Topic: sub-brain maps

Disentangling independent latent components from neural data is a desirable goal in neuroscience. Independent component analysis (ICA) has been used to identify disentangled latent neural trajectories and their corresponding sub-brain maps from recorded imaging sequences. However, enforcing full independence between all latent components may be overly restrictive, as each independent neural trajectory and sub-brain map results in a rank-1 imaging sequence. Additionally, the connectivity inferred from a rank-1 sub-brain map produces a rank-1 connectivity matrix, which may lack expressiveness. T