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Synaptic Information Storage Capacity Measured With Information Theory.

Mohammad Samavat1,2, Thomas M Bartol3, Kristen M Harris4

  • 1Department of Electrical and Computer Engineering, Jacobs School of Engineering, University of California, San Diego.

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Researchers quantified synaptic plasticity precision using Shannon information theory. This method revealed the brain

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Area of Science:

  • Neuroscience
  • Computational Neuroscience
  • Information Theory

Background:

  • Synaptic plasticity is crucial for neural information processing.
  • Understanding the precision of synaptic plasticity is key to comprehending memory and learning.
  • Previous studies utilized signal detection theory to analyze synaptic properties.

Purpose of the Study:

  • To quantify the precision and information storage capacity of synaptic plasticity using Shannon information theory.
  • To compare information theory with signal detection theory for analyzing synaptic strength.
  • To establish a novel analytical measure for synaptic information storage capacity (SISC).

Main Methods:

  • Applied Shannon information theory and Shannon entropy to quantify information stored in synapse dimensions.
  • Used dendritic spine head volumes in hippocampal area CA1 as a measure of synaptic strength.
  • Compared the distribution of distinguishable spine sizes to a uniform distribution using Kullback-Leibler divergence.

Main Results:

  • Information theory delineated 24 distinguishable synaptic strengths based on dendritic spine head volumes.
  • Calculated a synaptic information storage capacity (SISC) between 4.1 and 4.59 bits.
  • Found a nearly uniform distribution of spine head volumes, suggesting optimal utilization of distinguishable synaptic sizes.

Conclusions:

  • Shannon information theory offers a robust method for quantifying synaptic plasticity precision and information storage.
  • SISC provides a generalized analytical tool applicable to various brain regions, species, and conditions.
  • This approach can be extended to investigate the impact of diseases and learning on synaptic plasticity.