Modeling of extrasynaptic information transfer in neural networks using braid theory | Zendy

Olga Lukyanova | Zendy; O. Yu. Nikitin | Zendy

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Modeling of extrasynaptic information transfer in neural networks using braid theory

Author(s) -

Olga Lukyanova,

O. Yu. Nikitin

Publication year - 2018

Publication title -

procedia computer science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.334

H-Index - 76

ISSN - 1877-0509

DOI - 10.1016/j.procs.2018.11.076

Subject(s) - computer science , information transfer , artificial neural network , basis (linear algebra) , braid , distortion (music) , signal (programming language) , artificial intelligence , mixing (physics) , theoretical computer science , cognitive science , telecommunications , materials science , composite material , psychology , amplifier , geometry , mathematics , physics , bandwidth (computing) , quantum mechanics , programming language

Current neural network approaches mostly consider the synaptic signal transfer as a basis of interneuronal communication. At the same time, extrasynaptic signaling plays important role in the animal behavior. In the paper processes of information distortion during the extrasynaptic mixing are studied using braid theory. An approach to the procedural generation of deep neural networks incorporating properties of extrasynaptic information dynamics is proposed.

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