Modeling of Spatial and Temporal Dynamics in Biological Olfactory Systems

Abstract

The olfactory system is a very efficient biological setup capable of odor information processing with neural signals. The nature of neural signals restricts the information representation to multidimensional temporal sequences of spikes. The information is contained in the inter-spike intervals in each individual neural signal and in inter-spike intervals between multiple signals. A mechanism of interactions between random excitations evoked by odorants in the olfactory receptors of the epithelium and deterministic operation of the olfactory bulb is proposed and evaluated in this project. Inverse Frobenius-Perron models of the bulbs temporal sequences are fitted to the inter-spike distributions of temporally modulated receptor signals. Ultimately, such pattern matching results in an ability to recognize odors and offers a hypothetical model for signal processing occurring in the primary stage of the olfactory system.

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Document Details

Document Type
Technical Report
Publication Date
Sep 21, 2007
Accession Number
ADA472796

Entities

People

  • Andy G. Lozowski
  • Jacek M. Zurada
  • Mykola Lysetskiy

Organizations

  • University of Louisville

Tags

Communities of Interest

  • C4I
  • Energy and Power Technologies
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Animal Structures
  • Artificial Intelligence
  • Brain
  • Computational Science
  • Computer Vision
  • Detection
  • Information Processing
  • Information Science
  • Mathematical Models
  • Network Science
  • Neural Networks
  • Neurons
  • Pattern Recognition
  • Probability Distributions
  • Random Variables
  • Signal Processing
  • Stochastic Processes

Fields of Study

  • Biology

Readers

  • Computational Modeling and Simulation
  • Radar Systems Engineering.
  • Vision Science/Vision Psychology/Cognitive Neuroscience.