A dynamical memory with only one spiking neuron

Fuente: arXiv
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Main Authors: Depannemaecker, Damien, d'Hollande, Adrien, Wu, Jiaming, Rozenberg, Marcelo J.
Format: Preprint
Published: 2025
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author Depannemaecker, Damien
d'Hollande, Adrien
Wu, Jiaming
Rozenberg, Marcelo J.
author_facet Depannemaecker, Damien
d'Hollande, Adrien
Wu, Jiaming
Rozenberg, Marcelo J.
contents Common wisdom indicates that to implement a Dynamical Memory with spiking neurons two ingredients are necessary: recurrence and a neuron population. Here we shall show that the second requirement is not needed. We shall demonstrate that under very general assumptions a single recursive spiking neuron can realize a robust model of a dynamical memory. We demonstrate the implementation of a dynamical memory in both, software and hardware. In the former case, we introduce trivial extensions of the popular aQIF and AdEx models. In the latter, we show traces obtained in a circuit model with a recently proposed memristive spiking neuron. We show that the bistability of the theoretical models can be understood in terms of a self-consistent problem that can be represented geometrically. Our minimal dynamical memory model provides a simplest implementation of an important neuro-computational primitive, which can be useful in navigation system models based on purely spiking dynamics. A one neuron dynamical memory may also provides a natural explanation to the surprising recent observation that the excitation bump in Drosophila's ellipsoidal body is made by just a handful of neurons.
format Preprint
id arxiv_https___arxiv_org_abs_2505_15453
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle A dynamical memory with only one spiking neuron
Depannemaecker, Damien
d'Hollande, Adrien
Wu, Jiaming
Rozenberg, Marcelo J.
Neurons and Cognition
Common wisdom indicates that to implement a Dynamical Memory with spiking neurons two ingredients are necessary: recurrence and a neuron population. Here we shall show that the second requirement is not needed. We shall demonstrate that under very general assumptions a single recursive spiking neuron can realize a robust model of a dynamical memory. We demonstrate the implementation of a dynamical memory in both, software and hardware. In the former case, we introduce trivial extensions of the popular aQIF and AdEx models. In the latter, we show traces obtained in a circuit model with a recently proposed memristive spiking neuron. We show that the bistability of the theoretical models can be understood in terms of a self-consistent problem that can be represented geometrically. Our minimal dynamical memory model provides a simplest implementation of an important neuro-computational primitive, which can be useful in navigation system models based on purely spiking dynamics. A one neuron dynamical memory may also provides a natural explanation to the surprising recent observation that the excitation bump in Drosophila's ellipsoidal body is made by just a handful of neurons.
title A dynamical memory with only one spiking neuron
topic Neurons and Cognition
url https://arxiv.org/abs/2505.15453