Schedule of Events | Symposia

flatsurfer: A flexible, open-source package for generating limbic-centered flat maps of the cerebral cortex

Poster Session D - Monday, March 31, 2025, 8:00 – 10:00 am EDT, Back Bay Ballroom/Republic Ballroom

Joshua Paul Rodriguez¹ (rodriguezjoshuapaul@gmail.com), Chan H. Hong¹, Lisa Feldman Barrett^1,2, Karen S. Quigley¹, Bradford C. Dickerson^2,3, David C. Van Essen⁴, Jordan E. Theriault^1,2*, Yuta Katsumi^2,3*; ¹Northeastern University, Boston, MA, USA, ²Massachusetts General Hospital, Boston, MA, USA, ³Harvard Medical School, Boston, MA, USA, ⁴Washinton University in St. Louis, St. Louis, MO, USA

Surface-based visualization of neuroimaging data in relation to major anatomical or functional features of the cerebral cortex makes quality control easier and enhances the spatial interpretation of analysis results. Flattened representations of cortical surfaces (“flat maps”) can reveal some spatial associations that would not be obvious in three-dimensional space. Flat maps also distort some spatial relationships to preserve others, however, and the existing flat maps implemented in several software packages make relaxation cuts through the medial surface to preserve the lateral convexity. This distorts the cortical limbic areas near these cuts, and projects neighboring limbic vertices to different, sometimes opposite, peripheries of the flat map, making it difficult to visualize meaningful patterns on medial cortical surfaces. Here, we introduce limbic-centered flat maps of the cerebral cortex, a novel approach to cortical surface visualization that centers on limbic cortices and uses an azimuthal equal-area projection to optimize spatial representation of different cortical structures. We have developed flatsurfer, an open-source python package designed to make it easy for users to generate limbic-centered fla maps from any input neuroimaging data in common formats (e.g., .nii.gz, .mgz) with minimal coding experience. flatsurfer is also highly configurable, as it allows users to flexibly customize features of flat maps (e.g., underlay/overlay colors, parcellation borders/labels) and enables tailored visualizations in diverse experimental contexts. This package provides a powerful tool for exploring and interpreting neuroimaging data for investigators at all levels of expertise.

Topic Area: METHODS: Neuroimaging