Accurate and Efficient Simulation of Very High-Dimensional Neural Mass Models with Distributed-Delay Connectome Tensors

This paper introduces methods and a novel toolbox that efficiently integrates high-dimensional Neural Mass Models (NMMs) specified by two essential components. The first is the set of nonlinear Random Differential Equations (RDEs) of the dynamics of each neural mass. The second is the highly sparse...

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Autors principals:	Anisleidy González Mitjans, Deirel Paz Linares, Carlos López Naranjo, Ariosky Areces Gonzalez, Min Li, Ying Wang, Ronaldo Garcia Reyes, Maria L. Bringas-Vega, Ludovico Minati, Alan C. Evans, Pedro A. Valdes-Sosa
Format:	Artigo
Idioma:	Inglês
Publicat:	Elsevier 2023-07-01
Col·lecció:	NeuroImage
Matèries:	Neural Mass Model time-delay Connectome Tensor brain dynamics Local Linearization Method
Accés en línia:	http://www.sciencedirect.com/science/article/pii/S1053811923002884
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