Busca avançada
Ano de início
Entree
(Referência obtida automaticamente do Web of Science, por meio da informação sobre o financiamento pela FAPESP e o número do processo correspondente, incluída na publicação pelos autores.)

Conductance-based models and the fragmentation problem: A case study based on hippocampal CA1 pyramidal cell models and epilepsy

Texto completo
Autor(es):
Tejada, Julian [1, 2] ; Roque, C. Antonio [3]
Número total de Autores: 2
Afiliação do(s) autor(es):
[1] Univ Fed Sergipe, DPS, Dept Psicol, BR-49100000 Sao Cristovao, SE - Brazil
[2] Fdn Univ Konrad Lorenz, Fac Psicol, Bogota - Colombia
[3] Univ Sao Paulo, FFCLRP, Dept Fis, BR-14040901 Ribeirao Preto, SP - Brazil
Número total de Afiliações: 3
Tipo de documento: Artigo Científico
Fonte: Epilepsy & Behavior; v. 121, n. B AUG 2021.
Citações Web of Science: 0
Resumo

Epilepsy has been a central topic in computational neuroscience, and in silico models have shown to be excellent tools to integrate and evaluate findings from animal and clinical settings. Among the different languages and tools for computational modeling development, NEURON stands out as one of the most used and mature neurosimulators. However, despite the vast quantity of models developed with NEURON, a fragmentation problem is evident in the great majority of models related to the same type of cell or cell properties. This fragmentation causes a lack of interoperability between the models because of differences in parameters. The problem is not related to the neurosimulator, which is prepared to reuse elements of other models, but related to decisions made during the model development, when it is not uncommon to adjust parameter values according to the necessities of the study. Here, this problem is presented by studying computational models related to temporal lobe epilepsy and the definitions of hippocampal CA1 pyramidal cells. The current assessment aims to highlight the implications of fragmentation for reliable modeling and the need to adopt a framework that allows a better inter operability between different models. This article is part of the Special Issue \& ldquo;NEWroscience 2018 \& rdquo;. (c) 2019 Elsevier Inc. All rights reserved. (AU)

Processo FAPESP: 15/50122-0 - Fenômenos dinâmicos em redes complexas: fundamentos e aplicações
Beneficiário:Elbert Einstein Nehrer Macau
Modalidade de apoio: Auxílio à Pesquisa - Temático
Processo FAPESP: 13/07699-0 - Centro de Pesquisa, Inovação e Difusão em Neuromatemática - NeuroMat
Beneficiário:Oswaldo Baffa Filho
Modalidade de apoio: Auxílio à Pesquisa - Centros de Pesquisa, Inovação e Difusão - CEPIDs