Dimensionality reduction beyond neural subspaces with slice tensor component analysis
Background Introduction: Large-scale neural recording data can typically be described by patterns of co-activated neurons. However, the view of constraining neural activity variability to a fixed low-dimensional subspace may overlook higher-dimensional structures, such as fixed neural sequences or slowly evolving latent spaces. This study argues th...