“Principles of intensive human neuroimaging”.

Soazig Guyomarc’h, Tomas Knapen, Elisha P. Merriam, Kendrick Kay

Abstract The rise of large, publicly shared functional magnetic resonance imaging (fMRI) data sets in human neuroscience has focused on acquiring either a few hours of data on many individuals (wide fMRI) or many hours of data on a few individuals (deep fMRI). In this opinion article, we highlight an emerging approach within deep fMRI, which we refer to as intensive fMRI: one that strives for extensive sampling of cognitive phenomena to support computational modeling and detailed investigation of brain function at the single-voxel level. We discuss the fundamental principles, trade-offs, and practical considerations of intensive fMRI. We also emphasize that intensive fMRI does not simply mean collecting more data: it requires careful design of experiments to enable a rich hypothesis space, optimizing data quality, and strategically curating public resources to maximize community impact.