Addressing Inconsistency in Functional Neuroimaging: A Replicable Data-Driven Multi-Scale Functional Atlas for...

Area of Science:

• Cognitive Neuroscience
• Neuroimaging
• Systems Neuroscience

Background:

• Neuroimaging studies often lack standardized nomenclature for large-scale brain networks.
• Inconsistent terminology hinders the integration and comparability of findings across studies.
• A unifying framework is needed to harmonize brain network research.

Purpose of the Study:

• To present a whole-brain atlas of canonical functional brain networks.
• To standardize terminology and reference space for neuroimaging analyses.
• To enhance the utility and accessibility of functional brain network data.

Main Methods:

• Utilized a large dataset of over 100,000 resting-state functional magnetic resonance imaging (fMRI) datasets.
• Employed data-driven approaches to identify and characterize functional brain networks.
• Organized, labeled, and described networks using terms from cognitive and affective neuroscience.

Main Results:

• Developed a highly replicable whole-brain atlas of canonical functional brain networks.
• Networks captured information across multiple spatial scales.
• The atlas provides standardized labels and descriptions for functional brain entities.

Conclusions:

• The developed atlas offers a unifying framework for functional brain network research.
• It facilitates harmonization and standardization across diverse neuroimaging studies and modalities.
• This resource will enhance future data-driven and template-based neuroimaging analyses.