Integrating anatomical and functional landmarks for interparticipant alignment of imaging data

Abstract

Abstract Aligning brain maps using functional features rather than anatomical landmarks potentially improves individual identifiability and increases power in group neuroimaging studies. However, alignment based purely on functional magnetic resonance imaging (fMRI) risks omitting useful anatomical constraints. An optimized combination of anatomical and functional feature alignment could balance the advantages of each approach. We used 3T fMRI data from 80 Human Connectome Project participants during seven tasks. The effectiveness of functional and anatomical alignment methods was evaluated using interparticipant decoding accuracy. Functional alignment mapped vertices from participants to a template, aligning their fMRI responses to shared responses during movie viewing. The template was derived from the combined fMRI responses of a set of participants. We benchmarked the results against existing functional alignment methods, including the Procrustes method and ridge regression. A common practice in the field is to use the same participants for the alignment cohort and for template generation. We found that this inflates decoding accuracies by mixing anatomical and functional alignment. Based on this, we recommend that a template’s generalizability should be evaluated against held-out participants. Building on these findings, we investigated whether inter-subject alignment could be improved by integrating anatomical and functional information. We studied a modified alignment method where a single parameter interpolates between pure functional alignment and anatomical alignment. Optimizing the parameter with nested cross-validation, we found that integrating anatomical and functional information robustly reduced noise and improved alignment across a variety of alignment methods. Combining anatomical and functional information accounts for individual heterogeneity in functional topographies while incorporating anatomical constraints. The integrated alignment described here improves inter-subject decoding using functional brain maps. These findings also demonstrate that brain anatomy provides a lens into the inherent variability of individual neural landscapes.