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pro vyhledávání: '"Alexander Rivkind"'
Autor:
Ran Darshan, Alexander Rivkind
Publikováno v:
Cell Reports, Vol 39, Iss 1, Pp 110612- (2022)
Summary: Animals must monitor continuous variables such as position or head direction. Manifold attractor networks—which enable a continuum of persistent neuronal states—provide a key framework to explain this monitoring ability. Neural networks
Externí odkaz:
https://doaj.org/article/dc3134d9724f4b92be4429a8d044ab8c
Publikováno v:
PLoS Computational Biology, Vol 16, Iss 5, p e1007825 (2020)
Biological networks are often heterogeneous in their connectivity pattern, with degree distributions featuring a heavy tail of highly connected hubs. The implications of this heterogeneity on dynamical properties are a topic of much interest. Here we
Externí odkaz:
https://doaj.org/article/32ec9040c8224ce1a5ad1ef2aaa6b518
Autor:
Ran Darshan, Alexander Rivkind
Manifold attractors are a key framework for understanding how continuous variables, such as position or head direction, are encoded in the brain. In this framework, the variable is represented along a continuum of persistent neuronal states which for
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::16736e144cdef4a565517243687f8a75
https://doi.org/10.1101/2021.06.01.446635
https://doi.org/10.1101/2021.06.01.446635
Publikováno v:
PLoS Computational Biology, Vol 16, Iss 5, p e1007825 (2020)
PLoS Computational Biology
PLoS Computational Biology
Biological networks are often heterogeneous in their connectivity pattern, with degree distributions featuring a heavy tail of highly connected hubs. The implications of this heterogeneity on dynamical properties are a topic of much interest. Here we
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::80a36ad58ba000af82a35bfc6f02a8ee