Over the past years, numerous methods have emerged to automate the quantification of
animal behavior at a resolution not previously imaginable. This has opened up a new field of …

Animal behavior is shaped by a variety of" internal states"—partially hidden variables that
profoundly shape perception, cognition, and action. The neural basis of internal states, such …

Keypoint tracking algorithms can flexibly quantify animal movement from videos obtained in
a wide variety of settings. However, it remains unclear how to parse continuous keypoint …

Extracting behavioral measurements non-invasively from video is stymied by the fact that it is
a hard computational problem. Recent advances in deep learning have tremendously …

The study of naturalistic social behavior requires quantification of animals' interactions. This
is generally done through manual annotation—a highly time-consuming and tedious …

We present a comprehensive, detailed review of time-series data analysis, with emphasis on
deep time-series clustering (DTSC), and a case study in the context of movement behavior …

The use of rigorous ethological observation via machine learning techniques to understand
brain function (computational neuroethology) is a rapidly growing approach that is poised to …

The process of quantifying and analyzing animal behavior involves translating the naturally
occurring descriptive language of their actions into machine-readable code. Yet, codifying …

Contemporary pose estimation methods enable precise measurements of behavior via
supervised deep learning with hand-labeled video frames. Although effective in many cases …

Recently developed methods for video analysis, especially models for pose estimation and
behavior classification, are transforming behavioral quantification to be more precise …