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Measuring Behavior in the Home Cage: Study Design, Applications, Challenges, and Perspectives
Open accessAbstract
The reproducibility crisis (or replication crisis) in biomedical research is a particularly existential and under-addressed issue in the field of behavioral neuroscience, where, in spite of efforts to standardize testing and assay protocols, several known and unknown sources of confounding environmental factors add to variance. Human interference is a major contributor to variability both within and across laboratories, as well as novelty-induced anxiety. Attempts to reduce human interference and to measure more "natural" behaviors in subjects has led to the development of automated home-cage monitoring systems. These systems enable prolonged and longitudinal recordings, and provide large continuous measures of spontaneous behavior that can be analyzed across multiple time scales. In this review, a diverse team of neuroscientists and product developers share their experiences using such an automated monitoring system that combines Noldus PhenoTyper® home-cages and the video-based tracking software, EthoVision® XT, to extract digital biomarkers of motor, emotional, social and cognitive behavior. After presenting our working definition of a “home-cage”, we compare home-cage testing with more conventional out-of-cage tests (e.g., the open field) and outline the various advantages of the former, including opportunities for within-subject analyses and assessments of circadian and ultradian activity. Next, we address technical issues pertaining to the acquisition of behavioral data, such as the fine-tuning of the tracking software and the potential for integration with biotelemetry and optogenetics. Finally, we provide guidance on which behavioral measures to emphasize, how to filter, segment, and analyze behavior, and how to use analysis scripts. We summarize how the PhenoTyper has applications to study neuropharmacology as well as animal models of neurodegenerative and neuropsychiatric illness. Looking forward, we examine current challenges and the impact of new developments. Examples include the automated recognition of specific behaviors, unambiguous tracking of individuals in a social context, the development of more animal-centered measures of behavior and ways of dealing with large datasets. Together, we advocate that by embracing standardized home-cage monitoring platforms like the PhenoTyper, we are poised to directly assess issues pertaining to reproducibility, and more importantly, measure features of rodent behavior under more ethologically relevant scenarios.
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“Indeed, more sophisticated methods are becoming available for continuous recording and scoring of behavior in a home cage (Greico et al., 2021).”
From The rough-and-tumble play of rats as a natural behavior suitable for studying the social brain (2022) · cites this paper as Greico et al., 2021
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Pain assessment in laboratory species
Whittaker, A. L., & Brown, C. (2023) · Elsevier eBooks · doi:10.1016/b978-0-12-822215-7.00019-6
Laz, M.-A. D., Lampe, M., Connor, I., Shestachuk, D., Ludwig, M., Müller, U., Strauch, O. F., Suendermann, N., Lüth, S., & Kah, J. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.08.06.552188
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Self-citationVocalisations as a potential indicator of parturition in C57BL/6J mice
Capas-Peneda, S., Ferreira, A. I., Gilbert, C. L., Prins, J., Vanderplank, A., Rosati, G., Garzola, M., Olsson, I. A. S., & Morello, G. M. (2025) · Animal Welfare · doi:10.1017/awf.2025.10022
Викторовна, К. А., Lang, B., Jaap, A., Thöne‐Reineke, C., Lewejohann, L., & Mieske, P. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5346780
Kendricks, D. R., Sleiman, S. J., Fry, S. A., Stallone, J., Bernstein, B. J., Stevanovic, K. D., Wilson, L. R., Alexander, G. M., McCann, K. E., Dudek, S. M., et al. (2025) · Hormones and Behavior · doi:10.1016/j.yhbeh.2025.105794
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Automated home-cage-like monitoring for assessing innate behaviors in a murine hangover model
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Zoldi, A., Körmöczi, L., Plesz, S. B., Adlan, L. G., Kékesi, G., Liszli, P., Nyúl, L. G., Braunitzer, G., & Horváth, G. (2025) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2025.1601714
Kaura, R. L., Hrnčić, D., Dervišević, A., Borbélyová, V., Cevik, Ö. S., Heffer, M., & Čater, M. (2025) · Slovenian Veterinary Research · doi:10.26873/svr-2247-2025
Jura, B., Lenarczyk, M., Harda, Z., Szumiec, Ł., Ziemiańska, M., Kłosowicz, R., Parkitna, J. M. R., & Wojcik, D. K. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.11.12.687796
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Tracking Spatial and Activity Patterns in Captive Reptiles Using Deep Learning
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Metadata
- Authors
- Grieco, F., Bernstein, B. J., Biemans, B., Bikovski, L., Burnett, C. J., Cushman, J. D., van Dam, E. A., Fry, S. A., Richmond-Hacham, B., Homberg, J. R., Kas, M. J. H., Kessels, H. W., Koopmans, B., Krashes, M. J., Krishnan, V., Logan, S., Loos, M., McCann, K. E., Parduzi, Q., Pick, C. G., Prevot, T. D., Riedel, G., Robinson, L., Sadighi, M., Smit, A. B., Sonntag, W., Roelofs, R. F., Tegelenbosch, R. A. J., & Noldus, L. P. J. J.
- Affiliations
- Noldus Information Technology (NL)
- National Institutes of Health (US)
- F. Hoffmann-La Roche AG (CH)
- Tel Aviv University (IL)
- Icahn School of Medicine at Mount Sinai (US)
- Radboud University Medical Center (NL)
- University of Groningen (NL)
- University of Amsterdam (NL)
- Sylics (Netherlands) (NL)
- Baylor College of Medicine (US)
- University of Oklahoma Health Sciences Center (US)
- University of Aberdeen (GB)
- Vrije Universiteit Amsterdam (NL)
- Radboud University Nijmegen (NL)
- Corresponding author
- Noldus, Lucas P.J.J.
- ORCID
- Grieco, Fabrizio
- Bernstein, Briana J.
- Biemans, Barbara
- Bikovski, Lior
- Burnett, C. Joseph
- Cushman, Jesse D.
- van Dam, Elsbeth A.
- Fry, Sydney A.
- Richmond-Hacham, Bar
- Homberg, Judith R.
- Kas, Martien J. H.
- Kessels, Helmut W.
- Koopmans, Bastijn
- Krashes, Michael J.
- Krishnan, Vaishnav
- Logan, Sreemathi
- Loos, Maarten
- McCann, Katharine E.
- Parduzi, Qendresa
- Pick, Chaim G.
- Riedel, Gernot
- Robinson, Lianne
- Smit, August B.
- Sonntag, William
- Noldus, Lucas P.J.J.
- Venue
- Frontiers in Behavioral Neuroscience
- Publisher
- Frontiers Media SA
- Published
- 2021-09-24
- Volume
- 15
- Pages
- 735387-735387
- ISSN
- 1662-5153 (ISSN-L)
- PMC
- PMC8498589
- OpenAlex
- W3200442339
- Cited by
- 109
- References
- 255
- Citations by year
- 2026: 21 · 2025: 36 · 2024: 16 · 2023: 25 · 2022: 11
- FWCI
- 14.84
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Frontiers in Behavioral Neuroscience (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, other-oa)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- VU Research Portal (publishedVersion, other-oa)
- UvA-DARE (University of Amsterdam) (submittedVersion, other-oa)
- Radboud Repository (Radboud University) (submittedVersion, other-oa)
- Aberdeen University Research Archive (Aberdeen University) (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- University of Groningen research database (University of Groningen / Centre for Information Technology) (submittedVersion, cc-by)
- Data Archiving and Networked Services (DANS) (submittedVersion, other-oa)
- Funders
- National Institutes of Health
- National Institute on Aging (R00AG056662)
- National Institute of General Medical Sciences (P20GM125528)
- Topics
- Life Sciences › Agricultural and Biological Sciences › Animal Science and Zoology › Animal Behavior and Welfare Studies
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neuropharmacology Research
- Life Sciences › Neuroscience › Cognitive Neuroscience › Memory and Neural Mechanisms
- Keywords
- home cage monitoring, automated video tracking, digital biomarkers, rodent behavior, replication crisis, human disturbance, biotelemetry, optogenetics, behavioral segmentation, neuropharmacology, animal models of neurodegeneration, within-subject analysis
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