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Excess Entropies Suggest the Physiology of Neurons to Be Primed for Higher-Level Computation.
Stoop, Ralph L; Stoop, Norbert; Kanders, Karlis; Stoop, Ruedi.
Afiliação
  • Stoop RL; Institute of Neuroinformatics, University and ETH Zürich, Irchel Campus, Winterthurerstrasse 190, 8057 Zürich, Switzerland.
  • Stoop N; Department of Mathematics, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139-4307, USA.
  • Kanders K; Institute of Building Materials, ETH Zürich, Stefano-Franscini-Platz 3, 8093 Zürich, Switzerland.
  • Stoop R; Institute of Building Materials, ETH Zürich, Stefano-Franscini-Platz 3, 8093 Zürich, Switzerland.
Phys Rev Lett ; 127(14): 148101, 2021 Oct 01.
Article em En | MEDLINE | ID: mdl-34652209
Biological neuronal networks excel over artificial ones in many ways, but the origin of this is still unknown. Our symbolic dynamics-based tool of excess entropies suggests that neuronal cultures naturally implement data structures of a higher level than what we expect from artificial neural networks, or from close-to-biology neural networks. This points to a new pathway for improving artificial neural networks towards a level demonstrated by biology.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Modelos Neurológicos / Neurônios Limite: Humans Idioma: En Revista: Phys Rev Lett Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Modelos Neurológicos / Neurônios Limite: Humans Idioma: En Revista: Phys Rev Lett Ano de publicação: 2021 Tipo de documento: Article