Evidence map›Paper›PMID 35309686›Full record

ArticleFrontiers in behavioral neuroscience2022

Semi-Automated Training of Rat Ultrasonic Vocalizations.

Aaron M Johnson, Charles Lenell, Elizabeth Severa, Denis Michael Rudisch, Robert A Morrison, Adrianna C Shembel

Abstract read
In one paragraph

Article in Frontiers in behavioral neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Review
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.

Aaron M JohnsonDepartment of Otolaryngology-Head and Neck Surgery, New York University Grossman School of Medicine, New York, NY, United States.
Charles LenellDepartment of Surgery, University of Wisconsin-Madison, Madison, WI, United States.
Elizabeth SeveraDepartment of Otolaryngology-Head and Neck Surgery, New York University Grossman School of Medicine, New York, NY, United States.
Denis Michael RudischDepartment of Communication Sciences and Disorders, University of Wisconsin-Madison, Madison, WI, United States.
Robert A MorrisonDepartment of Speech Language and Hearing, School of Behavioral and Brain Sciences, UT Dallas, Dallas, TX, United States.
Adrianna C ShembelDepartment of Speech Language and Hearing, School of Behavioral and Brain Sciences, UT Dallas, Dallas, TX, United States.

Funding

University of Wisconsin Voice Research Training Program (T32)T32DC009401 · NIDCD · UNIVERSITY OF WISCONSIN-MADISON · PI Susan Lynn Thibeault · 2009 to 2026
$6.3M
Development of a behavioral rat model to assess proteomic and metabolomic adaptations of laryngeal muscles in response to vocal exerciseR21DC018107 · NIDCD · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI JOHNSON, AARON MATTHEW · 2020 to 2022
$509k
NIDCD NIH HHS R21 DC018107NIDCD NIH HHS T32 DC009401
6 · The paper itself

Abstract

Rats produce ultrasonic vocalizations (USVs) for conspecific communication. These USVs are valuable biomarkers for studying behavioral and mechanistic changes in a variety of diseases and disorders. Previous work has demonstrated operant conditioning can progressively increase the number of USVs produced by rats over multiple weeks. This operant conditioning paradigm is a useful model for investigating the effects of increased laryngeal muscle use on USV acoustic characteristics and underlying central and peripheral laryngeal sensorimotor mechanisms. Previous USV operant conditioning studies relied on manual training to elicit USV productions, which is both time and labor intensive and can introduce human variability. This manuscript introduces a semi-automated method for training rats to increase their rate of USV production by pairing commercially available operant conditioning equipment with an ultrasonic detection system. USV training requires three basic components: elicitation cue, detection of the behavior, and a reward to reinforce the desired behavior. With the semi-automated training paradigm, indirect exposure to the opposite sex or an olfactory cue can be used to elicit USV production. The elicited USV is then automatically detected by the ultrasonic acoustic system, which consequently triggers the release of a sucrose pellet reward. Our results demonstrate this semi-automated procedure produces a similar increase in USV production as the manual training method. Through automation of USV detection and reward administration, staffing requirements, human error, and subject behavioral variability may be minimized while scalability and reproducibility are increased. This automation may also result in greater experimental flexibility, allowing USV training paradigms to become more customizable for a wider array of applications. This semi-automated USV behavioral training paradigm improves upon manual training techniques by increasing the ease, speed, and quality of data collection.

Indexed as

automated trainingoperant conditioningratultrasonic vocalizationsvoice

Identifiers

PMID35309686
PMCPMC8931525

What OpenQuestion holds

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LicenceCC BY
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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.