Evidence map›Paper›PMID 20927576›Full record

ArticleJournal of computational neuroscience2011

Interacting oscillations in neural control of breathing: modeling and qualitative analysis.

Jonathan E Rubin, Bartholomew J Bacak, Yaroslav I Molkov, Natalia A Shevtsova, Jeffrey C Smith, Ilya A Rybak

Abstract read
In one paragraph

Article in Journal of computational neuroscience, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed
–field-weighted citation impact
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

35 citing papers in PubMed.

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  19. Computational models of the neural control of breathing.Wiley interdisciplinary reviews. Systems biology and medicine · 2017
    Review
  20. 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

6 authors.

Jonathan E RubinDepartment of Mathematics, University of Pittsburgh, 301 Thackeray Hall, Pittsburgh, PA 15260, USA. rubin@math.pitt.edu
Bartholomew J Bacak
Yaroslav I Molkov
Natalia A Shevtsova
Jeffrey C Smith
Ilya A Rybak

Funding

Multi-Scale Models of Neural Mechanisms Controlling Breathing in MammalsZIANS003108 · NINDS · NATIONAL INSTITUTE OF NEUROLOGICAL DISORDERS AND STROKE · PI SMITH, JEFFREY C · 2009 to 2023
$7.5M
Multiscale Model of Neural Control of BreathingR01NS069220 · NINDS · DREXEL UNIVERSITY · PI BEN-TAL, ALONA, DICK, THOMAS E · 2010 to 2014
$2.9M
CRCNS: State dependent neural mechanisms for respiratory pattern generationR01NS057815 · NINDS · DREXEL UNIVERSITY · PI RYBAK, ILYA A · 2006 to 2010
$1.4M
Modeling of pathogenic breathing pattern dysregulation in cardiopulmonary diseaseR33HL087379 · NHLBI · DREXEL UNIVERSITY · PI RYBAK, ILYA A · 2008 to 2010
$561k
Intramural NIH HHSNHLBI NIH HHS R33 HL087379NINDS NIH HHS R01 NS057815NINDS NIH HHS R01 NS069220
6 · The paper itself

Abstract

In mammalian respiration, late-expiratory (late-E, or pre-inspiratory) oscillations emerge in abdominal motor output with increasing metabolic demands (e.g., during hypercapnia, hypoxia, etc.). These oscillations originate in the retrotrapezoid nucleus/parafacial respiratory group (RTN/pFRG) and couple with the respiratory oscillations generated by the interacting neural populations of the Bötzinger (BötC) and pre-Bötzinger (pre-BötC) complexes, representing the kernel of the respiratory central pattern generator. Recently, we analyzed experimental data on the generation of late-E oscillations and proposed a large-scale computational model that simulates the possible interactions between the BötC/pre-BötC and RTN/pFRG oscillations under different conditions. Here we describe a reduced model that maintains the essential features and architecture of the large-scale model, but relies on simplified activity-based descriptions of neural populations. This simplification allowed us to use methods of dynamical systems theory, such as fast-slow decomposition, bifurcation analysis, and phase plane analysis, to elucidate the mechanisms and dynamics of synchronization between the RTN/pFRG and BötC/pre-BötC oscillations. Three physiologically relevant behaviors have been analyzed: emergence and quantal acceleration of late-E oscillations during hypercapnia, transformation of the late-E activity into a biphasic-E activity during hypercapnic hypoxia, and quantal slowing of BötC/pre-BötC oscillations with the reduction of pre-BötC excitability. Each behavior is elicited by gradual changes in excitatory drives or other model parameters, reflecting specific changes in metabolic and/or physiological conditions. Our results provide important theoretical insights into interactions between RTN/pFRG and BötC/pre-BötC oscillations and the role of these interactions in the control of breathing under different metabolic conditions.

Indexed as

Models, NeurologicalRespiratory Physiological PhenomenaAnimalsBiological ClocksComputer SimulationHumansMedulla OblongataNeural PathwaysNeuronsRespiratory Center

Identifiers

PMID20927576
PMCPMC3648224

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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.