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Updated: May 26, 2026

A Flexible Platform for Monitoring Cerebellum-Dependent Sensory Associative Learning
Published on: January 19, 2022
iMOSS: an integrated open-source tail suspension test platform for high-resolution immobility scoring and
Zengyou Ye1, Xia Min1, Sarah T Johnson1
1Behavioral Neuroscience Research Branch, Intramural Research Program, National Institute on Drug Abuse, National Institutes of Health, Baltimore, MD, United States.
Abstract:
The tail suspension test (TST) is widely used to assess stress-coping behavior in rodents, characterized by alternating periods of active (struggling) and passive (immobile) responses. Immobility in the TST is interpreted as behavioral despair and serves as a key measure for screening antidepressant compounds. Traditional manual scoring is labor-intensive and temporally imprecise, while existing automated systems often misclassify behaviors and have not shown the capacity to integrate behavioral data with neural recording methods. Here, we improved upon the traditional TST with our new developed iMOSS (Immobility/Mobility Optimized Scoring System)-two open-source, low-cost, and scalable tools for high-resolution quantification of mobility and immobility: (1) iMOSS-MV, a video-based frame-by-frame manual-scoring software instrument designed to precisely annotate the exact onset frame for each binary event, and (2) iMOSS-AS, a sensor-based automated instrument detecting immobility/mobility bouts from the sensor-signal using a machine-learning optimized detection threshold. The output from iMOSS-AS closely matched that from iMOSS-MV and outperformed other publicly available tools. Moreover, both systems reliably detected changes in mobility and immobility induced by imipramine treatment, demonstrating sensitivity to pharmacological manipulation. Finally, both iMOSS tools readily integrated with neural data, as shown by simultaneous analysis of medial septal glutamatergic calcium activity via fiber photometry. Thus, either iMOSS-MV or iMOSS-AS alone offers an efficient, user-friendly, and bias-minimized platform for high-throughput behavioral analysis, enabling seamless integration of behavioral and neural data in systems neuroscience research.
