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Abstract #1593

A Highly Replicable Multi-Scale Whole-Brain Atlas of Canonical Functional Networks from Over 100,000 Resting-State fMRI Datasets

Kyle Mark Jensen1,2, Vince Calhoun3, and Armin Iraji1,2
1Georgia State University, Atlanta, GA, United States, 2Tri-Institutional Center for Translational Research in Neuroimaging and Data Science, Atlanta, GA, United States, 3The Tri-Institutional Georgia State University/Georgia Institute of Technology/Emory University Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University (GSU), Atlanta, GA, United States

Synopsis

Keywords: fMRI Analysis, fMRI (resting state)

Motivation: There is a need for both standardized terminology as well as a universal reference space in the field of neuroscience.

Goal(s): NeuroMark represents a data-driven approach towards establishing a common reference space in
neuroimaging research. Here we present a functional brain atlas which translates the NeuroMark template into the field of neuroscience.

Approach: We manually labeled each of the 105 networks based on visual inspection of their spatial maps, computed similarity with multiple other atlases, and ordered and grouped them into 7 domains and 14 subdomains based on functional and spatial similarity.

Results: The resulting modules reveal many insights into the brain.

Impact: There are many atlases in the field, however, this one is highly replicable across individuals, datasets, and studies, and the multi-scale approach offers great promise towards helping to standardize both terminology and methodology in the field of neuroscience.

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Keywords