Evidence map›Paper›PMID 34434780›Full record

ArticleMethodsX2021

Methods for frequency and correlation analyses of neurograms.

Ginette Horcholle-Bossavit, Brigitte Quenet

Abstract read
In one paragraph

Article in MethodsX, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Ginette Horcholle-BossavitSorbonne Université, INSERM, UMRS1158 Neurophysiologie respiratoire expérimentale et clinique, Paris F-75013, France.
Brigitte QuenetPSL Research University, ESPCI-Paris Équipe de Statistique Appliquée, Paris F-75005, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Many physiological functions are based on motor rhythmic activities, among them breathing is a vital issue. The method presented here, or 'temporal grid extraction', aims at characterizing the temporal organization of such an activity. Beyond the measurement of the fundamental frequency, defining the successive cycles, some signal processing tools are helpful in order to look for the presence of higher frequency components that potentially structure these cycles. The method is applied to neurograms recorded from frog brainstem preparations, where two cycle types, buccal and lung cycles, may alternate. It relies on:•Continues Wavelet Transform (CWT) for time-frequency maps and frequency profiles•Crosscorrelation analysis for amplitude maps and amplitude profiles•Cycle-by-cycle autocorrelation analysis for autocorrelation maps and autocorrelation profilesUsing this method, the maps and profiles have revealed that a common high frequency clock drives both buccal and lung cycles.

Indexed as

Amplitude profileAutocorrelationCrosscorrelationCWT analysisCycle-by-cycle variabilityFrequency profileNeurogram processingOscillation profileRhythmic activity

Identifiers

PMID34434780
PMCPMC8374271

What OpenQuestion holds

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Registered trials

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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.