Towards high-throughput phenotyping of complex patterned behaviors in rodents: Focus on mouse self-grooming and its sequencing

Evan Kyzar, Siddharth Gaikwad, Andrew Roth, Jeremy Green, Mimi Pham, Adam Stewart, Yiqing Liang, Vikrant Kobla, Allan V. Kalueff*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

25 Citations (Scopus)

Abstract

Increasingly recognized in biological psychiatry, rodent self-grooming is a complex patterned behavior with evolutionarily conserved cephalo-caudal progression. While grooming is traditionally assessed by the latency, frequency and duration, its sequencing represents another important domain sensitive to various experimental manipulations. Such behavioral complexity requires novel objective approaches to quantify rodent grooming, in addition to time-consuming and highly variable manual observation. The present study combined modern behavior-recognition video-tracking technologies (CleverSys, Inc.) with manual observation to characterize in-depth spontaneous (novelty-induced) and artificial (water-induced) self-grooming in adult male C57BL/6J mice. We specifically focused on individual episodes of grooming (paw licking, head washing, body/leg washing, and tail/genital grooming), their duration and transitions between episodes. Overall, the frequency, duration and transitions detected using the automated approach significantly correlated with manual observations (R=0.51-0.7, p<0.001-0.05). This data validates the software-based detection of grooming, also indicating that behavior-recognition tools can be applied to characterize both the amount and sequential organization (patterning) of rodent grooming. Together with further refinement and methodological advancement, this approach will foster high-throughput neurophenotyping of grooming, with multiple applications in drug screening and testing of genetically modified animals.

Original languageEnglish
Pages (from-to)426-431
Number of pages6
JournalBehavioural Brain Research
Volume225
Issue number2
DOIs
Publication statusPublished - 1 Dec 2011
Externally publishedYes

Keywords

  • Automated detection
  • Behavioral patterning
  • High-throughput assays
  • Mouse self-grooming
  • Neurophenotyping

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