PixelPaws: a low-cost, open-source integrated platform for automated scoring of mouse behaviors
- 1Washington University School of Medicine in St. Louis
Abstract
Behavioral scoring is central to preclinical pain research but is typically performed manually, which is inherently low-throughput and subject to variability between observers. Automated alternatives exist, but cost and programming expertise limit adoption beyond the laboratories that build them. Here we describe PixelPaws, an open-source platform combining a near-infrared imaging enclosure built from consumer parts for under $300, multi-camera acquisition software, a bundled pose-estimation network, and eight classifiers in a graphical user interface. We evaluated the platform across standard assays of pain, itch, and opioid withdrawal. Licking, scratching, and jumping classifiers were validated against trained human observers by leave-one-session-out evaluation. In the formalin assay, classifier-scored licking followed the expected biphasic time course and was reduced dose-dependently by oxycodone, with a phase 2 potency estimate comparable to blinded manual scoring. Chloroquine roughly tripled scratching, and naloxone precipitated a burst of jumping in oxycodone-treated mice. From the same recordings we derived a set of paw contour metrics. Contour intensity fell after formalin and tracked the oxycodone dose series, and contour area shifted toward symmetry after oxycodone in nerve-injured mice. Behavioral sequencing revealed distinct changes in the transi
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BibTeX
@misc{slivicki2026pixelpaws,
title = {{PixelPaws: a low-cost, open-source integrated platform for automated scoring of mouse behaviors}},
author = {R. A. Slivicki and H. Wang and J. M. Mwirigi and K. Kucz and H. Hua and M. C. Creed and R. W. Gereau},
howpublished = {bioRxiv},
year = {2026},
month = sep,
doi = {10.64898/2026.09.19.752787},
url = {https://www.biorxiv.org/content/10.64898/2026.09.19.752787v1},
note = {CC BY-NC},
}
RIS
TY - UNPB
TI - PixelPaws: a low-cost, open-source integrated platform for automated scoring of mouse behaviors
AU - R. A. Slivicki
AU - H. Wang
AU - J. M. Mwirigi
AU - K. Kucz
AU - H. Hua
AU - M. C. Creed
AU - R. W. Gereau
PY - 2026
DA - 2026/09/19
PB - bioRxiv
DO - 10.64898/2026.09.19.752787
UR - https://www.biorxiv.org/content/10.64898/2026.09.19.752787v1
AB - Behavioral scoring is central to preclinical pain research but is typically performed manually, which is inherently low-throughput and subject to variability between observers. Automated alternatives exist, but cost and programming expertise limit adoption beyond the laboratories that build them. Here we describe PixelPaws, an open-source platform combining a near-infrared imaging enclosure built from consumer parts for under $300, multi-camera acquisition software, a bundled pose-estimation network, and eight classifiers in a graphical user interface. We evaluated the platform across standard assays of pain, itch, and opioid withdrawal. Licking, scratching, and jumping classifiers were validated against trained human observers by leave-one-session-out evaluation. In the formalin assay, classifier-scored licking followed the expected biphasic time course and was reduced dose-dependently by oxycodone, with a phase 2 potency estimate comparable to blinded manual scoring. Chloroquine roughly tripled scratching, and naloxone precipitated a burst of jumping in oxycodone-treated mice. From the same recordings we derived a set of paw contour metrics. Contour intensity fell after formalin and tracked the oxycodone dose series, and contour area shifted toward symmetry after oxycodone in nerve-injured mice. Behavioral sequencing revealed distinct changes in the transi
ER -