Leveraging Julia’s automated differentiation and symbolic computation to increase spectral DCM flexibility and speed

Using neuroimaging and electrophysiological data to infer neural parameter estimations from theoretical circuits requires solving the inverse problem. Here, we provide a new Julia language package designed to i) compose complex dynamical models in a simple and modular way with ModelingToolkit.jl, ii...

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Detalles Bibliográficos
Autores principales: Hofmann, David, Chesebro, Anthony G., Rackauckas, Chris, Mujica-Parodi, Lilianne R., Friston, Karl J., Edelman, Alan, Strey, Helmut H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10634910/
https://www.ncbi.nlm.nih.gov/pubmed/37961652
http://dx.doi.org/10.1101/2023.10.27.564407

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10634910/
https://www.ncbi.nlm.nih.gov/pubmed/37961652
http://dx.doi.org/10.1101/2023.10.27.564407

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