Evidence map›Paper›PMID 23832016›Full record

ArticleJournal of neuroscience methods2013

Automating ultrasonic vocalization analyses: the WAAVES program.

James M Reno, Bryan Marker, Lawrence K Cormack, Timothy Schallert, Christine L Duvauchelle

Abstract read
In one paragraph

Article in Journal of neuroscience methods, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing 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

25 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. DeepSqueak: a deep learning-based system for detection and analysis of ultrasonic vocalizations.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2019
    Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

James M RenoThe University of Texas at Austin, Department of Psychology, Behavioral Neuroscience, 108 East Dean Keeton Avenue, Stop A8000, Austin, TX 78712-1043, USA. jreno@utexas.edu
Bryan Marker
Lawrence K Cormack
Timothy Schallert
Christine L Duvauchelle

Funding

Integrative Neuroscience Initiative on Alcoholism - West - SupplementU01AA013517 · NIAAA · SCRIPPS RESEARCH INSTITUTE, THE · PI ROBERTO, MARISA · 2001 to 2014
$12.7M
Neurochemical & Behavioral Correlates of ETOH EffectsT32AA007471 · NIAAA · UNIVERSITY OF TEXAS AUSTIN · PI Kimberly Nixon · 1987 to 2026
$9.2M
NIAAA NIH HHS T32 AA007471NIAAA NIH HHS U01 AA013517PHS HHS NIAA013517PHS HHS T32 NIAA07471
6 · The paper itself

Abstract

backgroundHuman emotion is a crucial component of drug abuse and addiction. Ultrasonic vocalizations (USVs) elicited by rodents are a highly translational animal model of emotion in drug abuse studies. A major roadblock to comprehensive use of USV data is the overwhelming burden to attain accurate USV assessment in a timely manner. One of the most accurate methods of analyzing USVs, human auditory detection with simultaneous spectrogram inspection, requires USV sound files to be played back 4% normal speed. NEW

methodWAAVES (WAV-file Automated Analysis of Vocalizations Environment Specific) is an automated USV assessment program utilizing MATLAB's Signal and Image Processing Toolboxes in conjunction with a series of customized filters to separate USV calls from background noise, and accurately tabulate and categorize USVs as flat or frequency-modulated (FM) calls. In the current report, WAAVES functionality is demonstrated by USV analyses of cocaine self-administration data collected over 10 daily sessions.

resultsWAAVES counts are significantly correlated with human auditory counts (r(48)=0.9925; p<0.001). Statistical analyses used WAAVES output to examine individual differences in USV responses to cocaine, cocaine-associated cues and relationships between USVs, cocaine intake and locomotor activity. COMPARISON WITH EXISTING

methodWAAVES output is highly accurate and provides tabulated data in approximately 0.3% of the time required when using human auditory detection methods.

conclusionsThe development of a customized USV analysis program, such as WAAVES streamlines USV assessment and enhances the ability to utilize USVs as a tool to advance drug abuse research and ultimately develop effective treatments.

Indexed as

Acoustic StimulationAnalysis of VarianceAnimalsAutomationCocaineCocaine-Related DisordersCuesMaleMotor ActivityRatsRats, Sprague-DawleySelf AdministrationSignal Processing, Computer-AssistedSoftwareUltrasonicsVocalization, AnimalCocaineAddictionCocaineCravingRatSelf-administrationUSV

Identifiers

PMID23832016
PMCPMC3931607

What OpenQuestion holds

Textmetadata
LicenceTDM
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.