Cheese3D enables sensitive detection and analysis of whole-face movement in mice

Facial expressions and movements, from a subtle and ephemeral grimace to vigorous and rapid chewing, offer direct insights into the moment-to-moment changes of neural and physiological processes. Mice, with discernible facial responses and evolutionarily conserved mammalian facial movement control circuits, provide an ideal model in which to unravel the link between facial movement and underlying states. However, existing frameworks lack the spatial or temporal resolution to sensitively track all movements of the mouse face because of its small and conical form factor. We introduce Cheese3D, a computer vision system that captures high-speed 3D motion of the entire mouse face (including ears, eyes, whisker pad and jaw, covering both sides of the face), using a calibrated six-camera array. The interpretable framework extracts dynamics of anatomically meaningful 3D facial features in absolute world units at sub-mm precision. The precise face-wide motion data generated by Cheese3D provides clear insights, as shown by proof-of-principle experiments predicting anesthetic depth from changing facial patterns, inferring tooth and muscle anatomy from fast ingestion motions across the entire face, measuring minute differences in movements evoked by brainstem stimulation and relating neural activity to spontaneous facial movements, including expressive features only measurable in 3D (for example, angles of ear motion). Cheese3D can serve as a discovery tool that renders subtle mouse facial movements as a highly interpretable readout of otherwise hidden processes.

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Publication Details

Journal
Nature Neuroscience
Published
2026-04-27
DOI
https://doi.org/10.1038/s41593-026-02262-8
Primary Topic
Face Recognition and Perception
Type
article
Field-Weighted Citation Impact
0.00

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article

Cheese3D enables sensitive detection and analysis of whole-face movement in mice

Xun Helen Hou, Kyle Daruwalla, Jeremy C. Borniger, Zainab Ahmad et al.
Nature Neuroscience
Face Recognition and Perception
article

Cheese3D enables sensitive detection and analysis of whole-face movement in mice

Xun Helen Hou, Kyle Daruwalla, Jeremy C. Borniger, Zainab Ahmad, Irene Nozal Martin, Diana Naglič, Linghua Zhang, Xinyan Zhang, Rubin Zhao, Andrew Frankel, Catherine Rasgaitis
article en

Abstract

Facial expressions and movements, from a subtle and ephemeral grimace to vigorous and rapid chewing, offer direct insights into the moment-to-moment changes of neural and physiological processes. Mice, with discernible facial responses and evolutionarily conserved mammalian facial movement control circuits, provide an ideal model in which to unravel the link between facial movement and underlying states. However, existing frameworks lack the spatial or temporal resolution to sensitively track all movements of the mouse face because of its small and conical form factor. We introduce Cheese3D, a computer vision system that captures high-speed 3D motion of the entire mouse face (including ears, eyes, whisker pad and jaw, covering both sides of the face), using a calibrated six-camera array. The interpretable framework extracts dynamics of anatomically meaningful 3D facial features in absolute world units at sub-mm precision. The precise face-wide motion data generated by Cheese3D provides clear insights, as shown by proof-of-principle experiments predicting anesthetic depth from changing facial patterns, inferring tooth and muscle anatomy from fast ingestion motions across the entire face, measuring minute differences in movements evoked by brainstem stimulation and relating neural activity to spontaneous facial movements, including expressive features only measurable in 3D (for example, angles of ear motion). Cheese3D can serve as a discovery tool that renders subtle mouse facial movements as a highly interpretable readout of otherwise hidden processes.

Nature Neuroscience
Cold Spring Harbor Laboratory (US), Stony Brook University (US)
Brain and Behavior Research Foundation, Fulbright Association
Openalex Percentile: Top 6%
Face Recognition and Perception
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