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Cited by 1Neural dynamics and brain functionNeuroscience and Neuropharmacology ResearchIon channel regulation and function

Conductance relationships across compartments associated with bursting output in a model of a motor neuron in the crustacean cardiac ganglion

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Dopp, Daniel P., Samarth, Pranit S., Wang, Jing, Kick, Daniel Robert, Schulz, David J., Nair, Satish S.·2026·Journal of Neurophysiology
DOI 10.1152/jn.00324.2024PMC PMC12952988
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Abstract

Our results support the hypotheses that, despite being prevalent in biological neurons, correlated membrane conductances are not a necessary feature of synaptically driven bursting in CPG motor neurons and averaging conductances across motor neurons in a network can maintain biologically realistic output. Our results may be most relevant to similar networks, where “forced bursting” is a result of highly interconnected neurons with strong synaptic input organizing the output.

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  • The 2-7 fold variations in mRNA expression are captured in computational models with degenerate solutions.

    “and this is captured in computational models with degenerate solutions [18,31-34]”

    From A feature and not a bug: Replication failures can lead to new biology (2026) · cites this paper as [31]

    The Introduction says computational models can produce similar activity from many different conductance parameter sets, supporting the point about degenerate solutions. It reports two- to six-fold variation in maximal conductances, not two- to seven-fold variation in mRNA expression, and does not say the models capture that mRNA range. (LLM, conf=0.85)

    Experimental — accuracy not yet measured

  • In computational models it is feasible to examine the structures of the parameter spaces that contribute to an output or a physiological state.

    “In computational models it is feasible to examine the structures of the parameter spaces that contribute to an output or a physiological state [31,42,46,47].”

    From A feature and not a bug: Replication failures can lead to new biology (2026) · cites this paper as [31]

  • Correlations that are present in biological data from the large cells are not necessary for model function.

    “Interestingly, they demonstrate that correlations that are present in biological data from the large cells are not necessary for model function.”

    From A feature and not a bug: Replication failures can lead to new biology (2026) · cites this paper as [31]

  • Averaging need not fail, and the average properties of multiple neurons within a functional circuit may be an excellent predictor of the circuit's function.

    “Of course, averaging need not fail, and the average properties of multiple neurons within a functional circuit may be an excellent predictor of the circuit's function [31].”

    From A feature and not a bug: Replication failures can lead to new biology (2026) · cites this paper as [31]

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Research works printed but not linked: 49

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Cited by

Sorted by citations

Authors
Dopp, D. P., Samarth, P. S., Wang, J., Kick, D. R., Schulz, D. J., & Nair, S. S.
Affiliations
University of Missouri (US)
Corresponding author
  • Dopp, Daniel P.
  • Samarth, Pranit S.
ORCID
Venue
Journal of Neurophysiology
Publisher
American Physiological Society
Published
2026-03-01
Volume
135
Issue
3
Pages
686-704
ISSN
  • 0022-3077 (ISSN-L)
  • 1522-1598
DOI
10.1152/jn.00324.2024
PMC
PMC12952988
OpenAlex
W7125598322
Cited by
1
References
0
Citations by year
2026: 1
FWCI
4.11
Type
journal article
Language
en
Open access
Locations
  • Journal of Neurophysiology (publishedVersion)
  • PubMed Central (publishedVersion)
  • PubMed (publishedVersion)
Funders
  • HHS | National Institutes of Health (MH122023)
  • National Science Foundation (OAC-1730655)
Topics
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
  • Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neuropharmacology Research
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Ion channel regulation and function
Keywords
burst firing, motor neurons, central pattern generator, synaptic input, neuronal output, computational model
MeSH terms
Action Potentials, Animals, Brachyura, Heart, Models, Neurological, Motor Neurons, Gap Junctions, Ganglia, Invertebrate

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