Machine Learning Methods for Studying Latent Neural Activity Dynamics 事件

Machine Learning Methods for Studying Latent Neural Activity Dynamics arXiv:2606.10530v1 Announce Type: cross Abstract: Recent developments in brain recording are driving a demand for machine learning tools capable of decoding the latent structure of large populations of neurons. In this paper, we provide a comprehensive survey that outlines the trajectory of Latent Variable Models (LVMs) from early state-space models to more recent deep generative models. We organize the literature into three