Neuroscience has long been an essential driver of progress in artificial intelligence (AI). We
propose that to accelerate progress in AI, we must invest in fundamental research in …

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 …

Animals have exquisite control of their bodies, allowing them to perform a diverse range of
behaviours. How such control is implemented by the brain, however, remains unclear …

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

Animals move in three dimensions (3D). Thus, 3D measurement is necessary to report the
true kinematics of animal movement. Existing 3D measurement techniques draw on …

Recent studies in mice have shown that orofacial behaviors drive a large fraction of neural
activity across the brain. To understand the nature and function of these signals, we need …

Quantifying movement is critical for understanding animal behavior. Advances in computer
vision now enable markerless tracking from 2D video, but most animals move in 3D. Here …

Neuroscience has long been an essential driver of progress in artificial intelligence (AI). We
propose that to accelerate progress in AI, we must invest in fundamental research in …

Our natural behavioral repertoires include coordinated actions of characteristic types. To
better understand how neural activity relates to the expression of actions and action …

The cortical population code is pervaded by activity patterns evoked by movement, but it
remains largely unknown how such signals relate to natural behavior or how they might …