Electric Imaging through Evolution, a Modeling Study of Commonalities and Differences
Identifieur interne : 001247 ( Main/Curation ); précédent : 001246; suivant : 001248Electric Imaging through Evolution, a Modeling Study of Commonalities and Differences
Auteurs : Federico Pedraja [Uruguay] ; Pedro Aguilera [Uruguay] ; Angel A. Caputi [Uruguay] ; Ruben Budelli [Uruguay]Source :
- PLoS Computational Biology [ 1553-734X ] ; 2014.
Abstract
Modeling the electric field and images in electric fish contributes to a better understanding of the pre-receptor conditioning of electric images. Although the boundary element method has been very successful for calculating images and fields, complex electric organ discharges pose a challenge for active electroreception modeling. We have previously developed a direct method for calculating electric images which takes into account the structure and physiology of the electric organ as well as the geometry and resistivity of fish tissues. The present article reports a general application of our simulator for studying electric images in electric fish with heterogeneous, extended electric organs. We studied three species of Gymnotiformes, including both wave-type (
Url:
DOI: 10.1371/journal.pcbi.1003722
PubMed: 25010765
PubMed Central: 4091691
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Caputi</name><affiliation wicri:level="1"><nlm:aff id="aff2"><addr-line>Departamento de Neurociencias Integrativas y Computacionales, Instituto de Investigaciones Biológicas Clemente Estable, Montevideo, Uruguay</addr-line></nlm:aff><country xml:lang="fr">Uruguay</country><wicri:regionArea>Departamento de Neurociencias Integrativas y Computacionales, Instituto de Investigaciones Biológicas Clemente Estable, Montevideo</wicri:regionArea><wicri:noRegion>Montevideo</wicri:noRegion></affiliation></author><author><name sortKey="Budelli, Ruben" sort="Budelli, Ruben" uniqKey="Budelli R" first="Ruben" last="Budelli">Ruben Budelli</name><affiliation wicri:level="1"><nlm:aff id="aff1"><addr-line>Departamento de Biología Celular y Molecular, Facultad de Ciencias, Universidad de la República, Montevideo, Uruguay</addr-line></nlm:aff><country xml:lang="fr">Uruguay</country><wicri:regionArea>Departamento de Biología Celular y Molecular, Facultad de Ciencias, Universidad de la República, Montevideo</wicri:regionArea><wicri:noRegion>Montevideo</wicri:noRegion></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">25010765</idno><idno type="pmc">4091691</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4091691</idno><idno type="RBID">PMC:4091691</idno><idno type="doi">10.1371/journal.pcbi.1003722</idno><date when="2014">2014</date><idno type="wicri:Area/Pmc/Corpus">000542</idno><idno type="wicri:Area/Pmc/Curation">000542</idno><idno type="wicri:Area/Pmc/Checkpoint">000C64</idno><idno type="wicri:Area/Ncbi/Merge">003135</idno><idno type="wicri:Area/Ncbi/Curation">003135</idno><idno type="wicri:Area/Ncbi/Checkpoint">003135</idno><idno type="wicri:doubleKey">1553-734X:2014:Pedraja F:electric:imaging:through</idno><idno type="wicri:Area/Main/Merge">001251</idno><idno type="wicri:Area/Main/Curation">001247</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Electric Imaging through Evolution, a Modeling Study of Commonalities and Differences</title><author><name sortKey="Pedraja, Federico" sort="Pedraja, Federico" uniqKey="Pedraja F" first="Federico" last="Pedraja">Federico Pedraja</name><affiliation wicri:level="1"><nlm:aff id="aff1"><addr-line>Departamento de Biología Celular y Molecular, Facultad de Ciencias, Universidad de la República, Montevideo, Uruguay</addr-line></nlm:aff><country xml:lang="fr">Uruguay</country><wicri:regionArea>Departamento de Biología Celular y Molecular, Facultad de Ciencias, Universidad de la República, Montevideo</wicri:regionArea><wicri:noRegion>Montevideo</wicri:noRegion></affiliation></author><author><name sortKey="Aguilera, Pedro" sort="Aguilera, Pedro" uniqKey="Aguilera P" first="Pedro" last="Aguilera">Pedro Aguilera</name><affiliation wicri:level="1"><nlm:aff id="aff2"><addr-line>Departamento de Neurociencias Integrativas y Computacionales, Instituto de Investigaciones Biológicas Clemente Estable, Montevideo, Uruguay</addr-line></nlm:aff><country xml:lang="fr">Uruguay</country><wicri:regionArea>Departamento de Neurociencias Integrativas y Computacionales, Instituto de Investigaciones Biológicas Clemente Estable, Montevideo</wicri:regionArea><wicri:noRegion>Montevideo</wicri:noRegion></affiliation></author><author><name sortKey="Caputi, Angel A" sort="Caputi, Angel A" uniqKey="Caputi A" first="Angel A." last="Caputi">Angel A. Caputi</name><affiliation wicri:level="1"><nlm:aff id="aff2"><addr-line>Departamento de Neurociencias Integrativas y Computacionales, Instituto de Investigaciones Biológicas Clemente Estable, Montevideo, Uruguay</addr-line></nlm:aff><country xml:lang="fr">Uruguay</country><wicri:regionArea>Departamento de Neurociencias Integrativas y Computacionales, Instituto de Investigaciones Biológicas Clemente Estable, Montevideo</wicri:regionArea><wicri:noRegion>Montevideo</wicri:noRegion></affiliation></author><author><name sortKey="Budelli, Ruben" sort="Budelli, Ruben" uniqKey="Budelli R" first="Ruben" last="Budelli">Ruben Budelli</name><affiliation wicri:level="1"><nlm:aff id="aff1"><addr-line>Departamento de Biología Celular y Molecular, Facultad de Ciencias, Universidad de la República, Montevideo, Uruguay</addr-line></nlm:aff><country xml:lang="fr">Uruguay</country><wicri:regionArea>Departamento de Biología Celular y Molecular, Facultad de Ciencias, Universidad de la República, Montevideo</wicri:regionArea><wicri:noRegion>Montevideo</wicri:noRegion></affiliation></author></analytic><series><title level="j">PLoS Computational Biology</title><idno type="ISSN">1553-734X</idno><idno type="eISSN">1553-7358</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>Modeling the electric field and images in electric fish contributes to a better understanding of the pre-receptor conditioning of electric images. Although the boundary element method has been very successful for calculating images and fields, complex electric organ discharges pose a challenge for active electroreception modeling. We have previously developed a direct method for calculating electric images which takes into account the structure and physiology of the electric organ as well as the geometry and resistivity of fish tissues. The present article reports a general application of our simulator for studying electric images in electric fish with heterogeneous, extended electric organs. We studied three species of Gymnotiformes, including both wave-type (<italic>Apteronotus albifrons</italic>) and pulse-type <italic>(Gymnotus obscurus</italic> and <italic>Gymnotus coropinae</italic>) fish, with electric organs of different complexity. The results are compared with the African (<italic>Gnathonemus petersii</italic>) and American (<italic>Gymnotus omarorum</italic>) electric fish studied previously. We address the following issues: 1) how to calculate equivalent source distributions based on experimental measurements, 2) how the complexity of the electric organ discharge determines the features of the electric field and 3) how the basal field determines the characteristics of electric images. Our findings allow us to generalize the hypothesis (previously posed for <italic>G. omarorum</italic>) in which the perioral region and the rest of the body play different sensory roles. While the “electrosensory fovea” appears suitable for exploring objects in detail, the rest of the body is likened to a “peripheral retina” for detecting the presence and movement of surrounding objects. We discuss the commonalities and differences between species. Compared to African species, American electric fish show a weaker field. This feature, derived from the complexity of distributed electric organs, may endow Gymnotiformes with the ability to emit site-specific signals to be detected in the short range by a conspecific and the possibility to evolve predator avoidance strategies.</p></div></front><back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Lissmann, Hw" uniqKey="Lissmann H">HW Lissmann</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Lissmann, Hw" uniqKey="Lissmann H">HW Lissmann</name></author><author><name sortKey="Machin, Ke" uniqKey="Machin K">KE Machin</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Bullock, Th" uniqKey="Bullock T">TH Bullock</name></author><author><name sortKey="Chichibu, S" uniqKey="Chichibu S">S Chichibu</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Knudsen, Ei" uniqKey="Knudsen E">EI 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Macadar</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Stoddard, Pk" uniqKey="Stoddard P">PK Stoddard</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Caputi, A" uniqKey="Caputi A">A Caputi</name></author><author><name sortKey="Silva, A" uniqKey="Silva A">A Silva</name></author><author><name sortKey="Macadar, O" uniqKey="Macadar O">O Macadar</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Bacher, M" uniqKey="Bacher M">M Bacher</name></author></analytic></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct></listBibl></div1></back></TEI></record>Pour manipuler ce document sous Unix (Dilib)
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