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Are biological neurons that vicious ? Or only their models ?

Λεπτομέρειες βιβλιογραφικής εγγραφής
Τίτλος: Are biological neurons that vicious ? Or only their models ?
Συγγραφείς: Viéville, Thierry, Cessac, Bruno
Συνεισφορές: Centre Inria d'Université Côte d'Azur, Institut National de Recherche en Informatique et en Automatique (Inria), Université Nice Sophia Antipolis (1965 - 2019) (UNS), Neuromimetic intelligence (CORTEX), INRIA Lorraine, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université Henri Poincaré - Nancy 1 (UHP)-Université Nancy 2-Institut National Polytechnique de Lorraine (INPL)-Centre National de la Recherche Scientifique (CNRS)-Université Henri Poincaré - Nancy 1 (UHP)-Université Nancy 2-Institut National Polytechnique de Lorraine (INPL)-Centre National de la Recherche Scientifique (CNRS), Institut Non Linéaire de Nice Sophia-Antipolis (INLN), Université Nice Sophia Antipolis (1965 - 2019) (UNS)-Centre National de la Recherche Scientifique (CNRS)
Πηγή: https://hal.science/hal-00176200 ; 2007.
Στοιχεία εκδότη: CCSD
Έτος έκδοσης: 2007
Συλλογή: Université de Lorraine: HAL
Θεματικοί όροι: [PHYS.PHYS.PHYS-BIO-PH]Physics [physics]/Physics [physics]/Biological Physics [physics.bio-ph], [PHYS.PHYS.PHYS-COMP-PH]Physics [physics]/Physics [physics]/Computational Physics [physics.comp-ph]
Περιγραφή: 32 pages, 12 figures, submited ; With care, and keeping in mind that the biological plausibility of neuronal models with respect to the real brain activity is still an open question, we revisit some mathematical and numerical aspects of generalized Integrate and Fire (gIF) models and propose to eliminate assumptions related to spurious discontinuities. This concerns both the fire regime and then the integrate regime of the neuron. With this new point of view, some ``biological'' results obtained on ``models'' are to be reconsidered. This has also positive consequences. It allows us to reduce the bio-physical membrane equation to a very simple but powerful gIF numerical model. This also dramatically reduces the algorithmic complexity of event-based network simulations, as experimented here.
Τύπος εγγράφου: report
Γλώσσα: English
Relation: info:eu-repo/semantics/altIdentifier/arxiv/0709.4367; ARXIV: 0709.4367
Διαθεσιμότητα: https://hal.science/hal-00176200
Αριθμός Καταχώρησης: edsbas.D60B03AA
Βάση Δεδομένων: BASE
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  – Url: https://hal.science/hal-00176200#
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  Data: Are biological neurons that vicious ? Or only their models ?
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  Data: <searchLink fieldCode="AR" term="%22Viéville%2C+Thierry%22">Viéville, Thierry</searchLink><br /><searchLink fieldCode="AR" term="%22Cessac%2C+Bruno%22">Cessac, Bruno</searchLink>
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  Data: Centre Inria d'Université Côte d'Azur<br />Institut National de Recherche en Informatique et en Automatique (Inria)<br />Université Nice Sophia Antipolis (1965 - 2019) (UNS)<br />Neuromimetic intelligence (CORTEX)<br />INRIA Lorraine<br />Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA)<br />Institut National de Recherche en Informatique et en Automatique (Inria)-Université Henri Poincaré - Nancy 1 (UHP)-Université Nancy 2-Institut National Polytechnique de Lorraine (INPL)-Centre National de la Recherche Scientifique (CNRS)-Université Henri Poincaré - Nancy 1 (UHP)-Université Nancy 2-Institut National Polytechnique de Lorraine (INPL)-Centre National de la Recherche Scientifique (CNRS)<br />Institut Non Linéaire de Nice Sophia-Antipolis (INLN)<br />Université Nice Sophia Antipolis (1965 - 2019) (UNS)-Centre National de la Recherche Scientifique (CNRS)
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  Data: 32 pages, 12 figures, submited ; With care, and keeping in mind that the biological plausibility of neuronal models with respect to the real brain activity is still an open question, we revisit some mathematical and numerical aspects of generalized Integrate and Fire (gIF) models and propose to eliminate assumptions related to spurious discontinuities. This concerns both the fire regime and then the integrate regime of the neuron. With this new point of view, some ``biological'' results obtained on ``models'' are to be reconsidered. This has also positive consequences. It allows us to reduce the bio-physical membrane equation to a very simple but powerful gIF numerical model. This also dramatically reduces the algorithmic complexity of event-based network simulations, as experimented here.
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