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 …

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 …

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 …

Quantitative behavioral measurements are important for answering questions across
scientific disciplines—from neuroscience to ecology. State-of-the-art deep-learning methods …

The brain is worthy of study because it is in charge of behavior. A flurry of recent technical
advances in measuring and quantifying naturalistic behaviors provide an important …

The need for automated and efficient systems for tracking full animal pose has increased
with the complexity of behavioral data and analyses. Here we introduce LEAP (LEAP …

Animals produce vocalizations that range in complexity from a single repeated call to
hundreds of unique vocal elements patterned in sequences unfolding over hours …

Studying naturalistic animal behavior remains a difficult objective. Recent machine learning
advances have enabled limb localization; however, extracting behaviors requires …

Internal states shape stimulus responses and decision-making, but we lack methods to
identify them. To address this gap, we developed an unsupervised method to identify …

The first response exhibited by animals to changing environments is typically behavioral.
Behavior is thus central to predicting, and mitigating, the impacts that natural and …