Publikationsdatenbank

Mouse Lockbox Dataset: Behavior Recognition for Mice Solving Lockboxes (2025)

Art

Elektronische Veröffentlichung

Autoren

Reiske, Patrik

Boon, Marcus N.

Andresen, Niek (WE 11)

Traverso, Sole

Hohlbaum, Katharina

Lewejohann, Lars (WE 11)

Thöne‐Reineke, Christa (WE 11)

Hellwich, Olaf

Sprekeler, Henning

Kontakt

Institut für Tierschutz, Tierverhalten und Versuchstierkunde

Königsweg 67
14163 Berlin
+49 30 838 61146
tierschutz@vetmed.fu-berlin.de

Abstract / Zusammenfassung

Machine learning and computer vision methods have a major impact on the study of natural animal behavior, as they enable the (semi-)automatic analysis of vast amounts of video data. Mice are the standard mammalian model system in most research fields, but the datasets available today to refine such methods focus either on simple or social behaviors. In this work, we present a video dataset of individual mice solving complex mechanical puzzles, socalled lockboxes. The more than 110 hours of total playtime show their behavior recorded from three different perspectives. As a benchmark for frame-level action classification methods, we provide human-annotated labels for all videos of two different mice, that equal 13% of our dataset. Our keypoint (pose) tracking-based action classification framework illustrates the challenges of automated labeling of fine-grained behaviors, such as the manipulation of objects. We hope that our work will help accelerate the advancement of automated action and behavior classification in the computational neuroscience community. Our dataset is publicly available at https://doi.org/10.14279/depositonce-23850