Bistability, Noise and Information Processing in Sensory Neurons

Abstract

In this paper, we look at the interpretation of time series data from firing events in periodically stimulated sensory neurons. A theoretical model, representing the neurons as bistable switching elements embedded in a Gaussian noise background, is considered. The cooperative effects arising through the coupling of the noise to the modulation are examined, together with their possible implications in the features of Inter-Spike-Interval Histograms (ISIHs) that are ubiquitous in neurophysiological experimental data. Our approach provides the simplest possible interpretation of the ISIHs and has been found to reproduce the salient features of experimental ISIHs. Neural models, Single neurons, Stochastic resonance, Noise, Neural networks.

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Document Details

Document Type
Technical Report
Publication Date
Nov 01, 1993
Accession Number
ADA277501

Entities

People

  • Adi R. Bulsara

Organizations

  • Naval Command, Control and Ocean Surveillance Center

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Amplitude
  • Background Noise
  • Cells
  • Experimental Data
  • Firing Rate
  • Frequency
  • Information Processing
  • Information Science
  • Information Transfer
  • Intensity
  • Nerves
  • Nervous System
  • Neural Networks
  • Neurons
  • Neurophysiology
  • New Zealand
  • Noise

Readers

  • Neural Network Machine Learning.
  • Neuroscience
  • Optical Physics and Photonics.

Technology Areas

  • AI & ML
  • AI & ML - Neural Networks