Interplay between functional connectivity and scale-free dynamics in intrinsic fMRI networks

Area of Science:

• Neuroscience
• Brain Imaging
• Complex Systems

Background:

• Functional magnetic resonance imaging (fMRI) studies reveal spontaneous signal fluctuations organized in large-scale brain networks.
• fMRI signals exhibit 1/f power spectra, indicative of scale-free dynamics, a characteristic previously studied separately from functional connectivity.

Purpose of the Study:

• To investigate the interplay between functional connectivity and scale-free dynamics in human brain activity using fMRI.
• To explore how task performance modulates these dynamics and their contribution to inter-regional interactions.

Main Methods:

• Applied the fractal connectivity framework, a multivariate extension of fractional Gaussian noise models using wavelet analysis, to resting-state and task-based fMRI data from healthy adults.
• Analyzed scale-invariance in univariate and bivariate cross-temporal dynamics of fMRI signals.

Main Results:

• Scale-invariance was observed in bivariate cross-temporal dynamics, extending beyond univariate signal properties.
• Lower frequencies contributed more to inter-regional connectivity than higher frequencies, both at rest and during a visual detection task.
• Task performance altered cross-temporal dynamics, increasing the contribution of higher frequencies to global correlation, alongside decreased Hurst exponent and inter-regional correlations.
• Weaker task-related modulation of frequency contributions to connectivity correlated with better task performance (shorter, less variable reaction times).

Conclusions:

• Scale-free dynamics are present in cross-regional brain interactions, integrating findings from resting-state networks and scale-free dynamics research.
• The findings demonstrate that the brain's scale-free dynamics are not limited to individual brain regions but extend to their interactions.