Frequency-specific segregation and integration of human cerebral cortex: an intrinsic functional atlas

TL;DR

This study reveals stable frequency-specific subdivisions and network topologies in the human cerebral cortex, creating an intrinsic functional atlas that enhances understanding of brain network complexity.

Contribution

It introduces a novel frequency-specific parcellation method and constructs an intrinsic functional atlas based on spectral connectivity and eigen-clustering.

Findings

Identified 7-10 stable functional networks across frequencies.

Proposed an intrinsic atlas with 456 parcels.

Demonstrated stability of topologies across different datasets.

Abstract

The frequency-specific coupling mechanism of the functional human brain networks underpins its complex cognitive and behavioral functions. Nevertheless, it is not well unveiled what are the frequency-specific subdivisions and network topologies of the human brain. In this study, we estimated functional connectivity of the human cerebral cortex using spectral connection, and conducted frequency-specific parcellation using eigen-clustering and gradient-based methods, and then explored their topological structures. 7T fMRI data of 184 subjects in the HCP dataset were used for parcellation and exploring the topological properties of the functional networks, and 3T fMRI data of another 890 subjects were used to confirm the stability of the frequency-specific topologies. Seven to ten functional networks were stably integrated by two to four dissociable hub categories at specific frequencies, and we proposed an intrinsic functional atlas containing 456 parcels according to the parcellations across frequencies. The results revealed that the functional networks contained stable frequency-specific topologies, which may imply more abundant roles of the functional units and more complex interactions among them.