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Agreement in Spiking Neural Networks

Abstract : We study the problem of binary agreement in a spiking neural network (SNN). We show that binary agreement on n inputs can be achieved with O(n) of auxiliary neurons. Our simulation results suggest that agreement can be achieved in our network in O(log n) time. We then describe a subclass of SNNs with a biologically plausible property, which we call size-independence. We prove that solving a class of problems, including agreement and Winner-Take-All, in this model requires O(n) auxiliary neurons, which makes our agreement network size-optimal.
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Contributor : Denis Sheynikhovich Connect in order to contact the contributor
Submitted on : Monday, July 11, 2022 - 1:38:22 PM
Last modification on : Wednesday, August 3, 2022 - 3:59:30 AM


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Martin Kunev, Petr Kuznetsov, Denis Sheynikhovich. Agreement in Spiking Neural Networks. Journal of Computational Biology, Mary Ann Liebert, 2022, 29 (4), pp.358 - 369. ⟨10.1089/cmb.2021.0365⟩. ⟨inserm-03719607⟩



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