TrackUSF, a novel methodology for automated analysis of ultrasonic vocalizations, reveals modified social communication in a rat model of autism
preprint
OA: closed
CC-BY-NC-ND-4.0
Abstract
Rodents emit various social ultrasonic vocalizations (USVs), which reflect their emotional state and mediate social interaction. USVs are usually analyzed by manual or semi-automated methodologies categorizing discrete USVs according to their structure in the frequency-time domains. This laborious analysis hinders effective use of USVs for screening animal models of human pathologies associated with modified social behavior, such as autism spectrum disorder (ASD). Here we present a novel, automated methodology for analyzing USVs, termed TrackUSF. To validate TrackUSF, we analyzed a dataset of mouse mating calls and compared the results with a manual analysis by a trained observer. We found that TrackUSF was capable of detecting most USVs, with less than 1% of false-positive detections. We then employed TrackUSF to social vocalizations in Shank3 -deficient rats, a rat model of ASD and found, for the first time, that these vocalizations exhibit a spectrum of deviations from pro-social calls towards aggressive calls.
My notes (saved in your browser only)
Citation neighborhood (no data yet)
We don't have any in-corpus citations linked to this paper yet. The paper's references may be in our DB but unresolved to ``paper_id`` (resolution happens at ingest when the cited DOI matches a row we already have). Run the cross-source citation reconcile pass to retry.
References (42)
- doi:10.3109/14015439.2010.528788 via crossref
- doi:10.1371/journal.pone.0046610 via crossref
- doi:10.1016/j.jneumeth.2014.08.007 via crossref
- doi:10.1002/aur.1925 via crossref
- doi:10.1093/ilar.50.1.43 via crossref
- doi:10.1016/j.conb.2013.01.014 via crossref
- doi:10.1037/0735-7036.116.1.73 via crossref
- doi:10.1037/0735-7044.115.4.940 via crossref
- doi:10.1037/a0012889 via crossref
- doi:10.1016/j.neubiorev.2010.11.011 via crossref
- doi:10.1038/srep10237 via crossref
- doi:10.1038/srep23305 via crossref
- doi:10.1111/j.1601-183x.2010.00610.x via crossref
- doi:10.1111/j.1601-183x.2010.00610.x via crossref
- doi:10.3389/fnbeh.2012.00089 via crossref
- doi:10.7554/elife.18904 via crossref
- doi:10.1016/j.neubiorev.2016.03.029 via crossref
- doi:10.1111/gbb.12256 via crossref
- doi:10.1037/0033-2909.128.6.961 via crossref
- doi:10.1098/rstb.2011.0222 via crossref
- doi:10.1098/rsbl.2005.0366 via crossref
- doi:10.1016/j.ymssp.2018.10.006 via crossref
- doi:10.1007/s10772-018-9524-7 via crossref
- doi:10.1186/s13229-017-0169-1 via crossref
- doi:10.1037/0096-1523.34.4.1017 via crossref
- doi:10.1016/j.bbr.2007.02.015 via crossref
- doi:10.1098/rstb.2011.0221 via crossref
- doi:10.1016/j.jneumeth.2013.06.006 via crossref
- doi:10.1016/j.beproc.2016.08.005 via crossref
- doi:10.1016/j.neubiorev.2008.08.003 via crossref
- doi:10.1111/j.1601-183x.2010.00623.x via crossref
- doi:10.1590/s0100-879x2012007500038 via crossref
- doi:10.1016/0031-9384(86)90423-3 via crossref
- doi:10.1007/s10479-011-0841-3 via crossref
- doi:10.1016/j.neuron.2017.04.005 via crossref
- doi:10.1109/89.784104 via crossref
- doi:10.1523/jneurosci.1060-14.2014 via crossref
- doi:10.1016/j.neubiorev.2014.03.021 via crossref
- doi:10.1016/j.bbr.2013.05.047 via crossref
- doi:10.1371/journal.pone.0001365 via crossref
- doi:10.1007/s00441-013-1607-9 via crossref
- doi:10.1007/s00213-010-1859-y via crossref
Source provenance
- crossref
- last seen: 2026-07-17T06:50:14.526521+00:00
- europepmc
- last seen: 2026-05-19T01:45:01.086888+00:00
- unpaywall
- last seen: 2026-05-22T02:00:06.705733+00:00
License: CC-BY-NC-ND-4.0