Evidence map›Paper›PMID 36396795›Full record

ArticleBiological cybernetics2022

Variational and phase response analysis for limit cycles with hard boundaries, with applications to neuromechanical control problems.

Yangyang Wang, Jeffrey P Gill, Hillel J Chiel, Peter J Thomas

Open access · hybridAbstract read
In one paragraph

Article in Biological cybernetics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.9field-weighted citation impact, top 27% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Article
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  4. Article
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  6. Tutorial: using NEURON for neuromechanical simulations.Frontiers in computational neuroscience · 2023
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 2 institutions in 1 country.

Yangyang WangDepartment of Mathematics, The University of Iowa, Iowa City, IA, 52242, USA. yangyang-wang@uiowa.edu.
Jeffrey P GillDepartment of Biology, Case Western Reserve University, Cleveland, OH, 44106, USA.
Hillel J ChielDepartment of Biology, Case Western Reserve University, Cleveland, OH, 44106, USA.
Peter J ThomasDepartments of Mathematics, Applied Mathematics, and Statistics, Case Western Reserve University, Cleveland, OH, 44106, USA.
Case Western Reserve University · USUniversity of Iowa · US

Funding

A novel approach to analyzing functional connectomics and combinatorial control in a tractable small-brain closed-loop systemRF1NS118606 · NINDS · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI BYRNE, JOHN H, CHESTEK, CYNTHIA ANNE · 2020 to 2020
$3.0M
CRCNS: Evidence-based modeling of neuromodulatory action on network propertiesR01DA057767 · NIDA · UNIVERSITY OF IOWA · PI Yangyang Wang · 2022 to 2026
$1.8M
NIDA NIH HHS R01 DA057767NINDS NIH HHS RF1 NS118606
6 · The paper itself

Abstract

Motor systems show an overall robustness, but because they are highly nonlinear, understanding how they achieve robustness is difficult. In many rhythmic systems, robustness against perturbations involves response of both the shape and the timing of the trajectory. This makes the study of robustness even more challenging. To understand how a motor system produces robust behaviors in a variable environment, we consider a neuromechanical model of motor patterns in the feeding apparatus of the marine mollusk Aplysia californica (Shaw et al. in J Comput Neurosci 38(1):25-51, 2015; Lyttle et al. in Biol Cybern 111(1):25-47, 2017). We established in (Wang et al. in SIAM J Appl Dyn Syst 20(2):701-744, 2021. https://doi.org/10.1137/20M1344974 ) the tools for studying combined shape and timing responses of limit cycle systems under sustained perturbations and here apply them to study robustness of the neuromechanical model against increased mechanical load during swallowing. Interestingly, we discover that nonlinear biomechanical properties confer resilience by immediately increasing resistance to applied loads. In contrast, the effect of changed sensory feedback signal is significantly delayed by the firing rates' hard boundary properties. Our analysis suggests that sensory feedback contributes to robustness in swallowing primarily by shifting the timing of neural activation involved in the power stroke of the motor cycle (retraction). This effect enables the system to generate stronger retractor muscle forces to compensate for the increased load, and hence achieve strong robustness. The approaches that we are applying to understanding a neuromechanical model in Aplysia, and the results that we have obtained, are likely to provide insights into the function of other motor systems that encounter changing mechanical loads and hard boundaries, both due to mechanical and neuronal firing properties.

Indexed as

AplysiaFeedback, SensoryAnimalsGravitationAplysiaInfinitesimal phase response curveNonsmooth systemsRobust motor behaviorSensory feedbackVariational dynamics

Identifiers

PMID36396795
PMCPMC9691512
OpenAlexW4309265099

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.