Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Energy-efficient neuronal computation via quantal synaptic failures.

William B Levy1, Robert A Baxter

  • 1University of Virginia Health System, Department of Neurosurgery, Charlottesville, Virginia 22908, USA. wbl@virginia.edu

The Journal of Neuroscience : the Official Journal of the Society for Neuroscience
|June 1, 2002
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Growing dendrites enhance a neuron's computational power and memory capacity.

Neural networks : the official journal of the International Neural Network Society·2023
Same author

Communication consumes 35 times more energy than computation in the human cortex, but both costs are needed to predict synapse number.

Proceedings of the National Academy of Sciences of the United States of America·2021
Same author

Constructing multilayered neural networks with sparse, data-driven connectivity using biologically-inspired, complementary, homeostatic mechanisms.

Neural networks : the official journal of the International Neural Network Society·2019
Same author

Linearization of excitatory synaptic integration at no extra cost.

Journal of computational neuroscience·2018
Same author

Limited synapse overproduction can speed development but sometimes with long-term energy and discrimination penalties.

PLoS computational biology·2017
Same author

A consensus layer V pyramidal neuron can sustain interpulse-interval coding.

PloS one·2017
Same journal

Erratum: Yao et al., "Estrogen Regulates Bcl-w and Bim Expression: Role in Protection against β-Amyloid Peptide-Induced Neuronal Death".

The Journal of neuroscience : the official journal of the Society for Neuroscience·2026
Same journal

Erratum: L'Episcopo et al., "Plasticity of Subventricular Zone Neuroprogenitors in MPTP (1-Methyl-4-Phenyl-1,2,3,6-Tetrahydropyridine) Mouse Model of Parkinson's Disease Involves Cross Talk between Inflammatory and Wnt/β-Catenin Signaling Pathways: Functional Consequences for Neuroprotection and Repair".

The Journal of neuroscience : the official journal of the Society for Neuroscience·2026
Same journal

Representations of subsecond duration-based timing by complex spike synchrony in cerebellar Purkinje neurons.

The Journal of neuroscience : the official journal of the Society for Neuroscience·2026
Same journal

The extended language network: Language-responsive brain areas whose contributions to language remain to be discovered.

The Journal of neuroscience : the official journal of the Society for Neuroscience·2026
Same journal

Cortical and thalamic afferent connectomes distinguish ACC subregions of the macaque brain.

The Journal of neuroscience : the official journal of the Society for Neuroscience·2026
Same journal

The synaptic vesicle priming protein Munc13 mediates evoked somatodendritic dopamine release.

The Journal of neuroscience : the official journal of the Society for Neuroscience·2026
See all related articles

Synaptic failures in neurons can improve energy efficiency by optimizing information processing. This finding relates the optimal failure rate to the average firing rate, offering insights into neural computation.

Area of Science:

  • Neuroscience
  • Computational Neuroscience
  • Information Theory

Background:

  • Organisms evolve through compromises, often related to energy efficiency.
  • Neural processing involves trade-offs between information processing rate and energy consumption.
  • Synaptic transmission uncertainty is a key factor in neural computation.

Purpose of the Study:

  • To investigate how statistical uncertainty in synaptic transmission impacts neuronal energy efficiency.
  • To model neuronal information processing using information theory concepts.
  • To determine conditions under which synaptic failures enhance neuronal energetic efficiency.

Main Methods:

  • Conceptualizing dendrosomatic summation as a Shannon-type channel.
  • Analyzing synaptic uncertainty as part of dendrosomatic computation, not axonal transmission.

Related Experiment Videos

  • Developing a mathematical model to relate information gathered by dendritic summation to axonal information transmitted (H(p*)).

    • Main Results:

    • Conditions were identified where synaptic failures improve neuronal energetic efficiency.
    • A general expression was derived relating optimal failure rate (f) to average firing rate (p*): f ≈ 4(-H(p*)).
    • This relationship holds across different activity levels and is independent of the number of neuronal inputs.

    Conclusions:

    • Synaptic failures are not merely noise but can be a mechanism for optimizing energy efficiency in neural processing.
    • The derived expression provides a physiologically consistent framework for understanding optimal synaptic failure rates.
    • This work offers a novel perspective on neural computation, emphasizing energy efficiency as an evolutionary driver.