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Translational neuroscience applications for automated detection of rodent grooming with deep learning

Lab Animal volume 50, pages 244–245 (2021)Cite this article

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A Publisher Correction to this article was published on 16 September 2021

This article has been updated

Rodent grooming is an important behaviour that is commonly used to characterize preclinical models of human brain disorders. A new paper has leveraged deep learning to develop a precise, high throughput and automated grooming classifier to facilitate mechanistic neuroscience research on grooming.

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Fig. 1: Schematic of grooming microstructure and different potenital patterns that may not be detected by the grooming classifier developed by Geuther et al.

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Authors and Affiliations

  1. University of Newcastle, Newcastle, Australia

    Nicholas J. Burton, Léonie Borne & Elizbeth E. Manning

  2. Hunter Medical Research Institute, Newcastle, Australia

    Nicholas J. Burton, Léonie Borne & Elizbeth E. Manning

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  1. Nicholas J. Burton
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  2. Léonie Borne
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  3. Elizbeth E. Manning
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Correspondence to Elizbeth E. Manning.

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Burton, N.J., Borne, L. & Manning, E.E. Translational neuroscience applications for automated detection of rodent grooming with deep learning. Lab Anim 50, 244–245 (2021). https://doi.org/10.1038/s41684-021-00830-y

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