Traditional methods for understanding animal behavior through videos required experimenters to rewatch videos and manually score timing and location of events. This approach is time consuming, and prone to inconsistencies between different scorers. Pose estimation...
Björn Albrecht and colleagues in the lab of York Winter from Humboldt Universität have developed an innovative system that enhances the efficiency of markerless pose estimation. Their method integrates existing technologies like KineWheel and DeepLabCut, specifically...
ArUco (“Augmented Reality University of Cordoba”) Markers were developed by Thomas Smith and Trevor Smith in a joint effort with collaborators from the University of Texas at Dallas, West Virginia University, and Case Western Reserve University. These...
Understanding how we make decisions is a core challenge in cognitive science. Sequential Sampling Models (SSMs) offer a powerful way to analyze this process by modeling how we accumulate evidence before making a choice. A new Python toolbox called HSSM (for...
Spatial cognition paradigms in animal models tend to focus on allocentric means of navigation where animals rely on environmental landmarks. There is a need for spatial cognition paradigms that also take egocentric navigation into account, where an animal’s own point...
