Evidence map›Paper›PMID 26464980›Full record

ArticleeNeuro

Sigh and Eupnea Rhythmogenesis Involve Distinct Interconnected Subpopulations: A Combined Computational and Experimental Study

Natalia Toporikova, Marc Chevalier, Muriel Thoby-Brisson

Abstract read
In one paragraph

Article in eNeuro. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

18 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Article
  5. Article
  6. Dynamics of ramping bursts in a respiratory neuron model.Journal of computational neuroscience · 2022
    Article
  7. Article
  8. Review
  9. Article
  10. The sigh and related behaviors.Handbook of clinical neurology · 2022
    Review
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. 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

3 authors.

Natalia ToporikovaDepartment of Biology, Washington and Lee University , Lexington, Virginia 24450.
Marc ChevalierInstitut de Neurosciences Cognitives et Intégratives d'Aquitaine, CNRS UMR 5287 , Université de Bordeaux , 33076 Bordeaux, France.
Muriel Thoby-BrissonInstitut de Neurosciences Cognitives et Intégratives d'Aquitaine, CNRS UMR 5287 , Université de Bordeaux , 33076 Bordeaux, France.

Funding

Neuronal Determinants of Respiratory RhythmogenesisR01HL088886 · NHLBI · GEORGIA INSTITUTE OF TECHNOLOGY · PI BUTERA, ROBERT J · 2008 to 2011
$742k
NHLBI NIH HHS R01 HL088886
6 · The paper itself

Abstract

Neural networks control complex motor outputs by generating several rhythmic neuronal activities, often with different time scales. One example of such a network is the pre-Bötzinger complex respiratory network (preBötC) that can simultaneously generate fast, small-amplitude, monophasic eupneic breaths together with slow, high-amplitude, biphasic augmented breaths (sighs). However, the underlying rhythmogenic mechanisms for this bimodal discharge pattern remain unclear, leaving two possible explanations: the existence of either reconfiguring processes within the same network or two distinct subnetworks. Based on recent in vitro data obtained in the mouse embryo, we have built a computational model consisting of two compartments, interconnected through appropriate synapses. One compartment generates sighs and the other produces eupneic bursts. The model reproduces basic features of simultaneous sigh and eupnea generation (two types of bursts differing in terms of shape, amplitude, and frequency of occurrence) and mimics the effect of blocking glycinergic synapses. Furthermore, we used this model to make predictions that were subsequently tested on the isolated preBötC in mouse brainstem slice preparations. Through a combination of in vitro and in silico approaches we find that (1) sigh events are less sensitive to network excitability than eupneic activity, (2) calcium-dependent mechanisms and the Ih current play a prominent role in sigh generation, and (3) specific parameters of Ih activation set the low sensitivity to excitability in the sigh neuronal subset. Altogether, our results strongly support the hypothesis that distinct subpopulations within the preBötC network are responsible for sigh and eupnea rhythmogenesis.

Indexed as

computational modelin vitropre-Bötzinger complexrespiratory networksigh generation

Identifiers

PMID26464980
PMCPMC4596094

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.