Robots as Models of the Brain: What Can We Learn from Modelling Rat Navigation and Infant Imitation Games? View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2003

AUTHORS

Philippe Gaussier , Pierre Andry , Jean Paul Banquet , Mathias Quoy , Jacqueline Nadel , Arnaud Revel

ABSTRACT

Understanding the brain and the cognitive mechanisms is a central question for philosophers, neuroscientists, psychologs and engineers as well. In our team, we try to reconcile the old cybernetic approach with neural network modelling and artificial intelligence. This neurocybernetics approach aims at participating in the effort to build a science of the cognition. Our goal is clearly not to design optimal solutions for a particular problem but to try to understand what are the mechanisms allowing the brain to adapt itself in order to survive to a wide variety of unpredictable situations. Hence, robots can be seen as simulation tools allowing to test the behavioral consequences of a particular model in almost real conditions. We use Koala mobile robots (see fig. 1) equipped with one pan-tilt ”head” and a 5 degrees of freedom Katana arm. The pan-tilt head can rotates 180 degrees horizontally and vertically, and supports a single CCD color camera. More... »

PAGES

377-385

Book

TITLE

Artificial Intelligence in Medicine

ISBN

978-3-540-20129-8
978-3-540-39907-0

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-540-39907-0_52

DOI

http://dx.doi.org/10.1007/978-3-540-39907-0_52

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1049913810


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/2008/0801", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Artificial Intelligence and Image Processing", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/08", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Information and Computing Sciences", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "name": [
            "Neuro-cybernetic team, Image and Signal processing Lab. (ETIS), CNRS UMR 8051, UCP-ENSEA, 6 av du Ponceau, 95014, Cergy Pontoise, France"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Gaussier", 
        "givenName": "Philippe", 
        "id": "sg:person.01041272554.05", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01041272554.05"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "name": [
            "Neuro-cybernetic team, Image and Signal processing Lab. (ETIS), CNRS UMR 8051, UCP-ENSEA, 6 av du Ponceau, 95014, Cergy Pontoise, France"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Andry", 
        "givenName": "Pierre", 
        "id": "sg:person.012152621257.16", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012152621257.16"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "French Institute of Health and Medical Research", 
          "id": "https://www.grid.ac/institutes/grid.7429.8", 
          "name": [
            "Neuro-cybernetic team, Image and Signal processing Lab. (ETIS), CNRS UMR 8051, UCP-ENSEA, 6 av du Ponceau, 95014, Cergy Pontoise, France", 
            "Neurosciences and modelisation institute, INSERM 483, Jussieu, Paris"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Banquet", 
        "givenName": "Jean Paul", 
        "id": "sg:person.0773157354.72", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0773157354.72"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "name": [
            "Neuro-cybernetic team, Image and Signal processing Lab. (ETIS), CNRS UMR 8051, UCP-ENSEA, 6 av du Ponceau, 95014, Cergy Pontoise, France"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Quoy", 
        "givenName": "Mathias", 
        "id": "sg:person.010556353111.37", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010556353111.37"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Piti\u00e9-Salp\u00eatri\u00e8re Hospital", 
          "id": "https://www.grid.ac/institutes/grid.411439.a", 
          "name": [
            "Hopital de la Salp\u00e9tri\u00eare, Equipe D\u00e9veloppement et Psychopathologie UMR CNRS 7593, Paris, France"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Nadel", 
        "givenName": "Jacqueline", 
        "id": "sg:person.0665426200.17", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0665426200.17"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "name": [
            "Neuro-cybernetic team, Image and Signal processing Lab. (ETIS), CNRS UMR 8051, UCP-ENSEA, 6 av du Ponceau, 95014, Cergy Pontoise, France"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Revel", 
        "givenName": "Arnaud", 
        "id": "sg:person.010634335021.86", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010634335021.86"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1136/jnnp.20.1.11", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1000517405"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1080/088395198117596", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1009321480"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1017/cbo9780511489969.003", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011394074"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0926-6410(95)00033-x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011436968"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0893-6080(05)80153-4", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1012513700"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0893-6080(05)80153-4", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1012513700"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s004220100269", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1015097071", 
          "https://doi.org/10.1007/s004220100269"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0921-8890(95)00052-6", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029057226"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0921-8890(99)00070-6", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030554231"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/(sici)1099-0917(199709/12)6:3/4<179::aid-edp157>3.0.co;2-r", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1031041035"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/(sici)1099-0917(199709/12)6:3/4<179::aid-edp157>3.0.co;2-r", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1031041035"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/379255a0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1032842013", 
          "https://doi.org/10.1038/379255a0"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1017/cbo9780511489969.015", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1036108696"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1098/rstb.1990.0161", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1039129357"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/brain/120.10.1763", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1046280398"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1017/s0140525x99002034", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1052412362"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/3468.952717", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061157851"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2307/1129418", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1069382667"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2003", 
    "datePublishedReg": "2003-01-01", 
    "description": "Understanding the brain and the cognitive mechanisms is a central question for philosophers, neuroscientists, psychologs and engineers as well. In our team, we try to reconcile the old cybernetic approach with neural network modelling and artificial intelligence. This neurocybernetics approach aims at participating in the effort to build a science of the cognition. Our goal is clearly not to design optimal solutions for a particular problem but to try to understand what are the mechanisms allowing the brain to adapt itself in order to survive to a wide variety of unpredictable situations. Hence, robots can be seen as simulation tools allowing to test the behavioral consequences of a particular model in almost real conditions. We use Koala mobile robots (see fig. 1) equipped with one pan-tilt \u201dhead\u201d and a 5 degrees of freedom Katana arm. The pan-tilt head can rotates 180 degrees horizontally and vertically, and supports a single CCD color camera.", 
    "editor": [
      {
        "familyName": "Dojat", 
        "givenName": "Michel", 
        "type": "Person"
      }, 
      {
        "familyName": "Keravnou", 
        "givenName": "Elpida T.", 
        "type": "Person"
      }, 
      {
        "familyName": "Barahona", 
        "givenName": "Pedro", 
        "type": "Person"
      }
    ], 
    "genre": "chapter", 
    "id": "sg:pub.10.1007/978-3-540-39907-0_52", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isPartOf": {
      "isbn": [
        "978-3-540-20129-8", 
        "978-3-540-39907-0"
      ], 
      "name": "Artificial Intelligence in Medicine", 
      "type": "Book"
    }, 
    "name": "Robots as Models of the Brain: What Can We Learn from Modelling Rat Navigation and Infant Imitation Games?", 
    "pagination": "377-385", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1049913810"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/978-3-540-39907-0_52"
        ]
      }, 
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "edc5d01a140d5b6e86bf44b17d4dc0b02ef795c2eac8d0b23433b44e27e209c0"
        ]
      }
    ], 
    "publisher": {
      "location": "Berlin, Heidelberg", 
      "name": "Springer Berlin Heidelberg", 
      "type": "Organisation"
    }, 
    "sameAs": [
      "https://doi.org/10.1007/978-3-540-39907-0_52", 
      "https://app.dimensions.ai/details/publication/pub.1049913810"
    ], 
    "sdDataset": "chapters", 
    "sdDatePublished": "2019-04-16T08:05", 
    "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/v90/0000000359_0000000359/records_29219_00000002.jsonl", 
    "type": "Chapter", 
    "url": "https://link.springer.com/10.1007%2F978-3-540-39907-0_52"
  }
]
 

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.10.1007/978-3-540-39907-0_52'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/978-3-540-39907-0_52'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/978-3-540-39907-0_52'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/978-3-540-39907-0_52'


 

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

172 TRIPLES      23 PREDICATES      43 URIs      20 LITERALS      8 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/978-3-540-39907-0_52 schema:about anzsrc-for:08
2 anzsrc-for:0801
3 schema:author N2ed5436568cd467a809b35e4c52b6824
4 schema:citation sg:pub.10.1007/s004220100269
5 sg:pub.10.1038/379255a0
6 https://doi.org/10.1002/(sici)1099-0917(199709/12)6:3/4<179::aid-edp157>3.0.co;2-r
7 https://doi.org/10.1016/0921-8890(95)00052-6
8 https://doi.org/10.1016/0926-6410(95)00033-x
9 https://doi.org/10.1016/s0893-6080(05)80153-4
10 https://doi.org/10.1016/s0921-8890(99)00070-6
11 https://doi.org/10.1017/cbo9780511489969.003
12 https://doi.org/10.1017/cbo9780511489969.015
13 https://doi.org/10.1017/s0140525x99002034
14 https://doi.org/10.1080/088395198117596
15 https://doi.org/10.1093/brain/120.10.1763
16 https://doi.org/10.1098/rstb.1990.0161
17 https://doi.org/10.1109/3468.952717
18 https://doi.org/10.1136/jnnp.20.1.11
19 https://doi.org/10.2307/1129418
20 schema:datePublished 2003
21 schema:datePublishedReg 2003-01-01
22 schema:description Understanding the brain and the cognitive mechanisms is a central question for philosophers, neuroscientists, psychologs and engineers as well. In our team, we try to reconcile the old cybernetic approach with neural network modelling and artificial intelligence. This neurocybernetics approach aims at participating in the effort to build a science of the cognition. Our goal is clearly not to design optimal solutions for a particular problem but to try to understand what are the mechanisms allowing the brain to adapt itself in order to survive to a wide variety of unpredictable situations. Hence, robots can be seen as simulation tools allowing to test the behavioral consequences of a particular model in almost real conditions. We use Koala mobile robots (see fig. 1) equipped with one pan-tilt ”head” and a 5 degrees of freedom Katana arm. The pan-tilt head can rotates 180 degrees horizontally and vertically, and supports a single CCD color camera.
23 schema:editor Na86011975054465ba0487d174abc5caf
24 schema:genre chapter
25 schema:inLanguage en
26 schema:isAccessibleForFree false
27 schema:isPartOf Nd9c7258d06574ce7bffd8191369de7d8
28 schema:name Robots as Models of the Brain: What Can We Learn from Modelling Rat Navigation and Infant Imitation Games?
29 schema:pagination 377-385
30 schema:productId N7644b5d9e1654d2ea6f99262601c75f9
31 N99c57959419c4b1faad752711542f637
32 Nc01420bad41047cc8585aabf06c9f617
33 schema:publisher N2269098bad4e41ebbe09c3efa5856730
34 schema:sameAs https://app.dimensions.ai/details/publication/pub.1049913810
35 https://doi.org/10.1007/978-3-540-39907-0_52
36 schema:sdDatePublished 2019-04-16T08:05
37 schema:sdLicense https://scigraph.springernature.com/explorer/license/
38 schema:sdPublisher Nb6ae3fccfb6f47639d8aa858a9424a09
39 schema:url https://link.springer.com/10.1007%2F978-3-540-39907-0_52
40 sgo:license sg:explorer/license/
41 sgo:sdDataset chapters
42 rdf:type schema:Chapter
43 N10f0c8de84464a8caff0ce2d3ca8431d schema:familyName Dojat
44 schema:givenName Michel
45 rdf:type schema:Person
46 N215adbe2ef174d478f556b8b275657d9 schema:name Neuro-cybernetic team, Image and Signal processing Lab. (ETIS), CNRS UMR 8051, UCP-ENSEA, 6 av du Ponceau, 95014, Cergy Pontoise, France
47 rdf:type schema:Organization
48 N2269098bad4e41ebbe09c3efa5856730 schema:location Berlin, Heidelberg
49 schema:name Springer Berlin Heidelberg
50 rdf:type schema:Organisation
51 N26849e25ced7442c9b91b78e22838e31 rdf:first sg:person.0773157354.72
52 rdf:rest N9bbb29d8d48e4ead9c83d45e689379dc
53 N2ed5436568cd467a809b35e4c52b6824 rdf:first sg:person.01041272554.05
54 rdf:rest N5d8cfc0da23b4d9b8a25c9f3ada1264a
55 N52c77967fe8243f6b41af6427069ff90 rdf:first N5d17150bcd134434b24297dfc6f35183
56 rdf:rest rdf:nil
57 N53a59bcf64144744b524aabea8042cb3 schema:name Neuro-cybernetic team, Image and Signal processing Lab. (ETIS), CNRS UMR 8051, UCP-ENSEA, 6 av du Ponceau, 95014, Cergy Pontoise, France
58 rdf:type schema:Organization
59 N5d17150bcd134434b24297dfc6f35183 schema:familyName Barahona
60 schema:givenName Pedro
61 rdf:type schema:Person
62 N5d8cfc0da23b4d9b8a25c9f3ada1264a rdf:first sg:person.012152621257.16
63 rdf:rest N26849e25ced7442c9b91b78e22838e31
64 N6f233e60a0ef4223804142df868d3e00 schema:name Neuro-cybernetic team, Image and Signal processing Lab. (ETIS), CNRS UMR 8051, UCP-ENSEA, 6 av du Ponceau, 95014, Cergy Pontoise, France
65 rdf:type schema:Organization
66 N7242003a568c4fbebfd4fa94056e33da rdf:first Nace146bc184142a189882750e1737aa0
67 rdf:rest N52c77967fe8243f6b41af6427069ff90
68 N7505ad66105840a9b255a82d9e2b9280 rdf:first sg:person.010634335021.86
69 rdf:rest rdf:nil
70 N7644b5d9e1654d2ea6f99262601c75f9 schema:name dimensions_id
71 schema:value pub.1049913810
72 rdf:type schema:PropertyValue
73 N99c57959419c4b1faad752711542f637 schema:name doi
74 schema:value 10.1007/978-3-540-39907-0_52
75 rdf:type schema:PropertyValue
76 N9bbb29d8d48e4ead9c83d45e689379dc rdf:first sg:person.010556353111.37
77 rdf:rest Nfc7fa42cbfe74c438580fe0718600994
78 N9f04f882b3d94694a9428716617ff297 schema:name Neuro-cybernetic team, Image and Signal processing Lab. (ETIS), CNRS UMR 8051, UCP-ENSEA, 6 av du Ponceau, 95014, Cergy Pontoise, France
79 rdf:type schema:Organization
80 Na86011975054465ba0487d174abc5caf rdf:first N10f0c8de84464a8caff0ce2d3ca8431d
81 rdf:rest N7242003a568c4fbebfd4fa94056e33da
82 Nace146bc184142a189882750e1737aa0 schema:familyName Keravnou
83 schema:givenName Elpida T.
84 rdf:type schema:Person
85 Nb6ae3fccfb6f47639d8aa858a9424a09 schema:name Springer Nature - SN SciGraph project
86 rdf:type schema:Organization
87 Nc01420bad41047cc8585aabf06c9f617 schema:name readcube_id
88 schema:value edc5d01a140d5b6e86bf44b17d4dc0b02ef795c2eac8d0b23433b44e27e209c0
89 rdf:type schema:PropertyValue
90 Nd9c7258d06574ce7bffd8191369de7d8 schema:isbn 978-3-540-20129-8
91 978-3-540-39907-0
92 schema:name Artificial Intelligence in Medicine
93 rdf:type schema:Book
94 Nfc7fa42cbfe74c438580fe0718600994 rdf:first sg:person.0665426200.17
95 rdf:rest N7505ad66105840a9b255a82d9e2b9280
96 anzsrc-for:08 schema:inDefinedTermSet anzsrc-for:
97 schema:name Information and Computing Sciences
98 rdf:type schema:DefinedTerm
99 anzsrc-for:0801 schema:inDefinedTermSet anzsrc-for:
100 schema:name Artificial Intelligence and Image Processing
101 rdf:type schema:DefinedTerm
102 sg:person.01041272554.05 schema:affiliation N53a59bcf64144744b524aabea8042cb3
103 schema:familyName Gaussier
104 schema:givenName Philippe
105 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01041272554.05
106 rdf:type schema:Person
107 sg:person.010556353111.37 schema:affiliation N9f04f882b3d94694a9428716617ff297
108 schema:familyName Quoy
109 schema:givenName Mathias
110 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010556353111.37
111 rdf:type schema:Person
112 sg:person.010634335021.86 schema:affiliation N215adbe2ef174d478f556b8b275657d9
113 schema:familyName Revel
114 schema:givenName Arnaud
115 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010634335021.86
116 rdf:type schema:Person
117 sg:person.012152621257.16 schema:affiliation N6f233e60a0ef4223804142df868d3e00
118 schema:familyName Andry
119 schema:givenName Pierre
120 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012152621257.16
121 rdf:type schema:Person
122 sg:person.0665426200.17 schema:affiliation https://www.grid.ac/institutes/grid.411439.a
123 schema:familyName Nadel
124 schema:givenName Jacqueline
125 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0665426200.17
126 rdf:type schema:Person
127 sg:person.0773157354.72 schema:affiliation https://www.grid.ac/institutes/grid.7429.8
128 schema:familyName Banquet
129 schema:givenName Jean Paul
130 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0773157354.72
131 rdf:type schema:Person
132 sg:pub.10.1007/s004220100269 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015097071
133 https://doi.org/10.1007/s004220100269
134 rdf:type schema:CreativeWork
135 sg:pub.10.1038/379255a0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1032842013
136 https://doi.org/10.1038/379255a0
137 rdf:type schema:CreativeWork
138 https://doi.org/10.1002/(sici)1099-0917(199709/12)6:3/4<179::aid-edp157>3.0.co;2-r schema:sameAs https://app.dimensions.ai/details/publication/pub.1031041035
139 rdf:type schema:CreativeWork
140 https://doi.org/10.1016/0921-8890(95)00052-6 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029057226
141 rdf:type schema:CreativeWork
142 https://doi.org/10.1016/0926-6410(95)00033-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1011436968
143 rdf:type schema:CreativeWork
144 https://doi.org/10.1016/s0893-6080(05)80153-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012513700
145 rdf:type schema:CreativeWork
146 https://doi.org/10.1016/s0921-8890(99)00070-6 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030554231
147 rdf:type schema:CreativeWork
148 https://doi.org/10.1017/cbo9780511489969.003 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011394074
149 rdf:type schema:CreativeWork
150 https://doi.org/10.1017/cbo9780511489969.015 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036108696
151 rdf:type schema:CreativeWork
152 https://doi.org/10.1017/s0140525x99002034 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052412362
153 rdf:type schema:CreativeWork
154 https://doi.org/10.1080/088395198117596 schema:sameAs https://app.dimensions.ai/details/publication/pub.1009321480
155 rdf:type schema:CreativeWork
156 https://doi.org/10.1093/brain/120.10.1763 schema:sameAs https://app.dimensions.ai/details/publication/pub.1046280398
157 rdf:type schema:CreativeWork
158 https://doi.org/10.1098/rstb.1990.0161 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039129357
159 rdf:type schema:CreativeWork
160 https://doi.org/10.1109/3468.952717 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061157851
161 rdf:type schema:CreativeWork
162 https://doi.org/10.1136/jnnp.20.1.11 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000517405
163 rdf:type schema:CreativeWork
164 https://doi.org/10.2307/1129418 schema:sameAs https://app.dimensions.ai/details/publication/pub.1069382667
165 rdf:type schema:CreativeWork
166 https://www.grid.ac/institutes/grid.411439.a schema:alternateName Pitié-Salpêtrière Hospital
167 schema:name Hopital de la Salpétriêre, Equipe Développement et Psychopathologie UMR CNRS 7593, Paris, France
168 rdf:type schema:Organization
169 https://www.grid.ac/institutes/grid.7429.8 schema:alternateName French Institute of Health and Medical Research
170 schema:name Neuro-cybernetic team, Image and Signal processing Lab. (ETIS), CNRS UMR 8051, UCP-ENSEA, 6 av du Ponceau, 95014, Cergy Pontoise, France
171 Neurosciences and modelisation institute, INSERM 483, Jussieu, Paris
172 rdf:type schema:Organization
 




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


...