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Related Experiment Videos

Evaluating information transfer between auditory cortical neurons.

Boris Gourévitch1, Jos J Eggermont

  • 1Department of Physiology and Biophysics and Department of Psychology, University of Calgary, Calgary, Alberta, Canada.

Journal of Neurophysiology
|January 5, 2007
PubMed
Summary
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Transfer entropy quantifies information flow between neurons, aiding neural assembly research. This method reveals temporal integration windows and differs from cross-correlation analysis.

Area of Science:

  • Neuroscience
  • Information Theory
  • Computational Neuroscience

Background:

  • Neural assemblies are fundamental to brain function.
  • Understanding information transfer between neurons is crucial.
  • Existing methods like cross-correlation have limitations.

Purpose of the Study:

  • Introduce transfer entropy as a novel tool for analyzing neural assemblies.
  • Quantify information flow and feedback between neurons.
  • Investigate temporal integration windows and stimulus-induced firing rate modulation.

Main Methods:

  • Utilized transfer entropy to measure information fraction from a neuron's past in another neuron.
  • Applied transfer entropy to multiunit recordings from cat's auditory cortex.

Related Experiment Videos

  • Examined information transfer across a network of 16 simultaneous recordings during acoustic stimulation.

    • Main Results:

    • Transfer entropy quantifies directed information transfer between neurons.
    • Identified temporal integration windows during spontaneous activity ranging from 2 to 15 ms.
    • Demonstrated that transfer entropy provides different insights compared to cross-correlation analysis.

    Conclusions:

    • Transfer entropy is a valuable tool for investigating neural assemblies and information processing.
    • The method helps elucidate temporal dynamics and stimulus-response relationships in neural networks.
    • Findings suggest a re-evaluation of the neural assembly concept based on transfer entropy analysis.