Neuroscientists today can measure activity from more neurons than ever before, and are
facing the challenge of connecting these brain-wide neural recordings to computation and …

Recent advances in computer vision and machine learning underpin a collection of
algorithms with an impressive ability to decipher the content of images. These deep learning …

The desire to understand how the brain generates and patterns behavior has driven rapid
methodological innovation in tools to quantify natural animal behavior. While advances in …

Noninvasive behavioral tracking of animals during experiments is critical to many scientific
pursuits. Extracting the poses of animals without using markers is often essential to …

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 …

Comprehensive descriptions of animal behavior require precise three-dimensional (3D)
measurements of whole-body movements. Although two-dimensional approaches can track …

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 …

High‐resolution monitoring is fundamental to understand ecosystems dynamics in an era of
global change and biodiversity declines. While real‐time and automated monitoring of …

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

When experts are immersed in a task, do their brains prioritize task-related activity? Most
efforts to understand neural activity during well-learned tasks focus on cognitive …