Predicting individual face-selective topography using naturalistic stimuli

Subject-specific, functionally defined areas are conventionally estimated with functional localizers and a simplecontrast analysis between responses to different stimulus categories. Compared with functional localizers, natu-ralistic stimuli provide several advantages such as stronger and widespread brain activation, greater engagement,and increased subject compliance. In this study we demonstrate that a subject’s idiosyncratic functional topog-raphy can be estimated with highfidelity from that subject’s fMRI data obtained while watching a naturalisticmovie using hyperalignment to project other subjects’localizer data into that subject’s idiosyncratic corticalanatomy. Thesefindings lay the foundation for developing an efficient tool for mapping functional topographiesfor a wide range of perceptual and cognitive functions in new subjects based only on fMRI data collected whilewatching an engaging, naturalistic stimulus and other subjects’localizer data from a normative sample