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/nn.2872

DOI

http://dx.doi.org/10.1038/nn.2872

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1036027916

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/21725311


Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
Incoming Citations Browse incoming citations for this publication using opencitations.net

JSON-LD is the canonical representation for SciGraph data.

TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

[
  {
    "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
    "about": [
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/1701", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Psychology", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/17", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Psychology and Cognitive Sciences", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Acoustic Stimulation", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Animals", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Bayes Theorem", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Behavior, Animal", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Brain", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Brain Mapping", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Likelihood Functions", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Models, Biological", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Neurons", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Sound Localization", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Strigiformes", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Laboratoire de Neurosciences Cognitives", 
          "id": "https://www.grid.ac/institutes/grid.462870.f", 
          "name": [
            "Group for Neural Theory, D\u00e9partement d'Etudes Cognitives, Ecole Normale Sup\u00e9rieure, Paris, France.", 
            "Laboratoire de Neurosciences Cognitives, INSERM U960, Paris, France."
          ], 
          "type": "Organization"
        }, 
        "familyName": "Fischer", 
        "givenName": "Brian J", 
        "id": "sg:person.01230470433.79", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01230470433.79"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Albert Einstein College of Medicine", 
          "id": "https://www.grid.ac/institutes/grid.251993.5", 
          "name": [
            "Dominick P. Purpura Department of Neuroscience, Albert Einstein College of Medicine, Bronx, New York, USA."
          ], 
          "type": "Organization"
        }, 
        "familyName": "Pe\u00f1a", 
        "givenName": "Jos\u00e9 Luis", 
        "id": "sg:person.01130537730.48", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01130537730.48"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1152/jn.00628.2009", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1000798395"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1152/jn.00954.2002", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1001841983"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nature02768", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1005201330", 
          "https://doi.org/10.1038/nature02768"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nature02768", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1005201330", 
          "https://doi.org/10.1038/nature02768"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1152/jn.00400.2009", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1007086334"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0896-6273(00)80595-4", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1012350963"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1523/jneurosci.0220-06.2006", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1020104099"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nn0602-858", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1023252017", 
          "https://doi.org/10.1038/nn0602-858"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nn0602-858", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1023252017", 
          "https://doi.org/10.1038/nn0602-858"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.neuroscience.2007.12.022", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1027119486"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1146/annurev.neuro.26.041002.131123", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029848852"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1523/jneurosci.2533-05.2005", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030509586"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf00663105", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1033821927", 
          "https://doi.org/10.1007/bf00663105"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf00663105", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1033821927", 
          "https://doi.org/10.1007/bf00663105"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1523/jneurosci.1969-08.2008", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1038060873"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf00962720", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1041421686", 
          "https://doi.org/10.1007/bf00962720"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00422-008-0215-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1047148434", 
          "https://doi.org/10.1007/s00422-008-0215-3"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1371/journal.pone.0007721", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1047607529"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1037/h0061495", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1047620573"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0378-5955(98)00014-8", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1048512074"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/345434a0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1049596847", 
          "https://doi.org/10.1038/345434a0"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.bbr.2004.04.018", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1050035341"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1371/journal.pone.0010497", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1050995623"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nature04485", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1053079541", 
          "https://doi.org/10.1038/nature04485"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nature04485", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1053079541", 
          "https://doi.org/10.1038/nature04485"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nature04485", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1053079541", 
          "https://doi.org/10.1038/nature04485"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/nn1669", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1053234906", 
          "https://doi.org/10.1038/nn1669"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1121/1.2139619", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1062309607"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1121/1.392109", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1062343401"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1126/science.644324", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1062637614"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1523/jneurosci.10-10-03227.1990", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1078482849"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1078996115", 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1523/jneurosci.09-07-02591.1989", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1079306572"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1082125865", 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1523/jneurosci.02-09-01177.1982", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1082160993"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1523/jneurosci.18-06-02147.1998", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1083218767"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2011-08", 
    "datePublishedReg": "2011-08-01", 
    "description": "The owl captures prey using sound localization. In the classical model, the owl infers sound direction from the position of greatest activity in a brain map of auditory space. However, this model fails to describe the actual behavior. Although owls accurately localize sources near the center of gaze, they systematically underestimate peripheral source directions. We found that this behavior is predicted by statistical inference, formulated as a Bayesian model that emphasizes central directions. We propose that there is a bias in the neural coding of auditory space, which, at the expense of inducing errors in the periphery, achieves high behavioral accuracy at the ethologically relevant range. We found that the owl's map of auditory space decoded by a population vector is consistent with the behavioral model. Thus, a probabilistic model describes both how the map of auditory space supports behavior and why this representation is optimal.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1038/nn.2872", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": true, 
    "isFundedItemOf": [
      {
        "id": "sg:grant.2488950", 
        "type": "MonetaryGrant"
      }
    ], 
    "isPartOf": [
      {
        "id": "sg:journal.1118362", 
        "issn": [
          "1097-6256", 
          "1546-1726"
        ], 
        "name": "Nature Neuroscience", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "8", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "14"
      }
    ], 
    "name": "Owl's behavior and neural representation predicted by Bayesian inference", 
    "pagination": "1061", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "ab9f827682a8ba34cf711e04ccf1736e7ad55913deb4103b8a31ebaa88e596af"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "21725311"
        ]
      }, 
      {
        "name": "nlm_unique_id", 
        "type": "PropertyValue", 
        "value": [
          "9809671"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1038/nn.2872"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1036027916"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1038/nn.2872", 
      "https://app.dimensions.ai/details/publication/pub.1036027916"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-11T00:05", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000001_0000000264/records_8695_00000436.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://www.nature.com/articles/nn.2872"
  }
]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1038/nn.2872'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1038/nn.2872'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1038/nn.2872'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1038/nn.2872'


 

This table displays all metadata directly associated to this object as RDF triples.

225 TRIPLES      21 PREDICATES      71 URIs      32 LITERALS      20 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1038/nn.2872 schema:about N02d750e4ac1f401bb203020be6659398
2 N0f1663be517c45b1a84946bb502398fd
3 N419de9f71fb6446fa35b53da012b8bba
4 N7014f4d52d4d4a5098d15784244a9cc7
5 N8817caf39f9f4eba84d179ec3e8168ae
6 Nc28003d0a6a34415a648d0ea3cb370c5
7 Nd412cb4579c945dbaf950fe8ec555962
8 Ne91eed96c66343d3b7b69da66ccb4ce4
9 Ne9a3302e9588456daf4cb3a7ae54a99a
10 Nf20eacdc51264269b5f9945d441c9831
11 Nfac17d17392a4878af7979afd8ea277f
12 anzsrc-for:17
13 anzsrc-for:1701
14 schema:author N1f96ccb034ed4930aff42afc70a48f5b
15 schema:citation sg:pub.10.1007/bf00663105
16 sg:pub.10.1007/bf00962720
17 sg:pub.10.1007/s00422-008-0215-3
18 sg:pub.10.1038/345434a0
19 sg:pub.10.1038/nature02768
20 sg:pub.10.1038/nature04485
21 sg:pub.10.1038/nn0602-858
22 sg:pub.10.1038/nn1669
23 https://app.dimensions.ai/details/publication/pub.1078996115
24 https://app.dimensions.ai/details/publication/pub.1082125865
25 https://doi.org/10.1016/j.bbr.2004.04.018
26 https://doi.org/10.1016/j.neuroscience.2007.12.022
27 https://doi.org/10.1016/s0378-5955(98)00014-8
28 https://doi.org/10.1016/s0896-6273(00)80595-4
29 https://doi.org/10.1037/h0061495
30 https://doi.org/10.1121/1.2139619
31 https://doi.org/10.1121/1.392109
32 https://doi.org/10.1126/science.644324
33 https://doi.org/10.1146/annurev.neuro.26.041002.131123
34 https://doi.org/10.1152/jn.00400.2009
35 https://doi.org/10.1152/jn.00628.2009
36 https://doi.org/10.1152/jn.00954.2002
37 https://doi.org/10.1371/journal.pone.0007721
38 https://doi.org/10.1371/journal.pone.0010497
39 https://doi.org/10.1523/jneurosci.02-09-01177.1982
40 https://doi.org/10.1523/jneurosci.0220-06.2006
41 https://doi.org/10.1523/jneurosci.09-07-02591.1989
42 https://doi.org/10.1523/jneurosci.10-10-03227.1990
43 https://doi.org/10.1523/jneurosci.18-06-02147.1998
44 https://doi.org/10.1523/jneurosci.1969-08.2008
45 https://doi.org/10.1523/jneurosci.2533-05.2005
46 schema:datePublished 2011-08
47 schema:datePublishedReg 2011-08-01
48 schema:description The owl captures prey using sound localization. In the classical model, the owl infers sound direction from the position of greatest activity in a brain map of auditory space. However, this model fails to describe the actual behavior. Although owls accurately localize sources near the center of gaze, they systematically underestimate peripheral source directions. We found that this behavior is predicted by statistical inference, formulated as a Bayesian model that emphasizes central directions. We propose that there is a bias in the neural coding of auditory space, which, at the expense of inducing errors in the periphery, achieves high behavioral accuracy at the ethologically relevant range. We found that the owl's map of auditory space decoded by a population vector is consistent with the behavioral model. Thus, a probabilistic model describes both how the map of auditory space supports behavior and why this representation is optimal.
49 schema:genre research_article
50 schema:inLanguage en
51 schema:isAccessibleForFree true
52 schema:isPartOf N6941947817ac494fa754db4ee46fe7ce
53 N92d8c92c8ffe4543b15f73d9b9012572
54 sg:journal.1118362
55 schema:name Owl's behavior and neural representation predicted by Bayesian inference
56 schema:pagination 1061
57 schema:productId N34a2d8545b2b49f59d232ec3551199e8
58 N3e17c789f8ad4bd9a2728060e922f186
59 N426a979cd9b745faaf9b94d6e8c17427
60 N9876c63ff9814ec2b9588e312c5d987a
61 Ned2567181e234dbcb4d1439d291eb613
62 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036027916
63 https://doi.org/10.1038/nn.2872
64 schema:sdDatePublished 2019-04-11T00:05
65 schema:sdLicense https://scigraph.springernature.com/explorer/license/
66 schema:sdPublisher N1f72ef826c4b4a699d011de331462a56
67 schema:url https://www.nature.com/articles/nn.2872
68 sgo:license sg:explorer/license/
69 sgo:sdDataset articles
70 rdf:type schema:ScholarlyArticle
71 N02d750e4ac1f401bb203020be6659398 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
72 schema:name Neurons
73 rdf:type schema:DefinedTerm
74 N0f1663be517c45b1a84946bb502398fd schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
75 schema:name Brain
76 rdf:type schema:DefinedTerm
77 N1f72ef826c4b4a699d011de331462a56 schema:name Springer Nature - SN SciGraph project
78 rdf:type schema:Organization
79 N1f96ccb034ed4930aff42afc70a48f5b rdf:first sg:person.01230470433.79
80 rdf:rest N3e118dcf10d34a05b72c77237978d613
81 N34a2d8545b2b49f59d232ec3551199e8 schema:name nlm_unique_id
82 schema:value 9809671
83 rdf:type schema:PropertyValue
84 N3e118dcf10d34a05b72c77237978d613 rdf:first sg:person.01130537730.48
85 rdf:rest rdf:nil
86 N3e17c789f8ad4bd9a2728060e922f186 schema:name dimensions_id
87 schema:value pub.1036027916
88 rdf:type schema:PropertyValue
89 N419de9f71fb6446fa35b53da012b8bba schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
90 schema:name Behavior, Animal
91 rdf:type schema:DefinedTerm
92 N426a979cd9b745faaf9b94d6e8c17427 schema:name readcube_id
93 schema:value ab9f827682a8ba34cf711e04ccf1736e7ad55913deb4103b8a31ebaa88e596af
94 rdf:type schema:PropertyValue
95 N6941947817ac494fa754db4ee46fe7ce schema:volumeNumber 14
96 rdf:type schema:PublicationVolume
97 N7014f4d52d4d4a5098d15784244a9cc7 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
98 schema:name Animals
99 rdf:type schema:DefinedTerm
100 N8817caf39f9f4eba84d179ec3e8168ae schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
101 schema:name Strigiformes
102 rdf:type schema:DefinedTerm
103 N92d8c92c8ffe4543b15f73d9b9012572 schema:issueNumber 8
104 rdf:type schema:PublicationIssue
105 N9876c63ff9814ec2b9588e312c5d987a schema:name doi
106 schema:value 10.1038/nn.2872
107 rdf:type schema:PropertyValue
108 Nc28003d0a6a34415a648d0ea3cb370c5 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
109 schema:name Brain Mapping
110 rdf:type schema:DefinedTerm
111 Nd412cb4579c945dbaf950fe8ec555962 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
112 schema:name Bayes Theorem
113 rdf:type schema:DefinedTerm
114 Ne91eed96c66343d3b7b69da66ccb4ce4 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
115 schema:name Sound Localization
116 rdf:type schema:DefinedTerm
117 Ne9a3302e9588456daf4cb3a7ae54a99a schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
118 schema:name Acoustic Stimulation
119 rdf:type schema:DefinedTerm
120 Ned2567181e234dbcb4d1439d291eb613 schema:name pubmed_id
121 schema:value 21725311
122 rdf:type schema:PropertyValue
123 Nf20eacdc51264269b5f9945d441c9831 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
124 schema:name Models, Biological
125 rdf:type schema:DefinedTerm
126 Nfac17d17392a4878af7979afd8ea277f schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
127 schema:name Likelihood Functions
128 rdf:type schema:DefinedTerm
129 anzsrc-for:17 schema:inDefinedTermSet anzsrc-for:
130 schema:name Psychology and Cognitive Sciences
131 rdf:type schema:DefinedTerm
132 anzsrc-for:1701 schema:inDefinedTermSet anzsrc-for:
133 schema:name Psychology
134 rdf:type schema:DefinedTerm
135 sg:grant.2488950 http://pending.schema.org/fundedItem sg:pub.10.1038/nn.2872
136 rdf:type schema:MonetaryGrant
137 sg:journal.1118362 schema:issn 1097-6256
138 1546-1726
139 schema:name Nature Neuroscience
140 rdf:type schema:Periodical
141 sg:person.01130537730.48 schema:affiliation https://www.grid.ac/institutes/grid.251993.5
142 schema:familyName Peña
143 schema:givenName José Luis
144 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01130537730.48
145 rdf:type schema:Person
146 sg:person.01230470433.79 schema:affiliation https://www.grid.ac/institutes/grid.462870.f
147 schema:familyName Fischer
148 schema:givenName Brian J
149 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01230470433.79
150 rdf:type schema:Person
151 sg:pub.10.1007/bf00663105 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033821927
152 https://doi.org/10.1007/bf00663105
153 rdf:type schema:CreativeWork
154 sg:pub.10.1007/bf00962720 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041421686
155 https://doi.org/10.1007/bf00962720
156 rdf:type schema:CreativeWork
157 sg:pub.10.1007/s00422-008-0215-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047148434
158 https://doi.org/10.1007/s00422-008-0215-3
159 rdf:type schema:CreativeWork
160 sg:pub.10.1038/345434a0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1049596847
161 https://doi.org/10.1038/345434a0
162 rdf:type schema:CreativeWork
163 sg:pub.10.1038/nature02768 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005201330
164 https://doi.org/10.1038/nature02768
165 rdf:type schema:CreativeWork
166 sg:pub.10.1038/nature04485 schema:sameAs https://app.dimensions.ai/details/publication/pub.1053079541
167 https://doi.org/10.1038/nature04485
168 rdf:type schema:CreativeWork
169 sg:pub.10.1038/nn0602-858 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023252017
170 https://doi.org/10.1038/nn0602-858
171 rdf:type schema:CreativeWork
172 sg:pub.10.1038/nn1669 schema:sameAs https://app.dimensions.ai/details/publication/pub.1053234906
173 https://doi.org/10.1038/nn1669
174 rdf:type schema:CreativeWork
175 https://app.dimensions.ai/details/publication/pub.1078996115 schema:CreativeWork
176 https://app.dimensions.ai/details/publication/pub.1082125865 schema:CreativeWork
177 https://doi.org/10.1016/j.bbr.2004.04.018 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050035341
178 rdf:type schema:CreativeWork
179 https://doi.org/10.1016/j.neuroscience.2007.12.022 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027119486
180 rdf:type schema:CreativeWork
181 https://doi.org/10.1016/s0378-5955(98)00014-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1048512074
182 rdf:type schema:CreativeWork
183 https://doi.org/10.1016/s0896-6273(00)80595-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012350963
184 rdf:type schema:CreativeWork
185 https://doi.org/10.1037/h0061495 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047620573
186 rdf:type schema:CreativeWork
187 https://doi.org/10.1121/1.2139619 schema:sameAs https://app.dimensions.ai/details/publication/pub.1062309607
188 rdf:type schema:CreativeWork
189 https://doi.org/10.1121/1.392109 schema:sameAs https://app.dimensions.ai/details/publication/pub.1062343401
190 rdf:type schema:CreativeWork
191 https://doi.org/10.1126/science.644324 schema:sameAs https://app.dimensions.ai/details/publication/pub.1062637614
192 rdf:type schema:CreativeWork
193 https://doi.org/10.1146/annurev.neuro.26.041002.131123 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029848852
194 rdf:type schema:CreativeWork
195 https://doi.org/10.1152/jn.00400.2009 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007086334
196 rdf:type schema:CreativeWork
197 https://doi.org/10.1152/jn.00628.2009 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000798395
198 rdf:type schema:CreativeWork
199 https://doi.org/10.1152/jn.00954.2002 schema:sameAs https://app.dimensions.ai/details/publication/pub.1001841983
200 rdf:type schema:CreativeWork
201 https://doi.org/10.1371/journal.pone.0007721 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047607529
202 rdf:type schema:CreativeWork
203 https://doi.org/10.1371/journal.pone.0010497 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050995623
204 rdf:type schema:CreativeWork
205 https://doi.org/10.1523/jneurosci.02-09-01177.1982 schema:sameAs https://app.dimensions.ai/details/publication/pub.1082160993
206 rdf:type schema:CreativeWork
207 https://doi.org/10.1523/jneurosci.0220-06.2006 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020104099
208 rdf:type schema:CreativeWork
209 https://doi.org/10.1523/jneurosci.09-07-02591.1989 schema:sameAs https://app.dimensions.ai/details/publication/pub.1079306572
210 rdf:type schema:CreativeWork
211 https://doi.org/10.1523/jneurosci.10-10-03227.1990 schema:sameAs https://app.dimensions.ai/details/publication/pub.1078482849
212 rdf:type schema:CreativeWork
213 https://doi.org/10.1523/jneurosci.18-06-02147.1998 schema:sameAs https://app.dimensions.ai/details/publication/pub.1083218767
214 rdf:type schema:CreativeWork
215 https://doi.org/10.1523/jneurosci.1969-08.2008 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038060873
216 rdf:type schema:CreativeWork
217 https://doi.org/10.1523/jneurosci.2533-05.2005 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030509586
218 rdf:type schema:CreativeWork
219 https://www.grid.ac/institutes/grid.251993.5 schema:alternateName Albert Einstein College of Medicine
220 schema:name Dominick P. Purpura Department of Neuroscience, Albert Einstein College of Medicine, Bronx, New York, USA.
221 rdf:type schema:Organization
222 https://www.grid.ac/institutes/grid.462870.f schema:alternateName Laboratoire de Neurosciences Cognitives
223 schema:name Group for Neural Theory, Département d'Etudes Cognitives, Ecole Normale Supérieure, Paris, France.
224 Laboratoire de Neurosciences Cognitives, INSERM U960, Paris, France.
225 rdf:type schema:Organization
 




Preview window. Press ESC to close (or click here)


...