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Automated classification of acoustic startle reflex waveforms in young CBA/CaJ mice using machine learning

Timothy J Fawcett1, Chad S Cooper2, Ryan J Longenecker2

  • 1Global Center for Hearing and Speech Research, University of South Florida, Tampa, FL, USA; Research Computing, University of South Florida, Tampa, FL, USA; Department of Chemical and Biomedical Engineering, University of South Florida, Tampa, FL, USA.

Journal of Neuroscience Methods
|July 16, 2020
PubMed
Summary

A new machine learning method accurately classifies acoustic startle responses (ASRs) in mice, overcoming variability in current analysis techniques. This approach improves the reliability of ASR data for multisensory research.

Keywords:
Acoustic startle responseEnsemble modelsMachine learningPre-pulse inhibitionRandom forest

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