Kristopher Jensen

Manifold GPLVMs for discovering non-Euclidean latent structure in neural data

A common problem in neuroscience is to elucidate the collective neural representations of behaviorally important variables such as head direction, spatial location, upcoming movements, or mental spatial transformations. Often, these latent variables are internal constructs not directly accessible to…