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Stride-level analysis of mouse open field behavior using deep-learning-based pose estimation.

Keith Sheppard1, Justin Gardin1, Gautam S Sabnis1

  • 1The Jackson Laboratory, 600 Main Street, Bar Harbor, ME 04609, USA.

Cell Reports
|January 12, 2022
PubMed
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Researchers developed a new AI tool to precisely measure mouse gait and posture in the open field. This study reveals gait and posture deficits in autism spectrum disorder (ASD) models, offering insights into neurological conditions.

Area of Science:

  • Neuroscience
  • Genetics
  • Animal Behavior

Background:

  • Gait and posture abnormalities are common in neurological, neuromuscular, and neuropsychiatric disorders.
  • Rodent models are crucial for understanding disease mechanisms and testing interventions.
  • The open field apparatus is a standard tool for observing mouse behavior.

Purpose of the Study:

  • To develop a neural network-based assay for precise mouse gait and posture analysis using the open field apparatus.
  • To analyze gait and posture across a large cohort of mouse strains.
  • To investigate gait and posture deficits in autism spectrum disorder (ASD) models and understand their genetic basis.

Main Methods:

  • Development of a neural-network-based computational assay for gait and posture analysis.
Keywords:
Machine learninganimal behaviorcomplex behaviorgait analysisgenome-wide association study (GWAS)key-point detectionneural networkpose estimationposture analysisquantitative genetics

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  • Quantification of gait and posture in 62 mouse strains using the open field test.
  • Characterization of four mutant mouse lines with known gait deficits.
  • Genome-wide association study (GWAS) to identify genetic factors influencing mouse movement.

    • Main Results:

    • The developed assay precisely quantitates mouse gait and posture across 62 strains.
    • Multiple autism spectrum disorder (ASD) models exhibit significant gait and posture deficits.
    • Mouse gait and posture measures are highly heritable and can be classified into three distinct groups.
    • A GWAS identified genetic loci associated with stride-level mouse movement.

    Conclusions:

    • The neural-network-based assay provides a high-precision method for analyzing mouse gait and posture.
    • Gait and posture deficits appear to be a general feature in autism spectrum disorder (ASD) models.
    • This study establishes a valuable resource of mouse gait and posture data and offers insights into the genetic architecture of movement traits.