Energy efficient synaptic plasticity

  1. Ho Ling Li
  2. Mark CW van Rossum  Is a corresponding author
  1. University of Nottingham, United Kingdom

Abstract

Many aspects of the brain's design can be understood as the result of evolutionary drive towards metabolic efficiency. In addition to the energetic costs of neural computation and transmission, experimental evidence indicates that synaptic plasticity is metabolically demanding as well. As synaptic plasticity is crucial for learning, we examine how these metabolic costs enter in learning. We find that when synaptic plasticity rules are naively implemented, training neural networks requires extremely large amounts of energy when storing many patterns. We propose that this is avoided by precisely balancing labile forms of synaptic plasticity with more stable forms. This algorithm, termed synaptic caching, boosts energy efficiency manifold and can be used with any plasticity rule, including back-propagation. Our results yield a novel interpretation of the multiple forms of neural synaptic plasticity observed experimentally, including synaptic tagging and capture phenomena. Furthermore our results are relevant for energy efficient neuromorphic designs.

Data availability

Simulation scripts can be found at https://github.com/vanrossumlab/li_vanrossum_19.

The following previously published data sets were used

Article and author information

Author details

  1. Ho Ling Li

    School of Psychology, University of Nottingham, Nottingham, United Kingdom
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-5654-0183
  2. Mark CW van Rossum

    School of Psychology and School of Mathematical Sciences, University of Nottingham, Nottingham, United Kingdom
    For correspondence
    mark.vanrossum@nottingham.ac.uk
    Competing interests
    Mark CW van Rossum, Reviewing editor, eLife.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-6525-6814

Funding

Leverhulme Trust (RPG-2017-404)

  • Mark CW van Rossum

Engineering and Physical Sciences Research Council (EP/R030952/1)

  • Mark CW van Rossum

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Copyright

© 2020, Li & van Rossum

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.

Metrics

  • 3,260
    views
  • 474
    downloads
  • 29
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Ho Ling Li
  2. Mark CW van Rossum
(2020)
Energy efficient synaptic plasticity
eLife 9:e50804.
https://doi.org/10.7554/eLife.50804

Share this article

https://doi.org/10.7554/eLife.50804

Further reading

    1. Neuroscience
    Changrun Huang, Dirk van Moorselaar ... Jan Theeuwes
    Research Article

    Attentional capture by an irrelevant salient distractor is attenuated when the distractor appears more frequently in one location, suggesting learned suppression of that location. However, it remains unclear whether suppression is proactive (before attention is directed) or reactive (after attention is allocated). Here, we investigated this using a ‘pinging’ technique to probe the attentional distribution before search onset. In an EEG experiment, participants searched for a shape singleton while ignoring a color singleton distractor at a high-probability location. To reveal the hidden attentional priority map, participants also performed a continuous recall spatial memory task, with a neutral placeholder display presented before search onset. Behaviorally, search was more efficient when the distractor appeared at the high-probability location. Inverted encoding analysis of EEG data showed tuning profiles that decayed during memory maintenance but were revived by the placeholder display. Notably, tuning was most pronounced at the to-be-suppressed location, suggesting initial spatial selection followed by suppression. These findings suggest that learned distractor suppression is a reactive process, providing new insights into learned spatial distractor suppression mechanisms.

    1. Neuroscience
    Anne L Willems, Lukas Van Oudenhove, Bram Vervliet
    Research Article

    The unexpected absence of danger constitutes a pleasurable event that is critical for the learning of safety. Accumulating evidence points to similarities between the processing of absent threat and the well-established reward prediction error (PE). However, clear-cut evidence for this analogy in humans is scarce. In line with recent animal data, we showed that the unexpected omission of (painful) electrical stimulation triggers activations within key regions of the reward and salience pathways and that these activations correlate with the pleasantness of the reported relief. Furthermore, by parametrically violating participants’ probability and intensity related expectations of the upcoming stimulation, we showed for the first time in humans that omission-related activations in the VTA/SN were stronger following omissions of more probable and intense stimulations, like a positive reward PE signal. Together, our findings provide additional support for an overlap in the neural processing of absent danger and rewards in humans.