Neuronal morphologies built for reliable physiology in a rhythmic motor circuit

  1. Adriane G Otopalik  Is a corresponding author
  2. Jason Pipkin
  3. Eve Marder  Is a corresponding author
  1. Columbia University, United States
  2. Brandeis University, United States

Abstract

It is often assumed that highly-branched neuronal structures perform compartmentalized computations. Instead, the Gastric Mill (GM) neuron in the crustacean stomatogastric ganglion (STG) operates like a single electrotonic compartment, despite having thousands of branch points and total cable length >10 mm (Otopalik et al., 2017a, b). We now show: 1) that compact electrotonic architecture is generalizable to other STG neuron types, 2) these neurons present direction-insensitive, linear voltage integration, suggesting they pool synaptic inputs across their neuronal structures. 3) Simulations of 720 cable models spanning a broad range of geometries and passive properties show that compact electrotonus, linear integration, and directional insensitivity in STG neurons arise from their neurite geometries (diameters tapering from 10-20 µm to < 2 µm at their terminal tips). A broad parameter search reveals multiple morphological and biophysical solutions for achieving different degrees of passive electrotonic decrement and computational strategies in the absence of active properties.

Data availability

All computational scripts used for: analysis, visualization, and model simulations, will be promptly posted on the Marder Lab GitHub site (https://github.com/marderlab) upon publication, where it will be freely available to the public. These tools are currently available on A. Otopalik's GitHub site (https://github.com/otopalik/Otopalik-Pipkin-Marder-2019). All source data are publicly available on Dryad (https://dx.doi.org/10.5061/dryad.48pt6jd).

The following data sets were generated

Article and author information

Author details

  1. Adriane G Otopalik

    Department of Biological Sciences, Columbia University, New York, United States
    For correspondence
    ao2656@columbia.edu
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-3224-6502
  2. Jason Pipkin

    Volen Center, Brandeis University, Waltham, United States
    Competing interests
    No competing interests declared.
  3. Eve Marder

    Volen Center, Brandeis University, Waltham, United States
    For correspondence
    marder@brandeis.edu
    Competing interests
    Eve Marder, Deputy Editor, eLife.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-9632-5448

Funding

National Institute of Neurological Disorders and Stroke (F31NS092126)

  • Adriane G Otopalik

National Institute of Neurological Disorders and Stroke (R35NS097343)

  • Eve Marder

Grass Foundation

  • Adriane G Otopalik

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

Reviewing Editor

  1. Inna Slutsky, Tel Aviv University, Israel

Version history

  1. Received: September 7, 2018
  2. Accepted: January 12, 2019
  3. Accepted Manuscript published: January 18, 2019 (version 1)
  4. Version of Record published: January 28, 2019 (version 2)

Copyright

© 2019, Otopalik 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

  • 1,636
    views
  • 235
    downloads
  • 19
    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. Adriane G Otopalik
  2. Jason Pipkin
  3. Eve Marder
(2019)
Neuronal morphologies built for reliable physiology in a rhythmic motor circuit
eLife 8:e41728.
https://doi.org/10.7554/eLife.41728

Share this article

https://doi.org/10.7554/eLife.41728

Further reading

    1. Neuroscience
    Alyssa D Huff, Marlusa Karlen-Amarante ... Jan-Marino Ramirez
    Research Advance

    Obstructive sleep apnea (OSA) is a prevalent sleep-related breathing disorder that results in multiple bouts of intermittent hypoxia. OSA has many neurological and systemic comorbidities, including dysphagia, or disordered swallow, and discoordination with breathing. However, the mechanism in which chronic intermittent hypoxia (CIH) causes dysphagia is unknown. Recently, we showed the postinspiratory complex (PiCo) acts as an interface between the swallow pattern generator (SPG) and the inspiratory rhythm generator, the preBötzinger complex, to regulate proper swallow-breathing coordination (Huff et al., 2023). PiCo is characterized by interneurons co-expressing transporters for glutamate (Vglut2) and acetylcholine (ChAT). Here we show that optogenetic stimulation of ChATcre:Ai32, Vglut2cre:Ai32, and ChATcre:Vglut2FlpO:ChR2 mice exposed to CIH does not alter swallow-breathing coordination, but unexpectedly disrupts swallow behavior via triggering variable swallow motor patterns. This suggests that glutamatergic–cholinergic neurons in PiCo are not only critical for the regulation of swallow-breathing coordination, but also play an important role in the modulation of swallow motor patterning. Our study also suggests that swallow disruption, as seen in OSA, involves central nervous mechanisms interfering with swallow motor patterning and laryngeal activation. These findings are crucial for understanding the mechanisms underlying dysphagia, both in OSA and other breathing and neurological disorders.

    1. Neuroscience
    Vezha Boboeva, Alberto Pezzotta ... Athena Akrami
    Research Article

    The central tendency bias, or contraction bias, is a phenomenon where the judgment of the magnitude of items held in working memory appears to be biased toward the average of past observations. It is assumed to be an optimal strategy by the brain and commonly thought of as an expression of the brain’s ability to learn the statistical structure of sensory input. On the other hand, recency biases such as serial dependence are also commonly observed and are thought to reflect the content of working memory. Recent results from an auditory delayed comparison task in rats suggest that both biases may be more related than previously thought: when the posterior parietal cortex (PPC) was silenced, both short-term and contraction biases were reduced. By proposing a model of the circuit that may be involved in generating the behavior, we show that a volatile working memory content susceptible to shifting to the past sensory experience – producing short-term sensory history biases – naturally leads to contraction bias. The errors, occurring at the level of individual trials, are sampled from the full distribution of the stimuli and are not due to a gradual shift of the memory toward the sensory distribution’s mean. Our results are consistent with a broad set of behavioral findings and provide predictions of performance across different stimulus distributions and timings, delay intervals, as well as neuronal dynamics in putative working memory areas. Finally, we validate our model by performing a set of human psychophysics experiments of an auditory parametric working memory task.