Speaker
Description
Reference brain cortical surfaces derived from various structural pipelines enable integration of multimodal data into a standard space. In the absence of a common framework across structural pipelines, high profile surface atlases created within FreeSurfer (fsaverage) or Human Connectome Project (fs_LR) are not available in standard reference frames like the MNI152 or the 3D-reconstructed histological BigBrain model (Amunts et al. 2013). Here, we present our improved surface registration pipeline linking the BigBrain surface with other reference surfaces of interest (Lewis et al. 2020).
We implement a reparameterized multiscale pipeline via the Human Connectome Project's (HCP) Multimodal Surface Matching (MSM) tool (Robinson et al. 2014, 2018) and HCP workbench (Marcus et al. 2011). The BigBrain surface (Wagstyl et al. 2020) is first re-tessellated using mris_remesh (FreeSurfer7.1), which eliminates the suboptimal unfolding of the right occipital pole observed with our previous version. Registration is then carried out in a direct manner from the re-tessellated BigBrain surface to the reference surface. Performance of the updated pipeline shows improved accuracy and comparably low distortion as our previous approach.
This work allows the high-resolution, histological BigBrain model to serve as an unprecedented cross-validation tool for surface registration pipelines. Any surface atlas defined in another standard space, e.g. fs_LR or fsaverage, can now be transposed to BigBrain space such that macroscopic parcellation boundaries derived from in vivo imaging can be directly compared to cytoarchitectural properties. Likewise, BigBrain's histological landmarks or cortical layers can be transposed to fs_LR and fsaverage for a wide range of functional applications.
