6 papers
A cross-species neural foundation model for end-to-end speech decoding
Yizi Zhang, Linyang He, Chaofei Fan +9
Speech brain-computer interfaces (BCIs) aim to restore communication for people with paralysis by translating neural activity into text. Most systems use cascaded frameworks that d…
Animal behavioral analysis and neural encoding with transformer-based self-supervised pretraining
Yanchen Wang, Han Yu, Ari Blau +5
The brain can only be fully understood through the lens of the behavior it generates -- a guiding principle in modern neuroscience research that nevertheless presents significant t…
Inpainting the Neural Picture: Inferring Unrecorded Brain Area Dynamics from Multi-Animal Datasets
Ji Xia, Yizi Zhang, Shuqi Wang +4
Characterizing interactions between brain areas is a fundamental goal of systems neuroscience. While such analyses are possible when areas are recorded simultaneously, it is rare t…
An uncertainty-aware framework for data-efficient multi-view animal pose estimation
Lenny Aharon, Keemin Lee, Karan Sikka +4
Multi-view pose estimation is essential for quantifying animal behavior in scientific research, yet current methods struggle to achieve accurate tracking with limited labeled data…
Neural Encoding and Decoding at Scale
Yizi Zhang, Yanchen Wang, Mehdi Azabou +7
Recent work has demonstrated that large-scale, multi-animal models are powerful tools for characterizing the relationship between neural activity and behavior. Current large-scale…
A study of animal action segmentation algorithms across supervised, unsupervised, and semi-supervised learning paradigms
Ari Blau, Evan S Schaffer, Neeli Mishra +4
Action segmentation of behavioral videos is the process of labeling each frame as belonging to one or more discrete classes, and is a crucial component of many studies that investi…