A spiking neuron model of auditory neural coding

Guoping Wang, Misha Pavel

Research output: Contribution to journalConference articlepeer-review

Abstract

The focus of this paper is to propose an explanation for how biological auditory mechanism is able to use spiking neurons to code high bandwidth information using information channels with very slow sampling rates (< 20 Hz). The general approach described in this paper is to decompose the signal into narrow band channels, each of which can be sampled at a frequency that is much lower than the center frequency of the corresponding narrow band filter. The new idea here is that the system can use non-uniform sampling to capture both the amplitude of the modulation and the phase of the carrier signal. In this paper, we first describe a system based on FFT analysis combined with overlapadd and a sampling process where magnitude is digitized but phase is represented using a temporal code of spiking neurons. The coding/decoding mechanism is based on the properties of the refractory period. We demonstrate that it is possible to reduce the bit rate to 50% by coding the carrier phase using the timing of the pulses. In the second part of this paper we show how a biological system may approximate the broadband auditory signal using spiking neurons in conjunction with a simple model of neural refractory period.

Original languageEnglish (US)
Pages (from-to)598-604
Number of pages7
JournalLecture Notes in Computer Science
Volume3497
Issue numberII
DOIs
StatePublished - 2005
EventSecond International Symposium on Neural Networks: Advances in Neural Networks - ISNN 2005 - Chongqing, China
Duration: May 30 2005Jun 1 2005

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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