Recurrence quantification analysis in the study of online coordination in Norway rats (Rattus norvegicus).

Abstract

In social animals, studying interactions with conspecifics is crucial for understanding even basic physiological, behavioral, and cognitive processes. Due to a visible “ecological turn” in behavioral research, we observe a rapid development of novel methods devoted to studying interaction. In this article, we offer a case study of an animal interactive behavior, which uses new methods of video-recorded motion capturing combined with time-series analysis called recurrence quantification analysis. We apply the method to the video-recorded behavioral sequence observed in Rattus norvegicus to evidence the fine-grained structure of this behavior. We show how such dynamical analyses can lead to insights about the processes behind such behavioral patterns and their change. Finally, we show how this approach can be successfully applied to other examples of highly coordinated behaviors in the animal world.

The dynamics of dyadic interactions between people of different ethnicities depend on their identification with all humanity

“…We used two tools for these analyses: DeepLabCut. To extract movement from the videos, we followed the approach highlighted in 30 . First, we used an open-source toolbox called DeepLabCut (DLC) that builds on a state-of-the-art pose estimation algorithm (i.e., a computer vision technique that predicts and tracks the location of a person, animal, or object) to precisely track user-defined body parts 31 .…”