A population-averaged structural connectomic brain atlas dataset from 422 HCP-aging subjects

Yiming Xiao; Greydon Gilmore; Jason Kai; Jonathan C Lau; Terry Peters; Ali R Khan

doi:10.1016/j.dib.2023.109513

A population-averaged structural connectomic brain atlas dataset from 422 HCP-aging subjects

Data Brief. 2023 Aug 22:50:109513. doi: 10.1016/j.dib.2023.109513. eCollection 2023 Oct.

Authors

Yiming Xiao¹, Greydon Gilmore^{2

3}, Jason Kai⁴, Jonathan C Lau^{2

3}, Terry Peters^{4

5

6}, Ali R Khan^{2

4

5

6}

Affiliations

¹ Department of Computer Science and Software Engineering, Gina Cody School of Engineering and Computer Science, Concordia University, Montreal, QC, Canada.
² Centre for Functional and Metabolic Mapping, Robarts Research Institute, Western University, London, ON, Canada.
³ Department of Clinical Neurological Sciences, Division of Neurosurgery, Schulich School of Medicine & Dentistry, Western University, London, ON, Canada.
⁴ Department of Medical Biophysics, Schulich School of Medicine & Dentistry, Western University, London, ON, Canada.
⁵ School of Biomedical Engineering, Western University, London, ON, Canada.
⁶ The Brain and Mind Institute, Western University, London, ON, Canada.

Abstract

Population-averaged brain atlases, that are represented in a standard space with anatomical labels, are instrumental tools in neurosurgical planning and the study of neurodegenerative conditions. Traditional brain atlases are primarily derived from anatomical scans and contain limited information regarding the axonal organization of the white matter. With the advance of diffusion MRI that allows the modeling of fiber orientation distribution (FOD) in the brain tissue, there is an increasing interest for a population-averaged FOD template, especially based on a large healthy aging cohort, to offer structural connectivity information for connectomic surgery and analysis of neurodegeneration. The dataset described in this article contains a set of multi-contrast structural connectomic MRI atlases, including T1w, T2w, and FOD templates, along with the associated whole brain tractograms. The templates were made using multi-contrast group-wise registration based on 3T MRIs of 422 Human Connectome Project in Aging (HCP-A) subjects. To enhance the usability, probabilistic tissue maps and segmentation of 22 subcortical structures are provided. Finally, the subthalamic nucleus shown in the atlas is parcellated into sensorimotor, limbic, and associative sub-regions based on their structural connectivity to facilitate the analysis and planning of deep brain stimulation procedures. The dataset is available on the OSF Repository: https://osf.io/p7syt.

Keywords: Aging; Atlas; Diffusion MRI; Magnetic resonance imaging (MRI); Structural connectivity; Subthalamic nucleus.