Connectivity gradients in spontaneous brain activity at multiple frequency bands

Area of Science:

• Neuroscience
• Brain Imaging
• Systems Neuroscience

Background:

• Spontaneous brain oscillations reflect the brain's intrinsic organizational structure.
• Previous research mapped functional integration and segregation hierarchies using low-frequency functional connectivity.
• Understanding of brain oscillation hierarchies is limited due to focus on single, narrow frequency bands.

Purpose of the Study:

• To investigate the brain's functional organization hierarchy across multiple frequency bands.
• To explore variations in information integration rates across different large-scale brain networks.

Main Methods:

• Applied gradient analysis to fast resting-state functional magnetic resonance imaging (fMRI) signals.
• Utilized data from the Human Connectome Project and an independent dataset.
• Extended analysis to multiple frequency bands beyond the traditional ~0.01-0.1 Hz range.

Main Results:

• Identified a frequency-rank cortical map of the highest gradient.
• Found that the fundamental structure of functional organization is consistent across multiple frequency bands.
• Observed frequency-dependent variations in the highest integration levels across large-scale brain networks.

Conclusions:

• The brain's functional hierarchy exhibits consistent organizational principles across different frequency bands.
• Different brain networks integrate information at distinct rates, varying with frequency.
• Analyzing spontaneous brain activity across multiple frequency bands is crucial for understanding intrinsic brain architecture.