Evidence map›Paper›PMID 32040540›Full record

ArticlePloS one2020

USVSEG: A robust method for segmentation of ultrasonic vocalizations in rodents.

Ryosuke O Tachibana, Kouta Kanno, Shota Okabe, Kohta I Kobayasi, Kazuo Okanoya

Abstract read
In one paragraph

Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.

0numbers the graph read from it
0cells of the map it votes in
36citing 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

36 citing papers in PubMed.

  1. Article
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  8. Vocal recognition of partners by female prairie voles.bioRxiv : the preprint server for biology · 2024
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  9. Article
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  11. The breath shape controls intonation of mouse vocalizations.bioRxiv : the preprint server for biology · 2024
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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

5 authors.

Ryosuke O TachibanaDepartment of Life Sciences, Graduate School of Arts & Sciences, The University of Tokyo, Tokyo, Japan.ORCID 0000-0002-4766-4504
Kouta KannoLaboratory of Neuroscience, Course of Psychology, Department of Humanities, Faculty of Law, Economics and the Humanities, Kagoshima University, Kagoshima, Japan.
Shota OkabeDivision of Brain and Neurophysiology, Department of Physiology, Jichi Medical University, Tochigi, Japan.
Kohta I KobayasiGraduate School of Life and Medical Sciences, Doshisha University, Kyoto, Japan.
Kazuo OkanoyaDepartment of Life Sciences, Graduate School of Arts & Sciences, The University of Tokyo, Tokyo, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Rodents' ultrasonic vocalizations (USVs) provide useful information for assessing their social behaviors. Despite previous efforts in classifying subcategories of time-frequency patterns of USV syllables to study their functional relevance, methods for detecting vocal elements from continuously recorded data have remained sub-optimal. Here, we propose a novel procedure for detecting USV segments in continuous sound data containing background noise recorded during the observation of social behavior. The proposed procedure utilizes a stable version of the sound spectrogram and additional signal processing for better separation of vocal signals by reducing the variation of the background noise. Our procedure also provides precise time tracking of spectral peaks within each syllable. We demonstrated that this procedure can be applied to a variety of USVs obtained from several rodent species. Performance tests showed this method had greater accuracy in detecting USV syllables than conventional detection methods.

Indexed as

AcousticsAnimalsDatabases, FactualFemaleGerbillinaeMaleMiceMice, Inbred BALB CMice, Inbred C57BLMuridaeRatsRats, Inbred LewRodentiaSignal Processing, Computer-AssistedSignal-To-Noise RatioSound Spectrography

Identifiers

PMID32040540
PMCPMC7010259

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LicenceCC BY
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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.