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Front Hum Neurosci. 2017 Jun 19;11:306. doi: 10.3389/fnhum.2017.00306. eCollection 2017.

Probabilistic White Matter Atlases of Human Auditory, Basal Ganglia, Language, Precuneus, Sensorimotor, Visual and Visuospatial Networks.

Figley TD1,2,3, Mortazavi Moghadam B1,2,3, Bhullar N1,2,3, Kornelsen J1,2,3,4,5, Courtney SM6,7,8, Figley CR1,2,3,4,6,9.

Author information

1
Department of Radiology, University of ManitobaWinnipeg, MB, Canada.
2
Division of Diagnostic Imaging, Health Sciences CentreWinnipeg, MB, Canada.
3
Neuroscience Research Program, Kleysen Institute for Advanced MedicineWinnipeg, MB, Canada.
4
Department of Physiology and Pathophysiology, University of ManitobaWinnipeg, MB, Canada.
5
St. Boniface Hospital Research, Catholic Health Corporation of ManitobaWinnipeg, MB, Canada.
6
Department of Psychological and Brain Sciences, Johns Hopkins UniversityBaltimore, MD, United States.
7
Solomon H. Snyder Department of Neuroscience, Johns Hopkins UniversityBaltimore, MD, United States.
8
F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger InstituteBaltimore, MD, United States.
9
Biomedical Engineering Graduate Program, University of ManitobaWinnipeg, MB, Canada.

Abstract

Background: Despite the popularity of functional connectivity analyses and the well-known topology of several intrinsic cortical networks, relatively little is known about the white matter regions (i.e., structural connectivity) underlying these networks. In the current study, we have therefore performed fMRI-guided diffusion tensor imaging (DTI) tractography to create probabilistic white matter atlases for eight previously identified functional brain networks, including the Auditory, Basal Ganglia, Language, Precuneus, Sensorimotor, Primary Visual, Higher Visual and Visuospatial Networks. Methods: Whole-brain diffusion imaging data were acquired from a cohort of 32 healthy volunteers, and were warped to the ICBM template using a two-stage, high-dimensional, non-linear spatial normalization procedure. Deterministic tractography, with fractional anisotropy (FA) ≥0.15 and deviation angle <50°, was then performed using the Fiber Association by Continuous Tracking (FACT) algorithm, and a multi-ROI approach to identify tracts of interest. Regions-of-interest (ROIs) for each of the eight networks were taken from a pre-existing atlas of functionally defined regions to explore all ROI-to-ROI connections within each network, and all resulting streamlines were saved as binary masks to create probabilistic atlases (across participants) for tracts between each ROI-to-ROI pair. Results: The resulting functionally-defined white matter atlases (i.e., for each tract and each network as a whole) were saved as NIFTI images in stereotaxic ICBM coordinates, and have been added to the UManitoba-JHU Functionally-Defined Human White Matter Atlas (http://www.nitrc.org/projects/uofm_jhu_atlas/). Conclusion: To the best of our knowledge, this work represents the first attempt to comprehensively identify and map white matter connectomes for the Auditory, Basal Ganglia, Language, Precuneus, Sensorimotor, Primary Visual, Higher Visual and Visuospatial Networks. Therefore, the resulting probabilistic atlases represent a unique tool for future neuroimaging studies wishing to ascribe voxel-wise or ROI-based changes (i.e., in DTI or other quantitative white matter imaging signals) to these functional brain networks.

KEYWORDS:

MRI; atlas; brain; connectivity; connectome; diffusion; white matter

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