Quantifying behavior to understand the brain
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 at a resolution not previously imaginable. This has opened up a new field of …
A primer on motion capture with deep learning: principles, pitfalls, and perspectives
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 …
a hard computational problem. Recent advances in deep learning have tremendously …
Geometric deep learning enables 3D kinematic profiling across species and environments
Comprehensive descriptions of animal behavior require precise three-dimensional (3D)
measurements of whole-body movements. Although two-dimensional approaches can track …
measurements of whole-body movements. Although two-dimensional approaches can track …
Humman: Multi-modal 4d human dataset for versatile sensing and modeling
Abstract 4D human sensing and modeling are fundamental tasks in vision and graphics with
numerous applications. With the advances of new sensors and algorithms, there is an …
numerous applications. With the advances of new sensors and algorithms, there is an …
Connectomic reconstruction of a female Drosophila ventral nerve cord
A deep understanding of how the brain controls behaviour requires mapping neural circuits
down to the muscles that they control. Here, we apply automated tools to segment neurons …
down to the muscles that they control. Here, we apply automated tools to segment neurons …
Animal kingdom: A large and diverse dataset for animal behavior understanding
Understanding animals' behaviors is significant for a wide range of applications. However,
existing animal behavior datasets have limitations in multiple aspects, including limited …
existing animal behavior datasets have limitations in multiple aspects, including limited …
Lightning Pose: improved animal pose estimation via semi-supervised learning, Bayesian ensembling and cloud-native open-source tools
Contemporary pose estimation methods enable precise measurements of behavior via
supervised deep learning with hand-labeled video frames. Although effective in many cases …
supervised deep learning with hand-labeled video frames. Although effective in many cases …
Toward the explainability, transparency, and universality of machine learning for behavioral classification in neuroscience
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 …
brain function (computational neuroethology) is a rapidly growing approach that is poised to …
[HTML][HTML] Machine learning and artificial intelligence in neuroscience: A primer for researchers
F Badrulhisham, E Pogatzki-Zahn, D Segelcke… - Brain, Behavior, and …, 2024 - Elsevier
Artificial intelligence (AI) is often used to describe the automation of complex tasks that we
would attribute intelligence to. Machine learning (ML) is commonly understood as a set of …
would attribute intelligence to. Machine learning (ML) is commonly understood as a set of …
Three-dimensional surface motion capture of multiple freely moving pigs using MAMMAL
Understandings of the three-dimensional social behaviors of freely moving large-size
mammals are valuable for both agriculture and life science, yet challenging due to …
mammals are valuable for both agriculture and life science, yet challenging due to …