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An exact mathematical description of computation with transient spatiotemporal dynamics in a complex-valued neural network

Mathematics

An exact mathematical description of computation with transient spatiotemporal dynamics in a complex-valued neural network

R. C. Budzinski, A. N. Busch, et al.

This innovative research introduces a complex-valued neural network (cv-NN) that showcases advanced spatiotemporal dynamics for sophisticated computations, such as logic gates and secure message passing. Conducted by authors from Western University and Stanford University, this study reveals that the cv-NN computations can be interpreted by biological neurons, potentially paving the way for bio-hybrid computing systems.

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Playback language: English
Abstract
This paper introduces a complex-valued neural network (cv-NN) with linear interactions and phase-delays that exhibits sophisticated spatiotemporal dynamics used for computation. The cv-NN can perform logic gates, encode short-term memories, and mediate secure message passing. The computations are described by an exact, closed-form mathematical expression. Intracellular recordings from neocortical neurons demonstrate that the cv-NN computations are decodable by biological neurons. This work opens avenues for designing adaptable bio-hybrid computing systems.
Publisher
Communications Physics
Published On
Apr 01, 2024
Authors
Roberto C. Budzinski, Alexandra N. Busch, Samuel Mestern, Erwan Martin, Luisa H. B. Liboni, Federico W. Pasini, Ján Mináč, Todd Coleman, Wataru Inoue, Lyle E. Muller
Tags
complex-valued neural network
spatiotemporal dynamics
logic gates
bio-hybrid systems
secure message passing

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