Nanoconnectomic upper bound on the variability of synaptic plasticity

  1. Thomas M Bartol  Is a corresponding author
  2. Cailey Bromer
  3. Justin P Kinney
  4. Micheal A Chirillo
  5. Jennifer N Bourne
  6. Kristen M Harris
  7. Terrence J Sejnowski
  1. Howard Hughes Medical Institute, Salk Institute for Biological Studies, United States
  2. Massachusetts Institute of Technology, United States
  3. The University of Texas at Austin, United States
  4. University of Colorado Denver, United States

Abstract

Information in a computer is quantified by the number of bits that can be stored and recovered. An important question about the brain is how much information can be stored at a synapse through synaptic plasticity, which depends on the history of probabilistic synaptic activity. The strong correlation between size and efficacy of a synapse allowed us to estimate the variability of synaptic plasticity. In an EM reconstruction of hippocampal neuropil we found single axons making two or more synaptic contacts onto the same dendrites, having shared histories of presynaptic and postsynaptic activity. The spine heads and neck diameters, but not neck lengths, of these pairs were nearly identical in size. We found that there is a minimum of 26 distinguishable synaptic strengths, corresponding to storing 4.7 bits of information at each synapse. Because of stochastic variability of synaptic activation the observed precision requires averaging activity over several minutes.

Article and author information

Author details

  1. Thomas M Bartol

    Howard Hughes Medical Institute, Salk Institute for Biological Studies, La Jolla, United States
    For correspondence
    bartol@salk.edu
    Competing interests
    The authors declare that no competing interests exist.
  2. Cailey Bromer

    Howard Hughes Medical Institute, Salk Institute for Biological Studies, La Jolla, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Justin P Kinney

    Massachusetts Institute of Technology, Cambridge, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Micheal A Chirillo

    Center for Learning and Memory, Department of Neuroscience, The University of Texas at Austin, Austin, United States
    Competing interests
    The authors declare that no competing interests exist.
  5. Jennifer N Bourne

    University of Colorado Denver, Denver, United States
    Competing interests
    The authors declare that no competing interests exist.
  6. Kristen M Harris

    Center for Learning and Memory, Department of Neuroscience, The University of Texas at Austin, Austin, United States
    Competing interests
    The authors declare that no competing interests exist.
  7. Terrence J Sejnowski

    Howard Hughes Medical Institute, Salk Institute for Biological Studies, La Jolla, United States
    Competing interests
    The authors declare that no competing interests exist.

Reviewing Editor

  1. Sacha B Nelson, Brandeis University, United States

Version history

  1. Received: August 11, 2015
  2. Accepted: November 29, 2015
  3. Accepted Manuscript published: November 30, 2015 (version 1)
  4. Version of Record published: January 20, 2016 (version 2)

Copyright

© 2015, Bartol et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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  1. Thomas M Bartol
  2. Cailey Bromer
  3. Justin P Kinney
  4. Micheal A Chirillo
  5. Jennifer N Bourne
  6. Kristen M Harris
  7. Terrence J Sejnowski
(2015)
Nanoconnectomic upper bound on the variability of synaptic plasticity
eLife 4:e10778.
https://doi.org/10.7554/eLife.10778

Share this article

https://doi.org/10.7554/eLife.10778

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