Motor patterns during active electrosensory acquisition
Identifieur interne : 001021 ( Main/Curation ); précédent : 001020; suivant : 001022Motor patterns during active electrosensory acquisition
Auteurs : Volker Hofmann [Allemagne] ; Bart R. H. Geurten [Allemagne] ; Juan I. Sanguinetti-Scheck [Uruguay, Allemagne] ; Leonel G Mez-Sena [Uruguay] ; Jacob Engelmann [Allemagne]Source :
- Frontiers in Behavioral Neuroscience [ 1662-5153 ] ; 2014.
Abstract
Motor patterns displayed during active electrosensory acquisition of information seem to be an essential part of a sensory strategy by which weakly electric fish actively generate and shape sensory flow. These active sensing strategies are expected to adaptively optimize ongoing behavior with respect to either motor efficiency or sensory information gained. The tight link between the motor domain and sensory perception in active electrolocation make weakly electric fish like
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DOI: 10.3389/fnbeh.2014.00186
PubMed: 24904337
PubMed Central: 4036139
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Geurten</name><affiliation wicri:level="1"><nlm:aff id="aff2"><institution>Cellular Neurobiology, Schwann-Schleiden Research Centre, Georg-August-Universität</institution><country>Göttingen, Germany</country></nlm:aff><country xml:lang="fr">Allemagne</country><wicri:regionArea></wicri:regionArea><wicri:regionArea># see nlm:aff region in country</wicri:regionArea></affiliation></author><author><name sortKey="Sanguinetti Scheck, Juan I" sort="Sanguinetti Scheck, Juan I" uniqKey="Sanguinetti Scheck J" first="Juan I." last="Sanguinetti-Scheck">Juan I. Sanguinetti-Scheck</name><affiliation wicri:level="1"><nlm:aff id="aff3"><institution>Sección Biomatemática, Laboratorio de Neurociencias, Facultad de Ciencias, Universidad de la Republica</institution><country>Montevideo, Uruguay</country></nlm:aff><country xml:lang="fr">Uruguay</country><wicri:regionArea></wicri:regionArea><wicri:regionArea># see nlm:aff region in country</wicri:regionArea></affiliation><affiliation wicri:level="1"><nlm:aff id="aff4"><institution>Bernstein Center for Computational Neuroscience, Humboldt Universität Berlin</institution><country>Berlin, Germany</country></nlm:aff><country xml:lang="fr">Allemagne</country><wicri:regionArea></wicri:regionArea><wicri:regionArea># see nlm:aff region in country</wicri:regionArea></affiliation></author><author><name sortKey="G Mez Sena, Leonel" sort="G Mez Sena, Leonel" uniqKey="G Mez Sena L" first="Leonel" last="G Mez-Sena">Leonel G Mez-Sena</name><affiliation wicri:level="1"><nlm:aff id="aff3"><institution>Sección Biomatemática, Laboratorio de Neurociencias, Facultad de Ciencias, Universidad de la Republica</institution><country>Montevideo, Uruguay</country></nlm:aff><country xml:lang="fr">Uruguay</country><wicri:regionArea></wicri:regionArea><wicri:regionArea># see nlm:aff region in country</wicri:regionArea></affiliation></author><author><name sortKey="Engelmann, Jacob" sort="Engelmann, Jacob" uniqKey="Engelmann J" first="Jacob" last="Engelmann">Jacob Engelmann</name><affiliation wicri:level="1"><nlm:aff id="aff1"><institution>Active Sensing, Faculty of Biology, Cognitive Interaction Technology – Center of Excellence, Bielefeld University</institution><country>Bielefeld, Germany</country></nlm:aff><country xml:lang="fr">Allemagne</country><wicri:regionArea></wicri:regionArea><wicri:regionArea># see nlm:aff region in country</wicri:regionArea></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">24904337</idno><idno type="pmc">4036139</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4036139</idno><idno type="RBID">PMC:4036139</idno><idno type="doi">10.3389/fnbeh.2014.00186</idno><date when="2014">2014</date><idno type="wicri:Area/Pmc/Corpus">001C97</idno><idno type="wicri:Area/Pmc/Curation">001C97</idno><idno type="wicri:Area/Pmc/Checkpoint">000A98</idno><idno type="wicri:Area/Ncbi/Merge">003050</idno><idno type="wicri:Area/Ncbi/Curation">003050</idno><idno type="wicri:Area/Ncbi/Checkpoint">003050</idno><idno type="wicri:Area/Main/Merge">001022</idno><idno type="wicri:Area/Main/Curation">001021</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Motor patterns during active electrosensory acquisition</title><author><name sortKey="Hofmann, Volker" sort="Hofmann, Volker" uniqKey="Hofmann V" first="Volker" last="Hofmann">Volker Hofmann</name><affiliation wicri:level="1"><nlm:aff id="aff1"><institution>Active Sensing, Faculty of Biology, Cognitive Interaction Technology – Center of Excellence, Bielefeld University</institution><country>Bielefeld, Germany</country></nlm:aff><country xml:lang="fr">Allemagne</country><wicri:regionArea></wicri:regionArea><wicri:regionArea># see nlm:aff region in country</wicri:regionArea></affiliation></author><author><name sortKey="Geurten, Bart R H" sort="Geurten, Bart R H" uniqKey="Geurten B" first="Bart R. H." last="Geurten">Bart R. H. Geurten</name><affiliation wicri:level="1"><nlm:aff id="aff2"><institution>Cellular Neurobiology, Schwann-Schleiden Research Centre, Georg-August-Universität</institution><country>Göttingen, Germany</country></nlm:aff><country xml:lang="fr">Allemagne</country><wicri:regionArea></wicri:regionArea><wicri:regionArea># see nlm:aff region in country</wicri:regionArea></affiliation></author><author><name sortKey="Sanguinetti Scheck, Juan I" sort="Sanguinetti Scheck, Juan I" uniqKey="Sanguinetti Scheck J" first="Juan I." last="Sanguinetti-Scheck">Juan I. Sanguinetti-Scheck</name><affiliation wicri:level="1"><nlm:aff id="aff3"><institution>Sección Biomatemática, Laboratorio de Neurociencias, Facultad de Ciencias, Universidad de la Republica</institution><country>Montevideo, Uruguay</country></nlm:aff><country xml:lang="fr">Uruguay</country><wicri:regionArea></wicri:regionArea><wicri:regionArea># see nlm:aff region in country</wicri:regionArea></affiliation><affiliation wicri:level="1"><nlm:aff id="aff4"><institution>Bernstein Center for Computational Neuroscience, Humboldt Universität Berlin</institution><country>Berlin, Germany</country></nlm:aff><country xml:lang="fr">Allemagne</country><wicri:regionArea></wicri:regionArea><wicri:regionArea># see nlm:aff region in country</wicri:regionArea></affiliation></author><author><name sortKey="G Mez Sena, Leonel" sort="G Mez Sena, Leonel" uniqKey="G Mez Sena L" first="Leonel" last="G Mez-Sena">Leonel G Mez-Sena</name><affiliation wicri:level="1"><nlm:aff id="aff3"><institution>Sección Biomatemática, Laboratorio de Neurociencias, Facultad de Ciencias, Universidad de la Republica</institution><country>Montevideo, Uruguay</country></nlm:aff><country xml:lang="fr">Uruguay</country><wicri:regionArea></wicri:regionArea><wicri:regionArea># see nlm:aff region in country</wicri:regionArea></affiliation></author><author><name sortKey="Engelmann, Jacob" sort="Engelmann, Jacob" uniqKey="Engelmann J" first="Jacob" last="Engelmann">Jacob Engelmann</name><affiliation wicri:level="1"><nlm:aff id="aff1"><institution>Active Sensing, Faculty of Biology, Cognitive Interaction Technology – Center of Excellence, Bielefeld University</institution><country>Bielefeld, Germany</country></nlm:aff><country xml:lang="fr">Allemagne</country><wicri:regionArea></wicri:regionArea><wicri:regionArea># see nlm:aff region in country</wicri:regionArea></affiliation></author></analytic><series><title level="j">Frontiers in Behavioral Neuroscience</title><idno type="eISSN">1662-5153</idno><imprint><date when="2014">2014</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p>Motor patterns displayed during active electrosensory acquisition of information seem to be an essential part of a sensory strategy by which weakly electric fish actively generate and shape sensory flow. These active sensing strategies are expected to adaptively optimize ongoing behavior with respect to either motor efficiency or sensory information gained. The tight link between the motor domain and sensory perception in active electrolocation make weakly electric fish like <italic>Gnathonemus petersii</italic> an ideal system for studying sensory-motor interactions in the form of active sensing strategies. Analyzing the movements and electric signals of solitary fish during unrestrained exploration of objects in the dark, we here present the first formal quantification of motor patterns used by fish during electrolocation. Based on a cluster analysis of the kinematic values we categorized the basic units of motion. These were then analyzed for their associative grouping to identify and extract short coherent chains of behavior. This enabled the description of sensory behavior on different levels of complexity: from single movements, over short behaviors to more complex behavioral sequences during which the kinematics alter between different behaviors. We present detailed data for three classified patterns and provide evidence that these can be considered as motor components of active sensing strategies. In accordance with the idea of active sensing strategies, we found categorical motor patterns to be modified by the sensory context. In addition these motor patterns were linked with changes in the temporal sampling in form of differing electric organ discharge frequencies and differing spatial distributions. The ability to detect such strategies quantitatively will allow future research to investigate the impact of such behaviors on sensing.</p></div></front><back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Arthur, D" uniqKey="Arthur D">D. 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