Neuronal classification from network connectivity via adjacency spectral embedding

This work presents a novel strategy for classifying neurons, represented by nodes of a directed graph, based on their circuitry (edge connectivity). We assume a stochastic block model (SBM) in which neurons belong together if they connect to neurons of other groups according to the same probability...

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Detalles Bibliográficos
Autores principales: Mehta, Ketan, Goldin, Rebecca F., Marchette, David, Vogelstein, Joshua T., Priebe, Carey E., Ascoli, Giorgio A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MIT Press 2021
Materias:
Methods
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8567830/
https://www.ncbi.nlm.nih.gov/pubmed/34746623
http://dx.doi.org/10.1162/netn_a_00195

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8567830/
https://www.ncbi.nlm.nih.gov/pubmed/34746623
http://dx.doi.org/10.1162/netn_a_00195

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