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Inducing Plasticity of Astrocytic Receptors by Manipulation of Neuronal Firing Rates
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Quantifying encoding redundancy induced by rate correlations in Poisson neurons.

Tim Herfurth1, Tatjana Tchumatchenko1

  • 1Max Planck Institute for Brain Research, Theory of Neural Dynamics, Max-von-Laue-Strasse 4, 60438 Frankfurt, Germany.

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Summary
This summary is machine-generated.

This study introduces a new method to quantify how temporal correlations in neural firing impact information encoding. It reveals that signal features significantly shape redundancy in neural communication.

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Area of Science:

  • Computational Neuroscience
  • Information Theory
  • Neural Coding

Background:

  • Neuronal spike train correlations can introduce redundancy in stimulus encoding.
  • Quantitative methods to precisely measure the impact of these correlations on neural information transmission are limited.
  • Understanding these effects is crucial for deciphering neural communication.

Purpose of the Study:

  • To develop a general measure for information carried by correlated neuronal firing rate modulations.
  • To investigate the influence of rate correlations on encoding redundancy.
  • To establish mathematical connections between signal features and neural information redundancy.

Main Methods:

  • Analytical derivation of mutual information between a time-correlated rate signal and Poisson neuron spikes.
  • Focus on information carried solely by correlated rate modulations, excluding other spike correlations.
  • Analysis of how rate distribution and autocorrelation affect encoding redundancy.

Main Results:

  • Information carried by correlated spikes depends on spike autocorrelations.
  • Encoding redundancy due to rate correlations is influenced by rate histogram distribution and autocorrelation.
  • At low signal strengths, information in correlated spikes matches independent spikes, reflecting signal modulation depth.
  • Vanishing signal correlation time maximizes information but doesn't always equate to independent spike information.

Conclusions:

  • Provides a quantitative measure for information in correlated neuronal firing rates.
  • Demonstrates that signal-induced temporal correlations play a significant role in neural coding redundancy.
  • Offers insights into how signal characteristics shape redundancy and links existing theoretical methods.