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  Simple models including energy and spike constraints reproduce complex activity patterns and metabolic disruptions

Fardet, T., & Levina, A. (2020). Simple models including energy and spike constraints reproduce complex activity patterns and metabolic disruptions. PLoS Computational Biology, 16(12), 1-22. doi:10.1371/journal.pcbi.1008503.

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Fardet, T1, 2, Autor           
Levina, A1, 2, Autor           
Affiliations:
1Department Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497798              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497794              

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 Zusammenfassung: In this work, we introduce new phenomenological neuronal models (eLIF and mAdExp) that account for energy supply and demand in the cell as well as the inactivation of spike generation how these interact with subthreshold and spiking dynamics. Including these constraints, the new models reproduce a broad range of biologically-relevant behaviors that are identified to be crucial in many neurological disorders, but were not captured by commonly used phenomenological models. Because of their low dimensionality eLIF and mAdExp open the possibility of future large-scale simulations for more realistic studies of brain circuits involved in neuronal disorders. The new models enable both more accurate modeling and the possibility to study energy-associated disorders over the whole time-course of disease progression instead of only comparing the initially healthy status with the final diseased state. These models, therefore, provide new theoretical and computational methods to assess the opportunities of early diagnostics and the potential of energy-centered approaches to improve therapies.

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 Datum: 2011-112020-12
 Publikationsstatus: Online veröffentlicht
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 Identifikatoren: DOI: 10.1371/journal.pcbi.1008503
eDoc: e1008503
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Titel: PLoS Computational Biology
Genre der Quelle: Zeitschrift
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Ort, Verlag, Ausgabe: San Francisco, CA : Public Library of Science
Seiten: - Band / Heft: 16 (12) Artikelnummer: - Start- / Endseite: 1 - 22 Identifikator: ISSN: 1553-734X
CoNE: https://pure.mpg.de/cone/journals/resource/1000000000017180_1