Sparse Distributed Archetypes Reveal Compressible Network Motifs Underlying Naturalistic Cognition

Naturalistic cognition emerges from coordinated interactions among distributed brain systems operating across multiple representational scales. Characterizing this organization remains challenging because cognitively relevant information is embedded within high-dimensional neural activity. Here, we apply Multisubject Archetypal Analysis (MS-AA) to naturalistic fMRI data collected during intact narrative listening, word-scrambled audio, and rest to investigate how condition-relevant information is distributed across archetypal representations. We examine both spatial and temporal formulations of MS-AA as complementary views of naturalistic brain activity. Across analyses, decoding performance