Brief Announcement: Integrating Temporal Information to Spatial Information in a Neural Circuit

Authors Nancy Lynch, Mien Brabeeba Wang



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Author Details

Nancy Lynch
  • Massachusetts Institute of Technology, Cambridge, MA, United States
Mien Brabeeba Wang
  • Massachusetts Institute of Technology, Cambridge, MA, United States

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Nancy Lynch and Mien Brabeeba Wang. Brief Announcement: Integrating Temporal Information to Spatial Information in a Neural Circuit. In 33rd International Symposium on Distributed Computing (DISC 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 146, pp. 48:1-48:3, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019) https://doi.org/10.4230/LIPIcs.DISC.2019.48

Abstract

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.

Subject Classification

ACM Subject Classification
  • Theory of computation → Distributed computing models
  • Theory of computation → Distributed algorithms
  • Applied computing → Biological networks
Keywords
  • Spiking Neural Network
  • Distributed Algorithm
  • Biological Networks

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References

  1. Chi-Ning Chou, Kai-Min Chung, and Chi-Jen Lu. On the Algorithmic Power of Spiking Neural Networks. ITCS, 2019. Google Scholar
  2. T. Gollisch and M. Meister. Rapid neural coding in the retina with relative spike latencies. Science, 319:1108-1111, 2008. Google Scholar
  3. Yael Hitron and Merav Parter. Counting to Ten with Two Fingers: Compressed Counting with Spiking Neurons. arXiv:1902.10369 [cs.NE], 2019. URL: http://arxiv.org/abs/1902.10369.
  4. Nancy A. Lynch, Cameron Musco, and Merav Parter. Computational Tradeoffs in Biological Neural Networks: Self-Stabilizing Winner-Take-All Networks. ITCS, 2017. Google Scholar
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