Error generalization as a function of velocity and duration: human reaching movements View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2008-03

AUTHORS

Joseph T. Francis

ABSTRACT

Our sensory-motor control system has a remarkable ability to adapt to novel dynamics during reaching movements and generalizes this adaptation to movements made in different directions, positions and even speeds. The degree and pattern of this generalization are of great importance in deducing the underlying mechanisms that govern our motor control. In this report we expand our knowledge on the generalization between movements made at different speeds. We wished to determine the pattern of generalization between different speed and duration movements on a trial-by-trial basis. In addition, we tested three hypotheses for the pattern of generalization. The first hypothesis was that the generalization was maximum for the speed of the movement just made with a linear decrease in generalization as one moves away from that preferred speed. The second was that the generalization is always highest for the fastest speed movements and linearly decreases with speed. The last hypothesis came from our preliminary results, which suggested that the generalization plateaus. Human subjects made targeted reaching movements at four different maximum speeds (15, 35, 55 and 75 cm/s) presented in pseudorandom order to one spatial target (15 cm extent) while holding onto a robotic manipulandum that produced a viscous curl field. Catch trials (trial where the curl field was unexpectedly removed) were used to probe the generalization between the four speed/durations on a movement-by-movement basis. We found that the pattern of generalization was linear between the first three speed categories (15-55 cm/s), but plateaued after the 55 cm/s category. We compared the subjects' results with a simulated adaptive controller that used a population code by combining the output of basis elements. These basis elements encoded limb velocity and associated this with a force expectation at that velocity. We found that using a basis set of Gaussians the adaptive controller produced movements that generalized in virtually the exact manner as the subjects, as we have previously demonstrated for movements made to different spatial targets. Thus, the human internal model may employ such a population code. More... »

PAGES

23-37

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s00221-007-1202-y

DOI

http://dx.doi.org/10.1007/s00221-007-1202-y

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1039663100

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/18030456


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/2008/1109", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Neurosciences", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/11", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Medical and Health Sciences", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Adult", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Arm", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Hand", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Humans", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Models, Biological", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Motor Activity", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Movement", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Psychomotor Performance", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Reaction Time", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Robotics", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Space Perception", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "SUNY Downstate Medical Center", 
          "id": "https://www.grid.ac/institutes/grid.262863.b", 
          "name": [
            "Department of Physiology and Pharmacology, State University of New York Downstate School of Medicine, 450 Clarkson Ave., 11203, Brooklyn, NY, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Francis", 
        "givenName": "Joseph T.", 
        "id": "sg:person.01160760024.44", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01160760024.44"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1371/journal.pbio.0020330", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1002821624"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00221-005-0062-6", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1004388872", 
          "https://doi.org/10.1007/s00221-005-0062-6"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00221-005-0062-6", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1004388872", 
          "https://doi.org/10.1007/s00221-005-0062-6"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/35037588", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1005827456", 
          "https://doi.org/10.1038/35037588"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/35037588", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1005827456", 
          "https://doi.org/10.1038/35037588"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1152/jn.01281.2006", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1006213915"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/81469", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1009484325", 
          "https://doi.org/10.1038/81469"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/81469", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1009484325", 
          "https://doi.org/10.1038/81469"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1073/pnas.93.9.3843", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1010207007"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/29528", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1010313110", 
          "https://doi.org/10.1038/29528"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/29528", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1010313110", 
          "https://doi.org/10.1038/29528"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1152/jn.01020.2002", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1021511981"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1152/jn.01112.2002", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029335422"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00221-005-2231-z", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1032590967", 
          "https://doi.org/10.1007/s00221-005-2231-z"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00221-005-2231-z", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1032590967", 
          "https://doi.org/10.1007/s00221-005-2231-z"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1152/jn.00307.2006", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1034560390"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1152/jn.00519.2003", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1034613762"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1152/jn.00779.2002", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1035971045"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf00204593", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1042513593", 
          "https://doi.org/10.1007/bf00204593"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf00204593", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1042513593", 
          "https://doi.org/10.1007/bf00204593"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1152/jn.1999.81.5.2140", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1074455430"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1152/jn.1999.82.5.2676", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1074549994"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1152/jn.2001.86.2.971", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1074861599"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1523/jneurosci.23-27-09032.2003", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1076578217"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/iembs.2004.1404249", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1077364184"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1523/jneurosci.08-08-02928.1988", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1079730274"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1523/jneurosci.05-07-01688.1985", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1080085642"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1152/jn.1968.31.1.14", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1080718829"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1523/jneurosci.02-11-01527.1982", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1082174034"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1152/jn.1994.72.1.299", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1082585279"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1523/jneurosci.14-05-03208.1994", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1082690177"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1152/jn.1993.70.5.2097", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1082743199"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1523/jneurosci.17-04-01481.1997", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1083036620"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1152/jn.1998.79.4.1825", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1083240494"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2008-03", 
    "datePublishedReg": "2008-03-01", 
    "description": "Our sensory-motor control system has a remarkable ability to adapt to novel dynamics during reaching movements and generalizes this adaptation to movements made in different directions, positions and even speeds. The degree and pattern of this generalization are of great importance in deducing the underlying mechanisms that govern our motor control. In this report we expand our knowledge on the generalization between movements made at different speeds. We wished to determine the pattern of generalization between different speed and duration movements on a trial-by-trial basis. In addition, we tested three hypotheses for the pattern of generalization. The first hypothesis was that the generalization was maximum for the speed of the movement just made with a linear decrease in generalization as one moves away from that preferred speed. The second was that the generalization is always highest for the fastest speed movements and linearly decreases with speed. The last hypothesis came from our preliminary results, which suggested that the generalization plateaus. Human subjects made targeted reaching movements at four different maximum speeds (15, 35, 55 and 75 cm/s) presented in pseudorandom order to one spatial target (15 cm extent) while holding onto a robotic manipulandum that produced a viscous curl field. Catch trials (trial where the curl field was unexpectedly removed) were used to probe the generalization between the four speed/durations on a movement-by-movement basis. We found that the pattern of generalization was linear between the first three speed categories (15-55 cm/s), but plateaued after the 55 cm/s category. We compared the subjects' results with a simulated adaptive controller that used a population code by combining the output of basis elements. These basis elements encoded limb velocity and associated this with a force expectation at that velocity. We found that using a basis set of Gaussians the adaptive controller produced movements that generalized in virtually the exact manner as the subjects, as we have previously demonstrated for movements made to different spatial targets. Thus, the human internal model may employ such a population code.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1007/s00221-007-1202-y", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isFundedItemOf": [
      {
        "id": "sg:grant.2558746", 
        "type": "MonetaryGrant"
      }
    ], 
    "isPartOf": [
      {
        "id": "sg:journal.1005581", 
        "issn": [
          "0014-4819", 
          "1432-1106"
        ], 
        "name": "Experimental Brain Research", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "1", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "186"
      }
    ], 
    "name": "Error generalization as a function of velocity and duration: human reaching movements", 
    "pagination": "23-37", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "bcefe71a284c795f5ae6c9e64a367f158558dc432007884a5ee8940bbfbed8ed"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "18030456"
        ]
      }, 
      {
        "name": "nlm_unique_id", 
        "type": "PropertyValue", 
        "value": [
          "0043312"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s00221-007-1202-y"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1039663100"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s00221-007-1202-y", 
      "https://app.dimensions.ai/details/publication/pub.1039663100"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-11T14:34", 
    "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/v90/0000000373_0000000373/records_13106_00000001.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "http://link.springer.com/10.1007%2Fs00221-007-1202-y"
  }
]
 

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/s00221-007-1202-y'

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/s00221-007-1202-y'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s00221-007-1202-y'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s00221-007-1202-y'


 

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

205 TRIPLES      21 PREDICATES      68 URIs      32 LITERALS      20 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s00221-007-1202-y schema:about N269b7e2c1ab64580b2af6f565656ea73
2 N378be05933c5468a9a945a56f2250901
3 N4b95ed80786e47a7bd36fdb08e50e327
4 N59aaa900d8db4faf8287d40796c72ebd
5 N8e508775414646f5b7bfdc13f0bbc4a0
6 N921736857b244473b3e0130d41f01a4e
7 Nb7dc3843ad9d42cebd287ed95db2300b
8 Nd36ed346d9cb4464bd2048da7c667c6a
9 Nd7e29ba92a474f6ba79e35314f3b5a16
10 Ne9126993ecf041fb9b3ccf22c5a8bf81
11 Nf069c1dd8b09455b8e823f851055a0f3
12 anzsrc-for:11
13 anzsrc-for:1109
14 schema:author Nc4cc101d570947bd8ce433ae791fda62
15 schema:citation sg:pub.10.1007/bf00204593
16 sg:pub.10.1007/s00221-005-0062-6
17 sg:pub.10.1007/s00221-005-2231-z
18 sg:pub.10.1038/29528
19 sg:pub.10.1038/35037588
20 sg:pub.10.1038/81469
21 https://doi.org/10.1073/pnas.93.9.3843
22 https://doi.org/10.1109/iembs.2004.1404249
23 https://doi.org/10.1152/jn.00307.2006
24 https://doi.org/10.1152/jn.00519.2003
25 https://doi.org/10.1152/jn.00779.2002
26 https://doi.org/10.1152/jn.01020.2002
27 https://doi.org/10.1152/jn.01112.2002
28 https://doi.org/10.1152/jn.01281.2006
29 https://doi.org/10.1152/jn.1968.31.1.14
30 https://doi.org/10.1152/jn.1993.70.5.2097
31 https://doi.org/10.1152/jn.1994.72.1.299
32 https://doi.org/10.1152/jn.1998.79.4.1825
33 https://doi.org/10.1152/jn.1999.81.5.2140
34 https://doi.org/10.1152/jn.1999.82.5.2676
35 https://doi.org/10.1152/jn.2001.86.2.971
36 https://doi.org/10.1371/journal.pbio.0020330
37 https://doi.org/10.1523/jneurosci.02-11-01527.1982
38 https://doi.org/10.1523/jneurosci.05-07-01688.1985
39 https://doi.org/10.1523/jneurosci.08-08-02928.1988
40 https://doi.org/10.1523/jneurosci.14-05-03208.1994
41 https://doi.org/10.1523/jneurosci.17-04-01481.1997
42 https://doi.org/10.1523/jneurosci.23-27-09032.2003
43 schema:datePublished 2008-03
44 schema:datePublishedReg 2008-03-01
45 schema:description Our sensory-motor control system has a remarkable ability to adapt to novel dynamics during reaching movements and generalizes this adaptation to movements made in different directions, positions and even speeds. The degree and pattern of this generalization are of great importance in deducing the underlying mechanisms that govern our motor control. In this report we expand our knowledge on the generalization between movements made at different speeds. We wished to determine the pattern of generalization between different speed and duration movements on a trial-by-trial basis. In addition, we tested three hypotheses for the pattern of generalization. The first hypothesis was that the generalization was maximum for the speed of the movement just made with a linear decrease in generalization as one moves away from that preferred speed. The second was that the generalization is always highest for the fastest speed movements and linearly decreases with speed. The last hypothesis came from our preliminary results, which suggested that the generalization plateaus. Human subjects made targeted reaching movements at four different maximum speeds (15, 35, 55 and 75 cm/s) presented in pseudorandom order to one spatial target (15 cm extent) while holding onto a robotic manipulandum that produced a viscous curl field. Catch trials (trial where the curl field was unexpectedly removed) were used to probe the generalization between the four speed/durations on a movement-by-movement basis. We found that the pattern of generalization was linear between the first three speed categories (15-55 cm/s), but plateaued after the 55 cm/s category. We compared the subjects' results with a simulated adaptive controller that used a population code by combining the output of basis elements. These basis elements encoded limb velocity and associated this with a force expectation at that velocity. We found that using a basis set of Gaussians the adaptive controller produced movements that generalized in virtually the exact manner as the subjects, as we have previously demonstrated for movements made to different spatial targets. Thus, the human internal model may employ such a population code.
46 schema:genre research_article
47 schema:inLanguage en
48 schema:isAccessibleForFree false
49 schema:isPartOf N2e1633d1cdcf4d3a8eca358e9e75bc78
50 N3f1d8f965d334d5ebb6acfb39b8dfea9
51 sg:journal.1005581
52 schema:name Error generalization as a function of velocity and duration: human reaching movements
53 schema:pagination 23-37
54 schema:productId N611ba0e83cb6449a87daa8c4bbb10049
55 Nd35ffffe2b294e03bc90420eece346c5
56 Ne3159047eb164c04b75f58bfa5711d74
57 Ne39870743fed46edb230b136a7a3ea9a
58 Nf97a59d1cd96435d867e6f8731ef7265
59 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039663100
60 https://doi.org/10.1007/s00221-007-1202-y
61 schema:sdDatePublished 2019-04-11T14:34
62 schema:sdLicense https://scigraph.springernature.com/explorer/license/
63 schema:sdPublisher Nef08dcbd25db44e28f07d13ebdf5d4f1
64 schema:url http://link.springer.com/10.1007%2Fs00221-007-1202-y
65 sgo:license sg:explorer/license/
66 sgo:sdDataset articles
67 rdf:type schema:ScholarlyArticle
68 N269b7e2c1ab64580b2af6f565656ea73 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
69 schema:name Movement
70 rdf:type schema:DefinedTerm
71 N2e1633d1cdcf4d3a8eca358e9e75bc78 schema:issueNumber 1
72 rdf:type schema:PublicationIssue
73 N378be05933c5468a9a945a56f2250901 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
74 schema:name Hand
75 rdf:type schema:DefinedTerm
76 N3f1d8f965d334d5ebb6acfb39b8dfea9 schema:volumeNumber 186
77 rdf:type schema:PublicationVolume
78 N4b95ed80786e47a7bd36fdb08e50e327 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
79 schema:name Arm
80 rdf:type schema:DefinedTerm
81 N59aaa900d8db4faf8287d40796c72ebd schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
82 schema:name Robotics
83 rdf:type schema:DefinedTerm
84 N611ba0e83cb6449a87daa8c4bbb10049 schema:name readcube_id
85 schema:value bcefe71a284c795f5ae6c9e64a367f158558dc432007884a5ee8940bbfbed8ed
86 rdf:type schema:PropertyValue
87 N8e508775414646f5b7bfdc13f0bbc4a0 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
88 schema:name Space Perception
89 rdf:type schema:DefinedTerm
90 N921736857b244473b3e0130d41f01a4e schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
91 schema:name Adult
92 rdf:type schema:DefinedTerm
93 Nb7dc3843ad9d42cebd287ed95db2300b schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
94 schema:name Psychomotor Performance
95 rdf:type schema:DefinedTerm
96 Nc4cc101d570947bd8ce433ae791fda62 rdf:first sg:person.01160760024.44
97 rdf:rest rdf:nil
98 Nd35ffffe2b294e03bc90420eece346c5 schema:name dimensions_id
99 schema:value pub.1039663100
100 rdf:type schema:PropertyValue
101 Nd36ed346d9cb4464bd2048da7c667c6a schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
102 schema:name Reaction Time
103 rdf:type schema:DefinedTerm
104 Nd7e29ba92a474f6ba79e35314f3b5a16 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
105 schema:name Motor Activity
106 rdf:type schema:DefinedTerm
107 Ne3159047eb164c04b75f58bfa5711d74 schema:name doi
108 schema:value 10.1007/s00221-007-1202-y
109 rdf:type schema:PropertyValue
110 Ne39870743fed46edb230b136a7a3ea9a schema:name pubmed_id
111 schema:value 18030456
112 rdf:type schema:PropertyValue
113 Ne9126993ecf041fb9b3ccf22c5a8bf81 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
114 schema:name Humans
115 rdf:type schema:DefinedTerm
116 Nef08dcbd25db44e28f07d13ebdf5d4f1 schema:name Springer Nature - SN SciGraph project
117 rdf:type schema:Organization
118 Nf069c1dd8b09455b8e823f851055a0f3 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
119 schema:name Models, Biological
120 rdf:type schema:DefinedTerm
121 Nf97a59d1cd96435d867e6f8731ef7265 schema:name nlm_unique_id
122 schema:value 0043312
123 rdf:type schema:PropertyValue
124 anzsrc-for:11 schema:inDefinedTermSet anzsrc-for:
125 schema:name Medical and Health Sciences
126 rdf:type schema:DefinedTerm
127 anzsrc-for:1109 schema:inDefinedTermSet anzsrc-for:
128 schema:name Neurosciences
129 rdf:type schema:DefinedTerm
130 sg:grant.2558746 http://pending.schema.org/fundedItem sg:pub.10.1007/s00221-007-1202-y
131 rdf:type schema:MonetaryGrant
132 sg:journal.1005581 schema:issn 0014-4819
133 1432-1106
134 schema:name Experimental Brain Research
135 rdf:type schema:Periodical
136 sg:person.01160760024.44 schema:affiliation https://www.grid.ac/institutes/grid.262863.b
137 schema:familyName Francis
138 schema:givenName Joseph T.
139 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01160760024.44
140 rdf:type schema:Person
141 sg:pub.10.1007/bf00204593 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042513593
142 https://doi.org/10.1007/bf00204593
143 rdf:type schema:CreativeWork
144 sg:pub.10.1007/s00221-005-0062-6 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004388872
145 https://doi.org/10.1007/s00221-005-0062-6
146 rdf:type schema:CreativeWork
147 sg:pub.10.1007/s00221-005-2231-z schema:sameAs https://app.dimensions.ai/details/publication/pub.1032590967
148 https://doi.org/10.1007/s00221-005-2231-z
149 rdf:type schema:CreativeWork
150 sg:pub.10.1038/29528 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010313110
151 https://doi.org/10.1038/29528
152 rdf:type schema:CreativeWork
153 sg:pub.10.1038/35037588 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005827456
154 https://doi.org/10.1038/35037588
155 rdf:type schema:CreativeWork
156 sg:pub.10.1038/81469 schema:sameAs https://app.dimensions.ai/details/publication/pub.1009484325
157 https://doi.org/10.1038/81469
158 rdf:type schema:CreativeWork
159 https://doi.org/10.1073/pnas.93.9.3843 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010207007
160 rdf:type schema:CreativeWork
161 https://doi.org/10.1109/iembs.2004.1404249 schema:sameAs https://app.dimensions.ai/details/publication/pub.1077364184
162 rdf:type schema:CreativeWork
163 https://doi.org/10.1152/jn.00307.2006 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034560390
164 rdf:type schema:CreativeWork
165 https://doi.org/10.1152/jn.00519.2003 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034613762
166 rdf:type schema:CreativeWork
167 https://doi.org/10.1152/jn.00779.2002 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035971045
168 rdf:type schema:CreativeWork
169 https://doi.org/10.1152/jn.01020.2002 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021511981
170 rdf:type schema:CreativeWork
171 https://doi.org/10.1152/jn.01112.2002 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029335422
172 rdf:type schema:CreativeWork
173 https://doi.org/10.1152/jn.01281.2006 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006213915
174 rdf:type schema:CreativeWork
175 https://doi.org/10.1152/jn.1968.31.1.14 schema:sameAs https://app.dimensions.ai/details/publication/pub.1080718829
176 rdf:type schema:CreativeWork
177 https://doi.org/10.1152/jn.1993.70.5.2097 schema:sameAs https://app.dimensions.ai/details/publication/pub.1082743199
178 rdf:type schema:CreativeWork
179 https://doi.org/10.1152/jn.1994.72.1.299 schema:sameAs https://app.dimensions.ai/details/publication/pub.1082585279
180 rdf:type schema:CreativeWork
181 https://doi.org/10.1152/jn.1998.79.4.1825 schema:sameAs https://app.dimensions.ai/details/publication/pub.1083240494
182 rdf:type schema:CreativeWork
183 https://doi.org/10.1152/jn.1999.81.5.2140 schema:sameAs https://app.dimensions.ai/details/publication/pub.1074455430
184 rdf:type schema:CreativeWork
185 https://doi.org/10.1152/jn.1999.82.5.2676 schema:sameAs https://app.dimensions.ai/details/publication/pub.1074549994
186 rdf:type schema:CreativeWork
187 https://doi.org/10.1152/jn.2001.86.2.971 schema:sameAs https://app.dimensions.ai/details/publication/pub.1074861599
188 rdf:type schema:CreativeWork
189 https://doi.org/10.1371/journal.pbio.0020330 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002821624
190 rdf:type schema:CreativeWork
191 https://doi.org/10.1523/jneurosci.02-11-01527.1982 schema:sameAs https://app.dimensions.ai/details/publication/pub.1082174034
192 rdf:type schema:CreativeWork
193 https://doi.org/10.1523/jneurosci.05-07-01688.1985 schema:sameAs https://app.dimensions.ai/details/publication/pub.1080085642
194 rdf:type schema:CreativeWork
195 https://doi.org/10.1523/jneurosci.08-08-02928.1988 schema:sameAs https://app.dimensions.ai/details/publication/pub.1079730274
196 rdf:type schema:CreativeWork
197 https://doi.org/10.1523/jneurosci.14-05-03208.1994 schema:sameAs https://app.dimensions.ai/details/publication/pub.1082690177
198 rdf:type schema:CreativeWork
199 https://doi.org/10.1523/jneurosci.17-04-01481.1997 schema:sameAs https://app.dimensions.ai/details/publication/pub.1083036620
200 rdf:type schema:CreativeWork
201 https://doi.org/10.1523/jneurosci.23-27-09032.2003 schema:sameAs https://app.dimensions.ai/details/publication/pub.1076578217
202 rdf:type schema:CreativeWork
203 https://www.grid.ac/institutes/grid.262863.b schema:alternateName SUNY Downstate Medical Center
204 schema:name Department of Physiology and Pharmacology, State University of New York Downstate School of Medicine, 450 Clarkson Ave., 11203, Brooklyn, NY, USA
205 rdf:type schema:Organization
 




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


...