1. Neuroscience
Download icon

Neural variability determines coding strategies for natural self-motion in macaque monkeys

Research Advance
  • Cited 0
  • Views 649
  • Annotations
Cite this article as: eLife 2020;9:e57484 doi: 10.7554/eLife.57484

Abstract

We have previously reported that central neurons mediating vestibulo-spinal reflexes and self-motion perception optimally encode natural self-motion (Mitchell et al., 2018). Importantly however, the vestibular nuclei also comprise other neuronal classes that mediate essential functions such as the vestibulo-ocular reflex (VOR) and its adaptation. Here we show that heterogeneities in resting discharge variability mediate a trade-off between faithful encoding and optimal coding via temporal whitening. Specifically, neurons displaying lower variability did not whiten naturalistic self-motion but instead faithfully represented the stimulus' detailed time course, while neurons displaying higher variability displayed temporal whitening. Using a well-established model of VOR pathways, we demonstrate that faithful stimulus encoding is necessary to generate the compensatory eye movements found experimentally during naturalistic self-motion. Our findings suggest a novel functional role for variability towards establishing different coding strategies: 1) faithful stimulus encoding for generating the VOR; 2) optimized coding via temporal whitening for other vestibular functions.

Data availability

Data is available on figshare: 10.6084/m9.figshare.12594803.

Article and author information

Author details

  1. Isabelle Mackrous

    Department of Physiology, McGill University, Montreal, Canada
    Competing interests
    The authors declare that no competing interests exist.
  2. Jérome Carriot

    Department of Physiology, McGill University, Montreal, Canada
    Competing interests
    The authors declare that no competing interests exist.
  3. Kathleen E Cullen

    Department of Physiology, McGill University, Montreal, Canada
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-9348-0933
  4. Maurice J Chacron

    Department of Physiology, McGill University, Montreal, Canada
    For correspondence
    maurice.chacron@mcgill.ca
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-3032-452X

Funding

Canadian Institutes of Health Research (162285)

  • Jérome Carriot
  • Kathleen E Cullen
  • Maurice J Chacron

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

Ethics

Animal experimentation: All experimental protocols were approved by the McGill University Animal Care Committee (#4096) and complied with the guidelines of the Canadian Council on Animal Care.

Reviewing Editor

  1. Fred Rieke, University of Washington, United States

Publication history

  1. Received: April 2, 2020
  2. Accepted: September 10, 2020
  3. Accepted Manuscript published: September 11, 2020 (version 1)
  4. Version of Record published: September 28, 2020 (version 2)

Copyright

© 2020, Mackrous 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.

Metrics

  • 649
    Page views
  • 94
    Downloads
  • 0
    Citations

Article citation count generated by polling the highest count across the following sources: Crossref, PubMed Central, Scopus.

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)

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

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

Further reading

    1. Neuroscience
    Zachariah Bertels et al.
    Research Article Updated

    Migraine is the sixth most prevalent disease worldwide but the mechanisms that underlie migraine chronicity are poorly understood. Cytoskeletal flexibility is fundamental to neuronal-plasticity and is dependent on dynamic microtubules. Histone-deacetylase-6 (HDAC6) decreases microtubule dynamics by deacetylating its primary substrate, α-tubulin. We use validated mouse models of migraine to show that HDAC6-inhibition is a promising migraine treatment and reveal an undiscovered cytoarchitectural basis for migraine chronicity. The human migraine trigger, nitroglycerin, produced chronic migraine-associated pain and decreased neurite growth in headache-processing regions, which were reversed by HDAC6 inhibition. Cortical spreading depression (CSD), a physiological correlate of migraine aura, also decreased cortical neurite growth, while HDAC6-inhibitor restored neuronal complexity and decreased CSD. Importantly, a calcitonin gene-related peptide receptor antagonist also restored blunted neuronal complexity induced by nitroglycerin. Our results demonstrate that disruptions in neuronal cytoarchitecture are a feature of chronic migraine, and effective migraine therapies might include agents that restore microtubule/neuronal plasticity.

    1. Computational and Systems Biology
    2. Neuroscience
    Douglas G Lee, Jean Daunizeau
    Research Article Updated

    Why do we sometimes opt for actions or items that we do not value the most? Under current neurocomputational theories, such preference reversals are typically interpreted in terms of errors that arise from the unreliable signaling of value to brain decision systems. But, an alternative explanation is that people may change their mind because they are reassessing the value of alternative options while pondering the decision. So, why do we carefully ponder some decisions, but not others? In this work, we derive a computational model of the metacognitive control of decisions or MCD. In brief, we assume that fast and automatic processes first provide initial (and largely uncertain) representations of options' values, yielding prior estimates of decision difficulty. These uncertain value representations are then refined by deploying cognitive (e.g., attentional, mnesic) resources, the allocation of which is controlled by an effort-confidence tradeoff. Importantly, the anticipated benefit of allocating resources varies in a decision-by-decision manner according to the prior estimate of decision difficulty. The ensuing MCD model predicts response time, subjective feeling of effort, choice confidence, changes of mind, as well as choice-induced preference change and certainty gain. We test these predictions in a systematic manner, using a dedicated behavioral paradigm. Our results provide a quantitative link between mental effort, choice confidence, and preference reversals, which could inform interpretations of related neuroimaging findings.