Standardizing human brain parcellations

Abstract

Using brain atlases to localize regions of interest is a requirement for making neuroscientifically valid statistical inferences. These atlases, represented in volumetric or surface coordinate spaces, can describe brain topology from a variety of perspectives. Although many human brain atlases have circulated the field over the past fifty years, limited effort has been devoted to their standardization. Standardization can facilitate consistency and transparency with respect to orientation, resolution, labeling scheme, file storage format, and coordinate space designation. Our group has worked to consolidate an extensive selection of popular human brain atlases into a single, curated, open-source library, where they are stored following a standardized protocol with accompanying metadata, which can serve as the basis for future atlases. The repository containing the atlases, the specification, as well as relevant transformation functions is available in the neuroparc OSF registered repository or https://github.com/neurodata/neuroparc.

A low-resource reliable pipeline to democratize multi-modal connectome estimation and analysis

“…Connectomes were estimated by both m2g-d and m2g-f for all 35 parcellations from the Neuroparc repository [10] As mentioned before, the oracle accuracy of connectomes compared to true functional and structural properties of individuals' brains is impossible to measure. Instead, we measure the discriminability of each dataset (Figure 3), which is a measure of preservation of individual-specific information and data repeatability.…”

“…Both the m2g-d and m2g-f pipelines can be run independently or on the same dataset, provided the required data files are available. Which parcellation(s) to be used in the connectome creation can be specified by the user, whether they be unique files stored locally or from the neuroparc repository [10]. If no parcellations are present, then m2g will pull from the neuroparc repository and run all available parcellations.…”

Inside information: Systematic within-node functional connectivity changes observed across tasks or groups

“…Recent functional connectivity work has shown that quantitative results in graph theory measures when comparing groups of subjects or comparing the same subjects across different task-conditions, change significantly if node reconfiguration is taken into account through flexible individualized- or group- brain-state-dependent parcellations ( Luo et al, 2021 ). Despite this knowledge, fixed atlases are still applied in most studies of the connectome, and the search continues for the ideal atlas ( Bozek et al, 2018 ; Lawrence et al, 2021 ; Schaefer et al, 2018 ).…”

Inside Information: Systematic within-node connectivity changes observed across tasks or groups

“…Recent functional connectivity work has shown that quantitative results in graph theory measures when comparing groups of subjects or comparing the same subjects across different task-conditions, change significantly if node reconfiguration is taken into account through flexible individualized- or group-brain-state-dependent parcellations 40 . Yet fixed atlases are applied in most studies of the connectome, and the search continues for the ideal atlas 41, 42, 43 .…”