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arXiv · 2204.01472

Distributed online estimation of biophysical neural networks

Thiago B. Burghi·Timothy O'Leary·Rodolphe Sepulchre
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Abstract

In this work, we propose a distributed adaptive observer for a class of nonlinear networked systems inspired by biophysical neural network models. Neural systems learn by adjusting intrinsic and synaptic weights in a distributed fashion, with neuronal membrane voltages carrying information from neighbouring neurons in the network. We show that this learning principle can be used to design an adaptive observer based on a decentralized learning rule that greatly reduces the number of observer states required for exponential convergence of parameter estimates. This novel design is relevant for biological, biomedical and neuromorphic applications.

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Thiago B. Burghi, Timothy O'Leary, Rodolphe Sepulchre. 2022-04-04. Distributed online estimation of biophysical neural networks. https://arxiv.org/abs/2204.01472

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