Network constraints on learnability of probabilistic motor sequences

Human learners are adept at grasping the complex relationships underlying incoming sequential input(1). In the present work, we formalize complex relationships as graph structures(2) derived from temporal associations(3,4) in motor sequences. Next, we explore the extent to which learners are sensiti...

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Detalles Bibliográficos
Autores principales: Kahn, Ari E., Karuza, Elisabeth A., Vettel, Jean M., Bassett, Danielle S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2018
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6474692/
https://www.ncbi.nlm.nih.gov/pubmed/30988437
http://dx.doi.org/10.1038/s41562-018-0463-8

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6474692/
https://www.ncbi.nlm.nih.gov/pubmed/30988437
http://dx.doi.org/10.1038/s41562-018-0463-8

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