Evaluation of surface-based hippocampal registration using ground-truth subfield definitions

Abstract

The hippocampus is an archicortical structure, consisting of subfields with unique circuits. Understanding its microstructure, as proxied by these subfields, can improve our mechanistic understanding of learning and memory and has clinical potential for several neurological disorders. One prominent issue is how to parcellate, register, or retrieve homologous points between two hippocampi with grossly different morphologies. Here, we present a surface-based registration method that solves this issue in a contrast-agnostic, topology-preserving manner. Specifically, the entire hippocampus is first analytically unfolded, and then samples are registered in 2D unfolded space based on thickness, curvature, and gyrification. We demonstrate this method in seven 3D histology samples and show superior alignment with respect to subfields using this method over more conventional registration approaches. HighlightsO_LIHippocampal subfields contain microcircuits that are critical for memory and vulnerable to neurological disease. C_LIO_LIHippocampi have variable folding patterns between individuals, making them hard to register or parcellate. C_LIO_LIWe present a surface-based hippocampal registration method that is analogous to neocortical inflation to a sphere and registration. C_LIO_LITesting in seven detailed 3D histology samples revealed successful registration with respect to hippocampal subfields, and outperformed more conventional methods. C_LIO_LIThis method provides groundwork for detailed multimodal hippocampal mapping across subjects and datasets in the future. C_LI Data availabilityThe methodological advancements described here are made easily accessible in the latest version of open source software HippUnfold1. Code used in the development and testing of these methods, as well as preprocessed images, manual segmentations, and results, are openly available2.