Conditional visuo-motor learning and dimension reduction View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2006-06

AUTHORS

Fadila Hadj-Bouziane, Hélène Frankowska, Martine Meunier, Pierre-Arnaud Coquelin, Driss Boussaoud

ABSTRACT

Conditional visuo-motor learning consists in learning by trial and error to associate visual cues with correct motor responses, that have no direct link. Converging evidence supports the role of a large brain network in this type of learning, including the prefrontal and the premotor cortex, the basal ganglia BG and the hippocampus. In this paper we focus on the role of a major structure of the BG, the striatum. We first present behavioral results and electrophysiological data recorded from this structure in monkeys engaged in learning new visuo-motor associations. Visual stimuli were presented on a video screen and the animals had to learn, by trial and error, to select the correct movement of a joystick, in order to receive a liquid reward. Behavioral results revealed that the monkeys used a sequential strategy, whereby they learned the associations one by one although they were presented randomly. Human subjects, tested on the same task, also used a sequential strategy. Neuronal recordings in monkeys revealed learning-related modulations of neural activity in the striatum. We then present a mathematical model inspired by viability theory developed to implement the use of strategies during learning. This model complements existing models of the BG based on reinforcement learning RL, which do not take into account the use of strategies to reduce the dimension of the learning space. More... »

PAGES

95

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s10339-005-0028-4

DOI

http://dx.doi.org/10.1007/s10339-005-0028-4

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1022681034

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/16683172


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": "Basal Ganglia", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Humans", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Learning", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Models, Neurological", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Models, Statistical", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Neurons", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Psychomotor Performance", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "National Institute of Mental Health", 
          "id": "https://www.grid.ac/institutes/grid.416868.5", 
          "name": [
            "INCM UMR6193, CNRS& Aix-Marseille Universit\u00e9, 31 Chemin Jospeh Aiguier, 13402, Marseille, France", 
            "Laboratory of Brain and Cognition, NIMH, Bethesda, MD, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Hadj-Bouziane", 
        "givenName": "Fadila", 
        "id": "sg:person.01217257611.11", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01217257611.11"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "French National Centre for Scientific Research", 
          "id": "https://www.grid.ac/institutes/grid.4444.0", 
          "name": [
            "CNRS, CREA, Ecole Polytechnique, 1 rue Descartes, 75005, Paris, France"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Frankowska", 
        "givenName": "H\u00e9l\u00e8ne", 
        "id": "sg:person.014732773366.11", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014732773366.11"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Aix-Marseille University", 
          "id": "https://www.grid.ac/institutes/grid.5399.6", 
          "name": [
            "INCM UMR6193, CNRS& Aix-Marseille Universit\u00e9, 31 Chemin Jospeh Aiguier, 13402, Marseille, France"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Meunier", 
        "givenName": "Martine", 
        "id": "sg:person.01151714670.22", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01151714670.22"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "French National Centre for Scientific Research", 
          "id": "https://www.grid.ac/institutes/grid.4444.0", 
          "name": [
            "CNRS, CREA, Ecole Polytechnique, 1 rue Descartes, 75005, Paris, France"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Coquelin", 
        "givenName": "Pierre-Arnaud", 
        "id": "sg:person.01171126363.81", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01171126363.81"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Aix-Marseille University", 
          "id": "https://www.grid.ac/institutes/grid.5399.6", 
          "name": [
            "INCM UMR6193, CNRS& Aix-Marseille Universit\u00e9, 31 Chemin Jospeh Aiguier, 13402, Marseille, France"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Boussaoud", 
        "givenName": "Driss", 
        "id": "sg:person.0730715063.17", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0730715063.17"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1016/j.pneurobio.2003.12.001", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1000504111"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1037/0735-7044.115.5.971", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1001416460"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1037/0735-7044.115.5.971", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1001416460"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0166-2236(00)01570-8", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1007088116"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1460-9568.1997.tb01382.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1007962130"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0079-6123(08)60353-2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1008064239"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0166-2236(90)90105-j", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1009318185"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0166-2236(90)90105-j", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1009318185"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0891-0618(00)00099-5", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1012769597"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0165-0173(94)00007-c", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1013782478"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0306-4522(94)90536-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1013930205"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0306-4522(94)90536-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1013930205"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1162/089976600300015961", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1015123179"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0893-6080(99)00046-5", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1016131651"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1006/jmaa.1996.0273", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1019199558"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1201/9780203503584.sec3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1021121493"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/(sici)1098-1063(1999)9:2<101::aid-hipo3>3.0.co;2-l", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1022147300"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0896-6273(02)00967-4", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1023967151"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0079-6123(08)61349-7", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1027980632"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s1471-1931(00)00023-9", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1028555962"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf00250573", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1028634771", 
          "https://doi.org/10.1007/bf00250573"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf00250573", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1028634771", 
          "https://doi.org/10.1007/bf00250573"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf00229651", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1028880666", 
          "https://doi.org/10.1007/bf00229651"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf00229651", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1028880666", 
          "https://doi.org/10.1007/bf00229651"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.0953-816x.2003.03181.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029759153"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-1-4612-1592-9_4", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1034570490", 
          "https://doi.org/10.1007/978-1-4612-1592-9_4"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf00229650", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1034892789", 
          "https://doi.org/10.1007/bf00229650"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf00229650", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1034892789", 
          "https://doi.org/10.1007/bf00229650"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1146/annurev.ne.09.030186.002041", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1035901217"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s002210000405", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1040531047", 
          "https://doi.org/10.1007/s002210000405"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1126/science.1077349", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1040552809"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/3-540-45873-5_30", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1041369163", 
          "https://doi.org/10.1007/3-540-45873-5_30"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1460-9568.2004.03788.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1043404250"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.neuron.2005.06.006", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1043514293"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.neuron.2005.06.006", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1043514293"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1139/y96-035", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1043589326"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jphysparis.2004.01.014", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1044078907"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/cercor/12.10.1040", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1050936869"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/brain/113.1.207", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1059438601"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1137/s036301290036968x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1062880404"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1139/cjpp-74-4-469", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1062890176"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1615/critrevneurobiol.v10.i3-4.30", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1068132164"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1152/jn.1992.67.1.145", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1076961004"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1152/jn.1994.71.3.1151", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1082698987"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1152/jn.1998.80.2.947", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1083306180"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1152/jn.1998.80.2.964", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1083306181"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1017/cbo9780511626258", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1098669259"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.23919/ecc.2001.7076351", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1105845937"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.23919/ecc.2001.7076351", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1105845937"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2006-06", 
    "datePublishedReg": "2006-06-01", 
    "description": "Conditional visuo-motor learning consists in learning by trial and error to associate visual cues with correct motor responses, that have no direct link. Converging evidence supports the role of a large brain network in this type of learning, including the prefrontal and the premotor cortex, the basal ganglia BG and the hippocampus. In this paper we focus on the role of a major structure of the BG, the striatum. We first present behavioral results and electrophysiological data recorded from this structure in monkeys engaged in learning new visuo-motor associations. Visual stimuli were presented on a video screen and the animals had to learn, by trial and error, to select the correct movement of a joystick, in order to receive a liquid reward. Behavioral results revealed that the monkeys used a sequential strategy, whereby they learned the associations one by one although they were presented randomly. Human subjects, tested on the same task, also used a sequential strategy. Neuronal recordings in monkeys revealed learning-related modulations of neural activity in the striatum. We then present a mathematical model inspired by viability theory developed to implement the use of strategies during learning. This model complements existing models of the BG based on reinforcement learning RL, which do not take into account the use of strategies to reduce the dimension of the learning space.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1007/s10339-005-0028-4", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isPartOf": [
      {
        "id": "sg:journal.1032322", 
        "issn": [
          "1612-4782", 
          "1612-4790"
        ], 
        "name": "Cognitive Processing", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "2", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "7"
      }
    ], 
    "name": "Conditional visuo-motor learning and dimension reduction", 
    "pagination": "95", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "6c0dffbc766f9efd6408a2a510c6837c0e8ef79bcb1e9b2cdc2153a9101a7fdb"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "16683172"
        ]
      }, 
      {
        "name": "nlm_unique_id", 
        "type": "PropertyValue", 
        "value": [
          "101177984"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s10339-005-0028-4"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1022681034"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s10339-005-0028-4", 
      "https://app.dimensions.ai/details/publication/pub.1022681034"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-11T12:42", 
    "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/v90/0000000363_0000000363/records_70061_00000000.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "http://link.springer.com/10.1007%2Fs10339-005-0028-4"
  }
]
 

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/s10339-005-0028-4'

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/s10339-005-0028-4'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s10339-005-0028-4'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s10339-005-0028-4'


 

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

261 TRIPLES      21 PREDICATES      77 URIs      28 LITERALS      16 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s10339-005-0028-4 schema:about N094297eb6ee14392bc57073a09ef6196
2 N0f2a4d7deb044f34a28f27164f98f33c
3 N295f571691e04c379abc97f982c8f872
4 N3c6539ec50cc43fd9306d46d6f0a13dc
5 N48918d1d1ad74378bd99b1c0189e9751
6 N9147bacf1a104f27a347a6242d4e186a
7 Nb93a3da7048744d4a6a5bdda8b92c7d1
8 anzsrc-for:17
9 anzsrc-for:1701
10 schema:author Nee209236f7e94d04802dcbf1f57194d8
11 schema:citation sg:pub.10.1007/3-540-45873-5_30
12 sg:pub.10.1007/978-1-4612-1592-9_4
13 sg:pub.10.1007/bf00229650
14 sg:pub.10.1007/bf00229651
15 sg:pub.10.1007/bf00250573
16 sg:pub.10.1007/s002210000405
17 https://doi.org/10.1002/(sici)1098-1063(1999)9:2<101::aid-hipo3>3.0.co;2-l
18 https://doi.org/10.1006/jmaa.1996.0273
19 https://doi.org/10.1016/0165-0173(94)00007-c
20 https://doi.org/10.1016/0166-2236(90)90105-j
21 https://doi.org/10.1016/0306-4522(94)90536-3
22 https://doi.org/10.1016/j.jphysparis.2004.01.014
23 https://doi.org/10.1016/j.neuron.2005.06.006
24 https://doi.org/10.1016/j.pneurobio.2003.12.001
25 https://doi.org/10.1016/s0079-6123(08)60353-2
26 https://doi.org/10.1016/s0079-6123(08)61349-7
27 https://doi.org/10.1016/s0166-2236(00)01570-8
28 https://doi.org/10.1016/s0891-0618(00)00099-5
29 https://doi.org/10.1016/s0893-6080(99)00046-5
30 https://doi.org/10.1016/s0896-6273(02)00967-4
31 https://doi.org/10.1016/s1471-1931(00)00023-9
32 https://doi.org/10.1017/cbo9780511626258
33 https://doi.org/10.1037/0735-7044.115.5.971
34 https://doi.org/10.1093/brain/113.1.207
35 https://doi.org/10.1093/cercor/12.10.1040
36 https://doi.org/10.1111/j.0953-816x.2003.03181.x
37 https://doi.org/10.1111/j.1460-9568.1997.tb01382.x
38 https://doi.org/10.1111/j.1460-9568.2004.03788.x
39 https://doi.org/10.1126/science.1077349
40 https://doi.org/10.1137/s036301290036968x
41 https://doi.org/10.1139/cjpp-74-4-469
42 https://doi.org/10.1139/y96-035
43 https://doi.org/10.1146/annurev.ne.09.030186.002041
44 https://doi.org/10.1152/jn.1992.67.1.145
45 https://doi.org/10.1152/jn.1994.71.3.1151
46 https://doi.org/10.1152/jn.1998.80.2.947
47 https://doi.org/10.1152/jn.1998.80.2.964
48 https://doi.org/10.1162/089976600300015961
49 https://doi.org/10.1201/9780203503584.sec3
50 https://doi.org/10.1615/critrevneurobiol.v10.i3-4.30
51 https://doi.org/10.23919/ecc.2001.7076351
52 schema:datePublished 2006-06
53 schema:datePublishedReg 2006-06-01
54 schema:description Conditional visuo-motor learning consists in learning by trial and error to associate visual cues with correct motor responses, that have no direct link. Converging evidence supports the role of a large brain network in this type of learning, including the prefrontal and the premotor cortex, the basal ganglia BG and the hippocampus. In this paper we focus on the role of a major structure of the BG, the striatum. We first present behavioral results and electrophysiological data recorded from this structure in monkeys engaged in learning new visuo-motor associations. Visual stimuli were presented on a video screen and the animals had to learn, by trial and error, to select the correct movement of a joystick, in order to receive a liquid reward. Behavioral results revealed that the monkeys used a sequential strategy, whereby they learned the associations one by one although they were presented randomly. Human subjects, tested on the same task, also used a sequential strategy. Neuronal recordings in monkeys revealed learning-related modulations of neural activity in the striatum. We then present a mathematical model inspired by viability theory developed to implement the use of strategies during learning. This model complements existing models of the BG based on reinforcement learning RL, which do not take into account the use of strategies to reduce the dimension of the learning space.
55 schema:genre research_article
56 schema:inLanguage en
57 schema:isAccessibleForFree false
58 schema:isPartOf N7ff5172550f84731829939ef9eccb96e
59 Nce5a067bae9d4c98b9a9d6a7386aa6f7
60 sg:journal.1032322
61 schema:name Conditional visuo-motor learning and dimension reduction
62 schema:pagination 95
63 schema:productId N267af8759bf24ead83416ff32ced9b62
64 N6180aff873f54f719f02dfeb161110db
65 N65bef7a3cc294ff2a43fd95f4237e5c9
66 Nd27058f834a243569118c3b0c6f1b0b5
67 Ned392e095f1b40ebb06ded9372b803e0
68 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022681034
69 https://doi.org/10.1007/s10339-005-0028-4
70 schema:sdDatePublished 2019-04-11T12:42
71 schema:sdLicense https://scigraph.springernature.com/explorer/license/
72 schema:sdPublisher N8e6e2bc256b7411e9000452361042a04
73 schema:url http://link.springer.com/10.1007%2Fs10339-005-0028-4
74 sgo:license sg:explorer/license/
75 sgo:sdDataset articles
76 rdf:type schema:ScholarlyArticle
77 N094297eb6ee14392bc57073a09ef6196 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
78 schema:name Models, Neurological
79 rdf:type schema:DefinedTerm
80 N0e06c5acaf434dd09d1e09841a7f6a92 rdf:first sg:person.014732773366.11
81 rdf:rest N87ed9514a2ec42d986a3bde5ea10fc83
82 N0f2a4d7deb044f34a28f27164f98f33c schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
83 schema:name Neurons
84 rdf:type schema:DefinedTerm
85 N1dc9f2dd2521428daee48ed3ea77bb12 rdf:first sg:person.01171126363.81
86 rdf:rest N6ca874203816498db19563fcf3b49ed6
87 N267af8759bf24ead83416ff32ced9b62 schema:name readcube_id
88 schema:value 6c0dffbc766f9efd6408a2a510c6837c0e8ef79bcb1e9b2cdc2153a9101a7fdb
89 rdf:type schema:PropertyValue
90 N295f571691e04c379abc97f982c8f872 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
91 schema:name Learning
92 rdf:type schema:DefinedTerm
93 N3c6539ec50cc43fd9306d46d6f0a13dc schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
94 schema:name Models, Statistical
95 rdf:type schema:DefinedTerm
96 N48918d1d1ad74378bd99b1c0189e9751 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
97 schema:name Humans
98 rdf:type schema:DefinedTerm
99 N6180aff873f54f719f02dfeb161110db schema:name nlm_unique_id
100 schema:value 101177984
101 rdf:type schema:PropertyValue
102 N65bef7a3cc294ff2a43fd95f4237e5c9 schema:name pubmed_id
103 schema:value 16683172
104 rdf:type schema:PropertyValue
105 N6ca874203816498db19563fcf3b49ed6 rdf:first sg:person.0730715063.17
106 rdf:rest rdf:nil
107 N7ff5172550f84731829939ef9eccb96e schema:issueNumber 2
108 rdf:type schema:PublicationIssue
109 N87ed9514a2ec42d986a3bde5ea10fc83 rdf:first sg:person.01151714670.22
110 rdf:rest N1dc9f2dd2521428daee48ed3ea77bb12
111 N8e6e2bc256b7411e9000452361042a04 schema:name Springer Nature - SN SciGraph project
112 rdf:type schema:Organization
113 N9147bacf1a104f27a347a6242d4e186a schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
114 schema:name Basal Ganglia
115 rdf:type schema:DefinedTerm
116 Nb93a3da7048744d4a6a5bdda8b92c7d1 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
117 schema:name Psychomotor Performance
118 rdf:type schema:DefinedTerm
119 Nce5a067bae9d4c98b9a9d6a7386aa6f7 schema:volumeNumber 7
120 rdf:type schema:PublicationVolume
121 Nd27058f834a243569118c3b0c6f1b0b5 schema:name doi
122 schema:value 10.1007/s10339-005-0028-4
123 rdf:type schema:PropertyValue
124 Ned392e095f1b40ebb06ded9372b803e0 schema:name dimensions_id
125 schema:value pub.1022681034
126 rdf:type schema:PropertyValue
127 Nee209236f7e94d04802dcbf1f57194d8 rdf:first sg:person.01217257611.11
128 rdf:rest N0e06c5acaf434dd09d1e09841a7f6a92
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:journal.1032322 schema:issn 1612-4782
136 1612-4790
137 schema:name Cognitive Processing
138 rdf:type schema:Periodical
139 sg:person.01151714670.22 schema:affiliation https://www.grid.ac/institutes/grid.5399.6
140 schema:familyName Meunier
141 schema:givenName Martine
142 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01151714670.22
143 rdf:type schema:Person
144 sg:person.01171126363.81 schema:affiliation https://www.grid.ac/institutes/grid.4444.0
145 schema:familyName Coquelin
146 schema:givenName Pierre-Arnaud
147 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01171126363.81
148 rdf:type schema:Person
149 sg:person.01217257611.11 schema:affiliation https://www.grid.ac/institutes/grid.416868.5
150 schema:familyName Hadj-Bouziane
151 schema:givenName Fadila
152 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01217257611.11
153 rdf:type schema:Person
154 sg:person.014732773366.11 schema:affiliation https://www.grid.ac/institutes/grid.4444.0
155 schema:familyName Frankowska
156 schema:givenName Hélène
157 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014732773366.11
158 rdf:type schema:Person
159 sg:person.0730715063.17 schema:affiliation https://www.grid.ac/institutes/grid.5399.6
160 schema:familyName Boussaoud
161 schema:givenName Driss
162 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0730715063.17
163 rdf:type schema:Person
164 sg:pub.10.1007/3-540-45873-5_30 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041369163
165 https://doi.org/10.1007/3-540-45873-5_30
166 rdf:type schema:CreativeWork
167 sg:pub.10.1007/978-1-4612-1592-9_4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034570490
168 https://doi.org/10.1007/978-1-4612-1592-9_4
169 rdf:type schema:CreativeWork
170 sg:pub.10.1007/bf00229650 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034892789
171 https://doi.org/10.1007/bf00229650
172 rdf:type schema:CreativeWork
173 sg:pub.10.1007/bf00229651 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028880666
174 https://doi.org/10.1007/bf00229651
175 rdf:type schema:CreativeWork
176 sg:pub.10.1007/bf00250573 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028634771
177 https://doi.org/10.1007/bf00250573
178 rdf:type schema:CreativeWork
179 sg:pub.10.1007/s002210000405 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040531047
180 https://doi.org/10.1007/s002210000405
181 rdf:type schema:CreativeWork
182 https://doi.org/10.1002/(sici)1098-1063(1999)9:2<101::aid-hipo3>3.0.co;2-l schema:sameAs https://app.dimensions.ai/details/publication/pub.1022147300
183 rdf:type schema:CreativeWork
184 https://doi.org/10.1006/jmaa.1996.0273 schema:sameAs https://app.dimensions.ai/details/publication/pub.1019199558
185 rdf:type schema:CreativeWork
186 https://doi.org/10.1016/0165-0173(94)00007-c schema:sameAs https://app.dimensions.ai/details/publication/pub.1013782478
187 rdf:type schema:CreativeWork
188 https://doi.org/10.1016/0166-2236(90)90105-j schema:sameAs https://app.dimensions.ai/details/publication/pub.1009318185
189 rdf:type schema:CreativeWork
190 https://doi.org/10.1016/0306-4522(94)90536-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1013930205
191 rdf:type schema:CreativeWork
192 https://doi.org/10.1016/j.jphysparis.2004.01.014 schema:sameAs https://app.dimensions.ai/details/publication/pub.1044078907
193 rdf:type schema:CreativeWork
194 https://doi.org/10.1016/j.neuron.2005.06.006 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043514293
195 rdf:type schema:CreativeWork
196 https://doi.org/10.1016/j.pneurobio.2003.12.001 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000504111
197 rdf:type schema:CreativeWork
198 https://doi.org/10.1016/s0079-6123(08)60353-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008064239
199 rdf:type schema:CreativeWork
200 https://doi.org/10.1016/s0079-6123(08)61349-7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027980632
201 rdf:type schema:CreativeWork
202 https://doi.org/10.1016/s0166-2236(00)01570-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007088116
203 rdf:type schema:CreativeWork
204 https://doi.org/10.1016/s0891-0618(00)00099-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012769597
205 rdf:type schema:CreativeWork
206 https://doi.org/10.1016/s0893-6080(99)00046-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016131651
207 rdf:type schema:CreativeWork
208 https://doi.org/10.1016/s0896-6273(02)00967-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023967151
209 rdf:type schema:CreativeWork
210 https://doi.org/10.1016/s1471-1931(00)00023-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028555962
211 rdf:type schema:CreativeWork
212 https://doi.org/10.1017/cbo9780511626258 schema:sameAs https://app.dimensions.ai/details/publication/pub.1098669259
213 rdf:type schema:CreativeWork
214 https://doi.org/10.1037/0735-7044.115.5.971 schema:sameAs https://app.dimensions.ai/details/publication/pub.1001416460
215 rdf:type schema:CreativeWork
216 https://doi.org/10.1093/brain/113.1.207 schema:sameAs https://app.dimensions.ai/details/publication/pub.1059438601
217 rdf:type schema:CreativeWork
218 https://doi.org/10.1093/cercor/12.10.1040 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050936869
219 rdf:type schema:CreativeWork
220 https://doi.org/10.1111/j.0953-816x.2003.03181.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1029759153
221 rdf:type schema:CreativeWork
222 https://doi.org/10.1111/j.1460-9568.1997.tb01382.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1007962130
223 rdf:type schema:CreativeWork
224 https://doi.org/10.1111/j.1460-9568.2004.03788.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1043404250
225 rdf:type schema:CreativeWork
226 https://doi.org/10.1126/science.1077349 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040552809
227 rdf:type schema:CreativeWork
228 https://doi.org/10.1137/s036301290036968x schema:sameAs https://app.dimensions.ai/details/publication/pub.1062880404
229 rdf:type schema:CreativeWork
230 https://doi.org/10.1139/cjpp-74-4-469 schema:sameAs https://app.dimensions.ai/details/publication/pub.1062890176
231 rdf:type schema:CreativeWork
232 https://doi.org/10.1139/y96-035 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043589326
233 rdf:type schema:CreativeWork
234 https://doi.org/10.1146/annurev.ne.09.030186.002041 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035901217
235 rdf:type schema:CreativeWork
236 https://doi.org/10.1152/jn.1992.67.1.145 schema:sameAs https://app.dimensions.ai/details/publication/pub.1076961004
237 rdf:type schema:CreativeWork
238 https://doi.org/10.1152/jn.1994.71.3.1151 schema:sameAs https://app.dimensions.ai/details/publication/pub.1082698987
239 rdf:type schema:CreativeWork
240 https://doi.org/10.1152/jn.1998.80.2.947 schema:sameAs https://app.dimensions.ai/details/publication/pub.1083306180
241 rdf:type schema:CreativeWork
242 https://doi.org/10.1152/jn.1998.80.2.964 schema:sameAs https://app.dimensions.ai/details/publication/pub.1083306181
243 rdf:type schema:CreativeWork
244 https://doi.org/10.1162/089976600300015961 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015123179
245 rdf:type schema:CreativeWork
246 https://doi.org/10.1201/9780203503584.sec3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021121493
247 rdf:type schema:CreativeWork
248 https://doi.org/10.1615/critrevneurobiol.v10.i3-4.30 schema:sameAs https://app.dimensions.ai/details/publication/pub.1068132164
249 rdf:type schema:CreativeWork
250 https://doi.org/10.23919/ecc.2001.7076351 schema:sameAs https://app.dimensions.ai/details/publication/pub.1105845937
251 rdf:type schema:CreativeWork
252 https://www.grid.ac/institutes/grid.416868.5 schema:alternateName National Institute of Mental Health
253 schema:name INCM UMR6193, CNRS& Aix-Marseille Université, 31 Chemin Jospeh Aiguier, 13402, Marseille, France
254 Laboratory of Brain and Cognition, NIMH, Bethesda, MD, USA
255 rdf:type schema:Organization
256 https://www.grid.ac/institutes/grid.4444.0 schema:alternateName French National Centre for Scientific Research
257 schema:name CNRS, CREA, Ecole Polytechnique, 1 rue Descartes, 75005, Paris, France
258 rdf:type schema:Organization
259 https://www.grid.ac/institutes/grid.5399.6 schema:alternateName Aix-Marseille University
260 schema:name INCM UMR6193, CNRS& Aix-Marseille Université, 31 Chemin Jospeh Aiguier, 13402, Marseille, France
261 rdf:type schema:Organization
 




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


...