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The EBRAINS Hodgkin-Huxley Neuron Builder: An online resource for building data-driven neuron models.
Bologna, Luca Leonardo; Smiriglia, Roberto; Lupascu, Carmen Alina; Appukuttan, Shailesh; Davison, Andrew P; Ivaska, Genrich; Courcol, Jean-Denis; Migliore, Michele.
Afiliação
  • Bologna LL; Institute of Biophysics, National Research Council, Palermo, Italy.
  • Smiriglia R; Institute of Biophysics, National Research Council, Palermo, Italy.
  • Lupascu CA; Institute of Biophysics, National Research Council, Palermo, Italy.
  • Appukuttan S; Centre National de la Recherche Scientifique, Institut des Neurosciences Paris-Saclay, Université Paris-Saclay, Saclay, France.
  • Davison AP; Centre National de la Recherche Scientifique, Institut des Neurosciences Paris-Saclay, Université Paris-Saclay, Saclay, France.
  • Ivaska G; Blue Brain Project, École Polytechnique Fédérale de Lausanne, Geneva, Switzerland.
  • Courcol JD; Blue Brain Project, École Polytechnique Fédérale de Lausanne, Geneva, Switzerland.
  • Migliore M; Institute of Biophysics, National Research Council, Palermo, Italy.
Front Neuroinform ; 16: 991609, 2022.
Article em En | MEDLINE | ID: mdl-36225653
ABSTRACT
In the last decades, brain modeling has been established as a fundamental tool for understanding neural mechanisms and information processing in individual cells and circuits at different scales of observation. Building data-driven brain models requires the availability of experimental data and analysis tools as well as neural simulation environments and, often, large scale computing facilities. All these components are rarely found in a comprehensive framework and usually require ad hoc programming. To address this, we developed the EBRAINS Hodgkin-Huxley Neuron Builder (HHNB), a web resource for building single cell neural models via the extraction of activity features from electrophysiological traces, the optimization of the model parameters via a genetic algorithm executed on high performance computing facilities and the simulation of the optimized model in an interactive framework. Thanks to its inherent characteristics, the HHNB facilitates the data-driven model building workflow and its reproducibility, hence fostering a collaborative approach to brain modeling.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2022 Tipo de documento: Article