Toward discovery science of human brain function.

Area of Science:

• Neuroimaging
• Systems Neuroscience
• Computational Neuroscience

Background:

• Functional neuroimaging lacks common paradigms for hypothesis-free brain system exploration.
• Resting-state functional MRI (R-fMRI) offers a potential solution by analyzing spontaneous brain activity.
• R-fMRI reveals temporally correlated signal fluctuations, defining functional connectivity and the "functional connectome."

Purpose of the Study:

• To establish a common paradigm for brain system interrogation using R-fMRI.
• To map the functional connectome and identify inter-individual differences.
• To initiate discovery science in brain function through large-scale data aggregation.

Main Methods:

• Collected R-fMRI data from 1,414 volunteers across 35 international centers.
• Analyzed spontaneous low-frequency (<0.1 Hz) signal fluctuations during rest.
• Mapped functional connectivity patterns and identified loci of inter-individual variability.

Main Results:

• Demonstrated a universal architecture of positive and negative functional connections.
• Identified consistent regions of inter-individual variability in the functional connectome.
• Found age and sex to be significant determinants of functional connectivity patterns.

Conclusions:

• Independent R-fMRI datasets can be aggregated, demonstrating the feasibility of multicenter collaboration.
• The functional connectome exhibits both common architecture and unique individual features.
• High-throughput R-fMRI provides quantitative phenotypes for genetic studies and biomarkers for brain development and pathology.