2026-08-17T20:50:14Z https://drops.dagstuhl.de/oai

oai:drops-oai.dagstuhl.de:11355 2024-03-06T10:48:01Z ddc:004 open_access

Brief Announcement: Integrating Temporal Information to Spatial Information in a Neural Circuit Lynch, Nancy Wang, Mien Brabeeba Spiking Neural Network Distributed Algorithm Biological Networks In this paper, we consider networks of deterministic spiking neurons, firing synchronously at discrete times. We consider the problem of translating temporal information into spatial information in such networks, an important task that is carried out by actual brains. Specifically, we define two problems: "First Consecutive Spikes Counting" and "Total Spikes Counting", which model temporal-coding and rate-coding aspects of temporal-to-spatial translation respectively. Assuming an upper bound of T on the length of the temporal input signal, we design two networks that solve two problems, each using O(log T) neurons and terminating in time T+1. We also prove that these bounds are tight. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Nancy Lynch and Mien Brabeeba Wang 2019 Is Part Of LIPIcs, Volume 146, 33rd International Symposium on Distributed Computing (DISC 2019) InProceedings Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/LIPIcs.DISC.2019.48 urn:nbn:de:0030-drops-113551 https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.DISC.2019.48 eng https://creativecommons.org/licenses/by/3.0/legalcode