Instantaneous Frequency: A New Functional Biomarker for Dynamic Brain Causal Networks

Area of Science:

• Neuroimaging
• Network Neuroscience
• Signal Processing

Background:

• Introduces instantaneous frequency (IF) analysis as a novel method for characterizing dynamic brain causal networks.
• Utilizes functional magnetic resonance imaging (fMRI) blood-oxygen-level-dependent (BOLD) signals.

Purpose of the Study:

• To present and validate IF analysis for dynamic brain network characterization.
• To explore the potential of IF as a biomarker for global network oscillatory behavior.

Main Methods:

• Effective connectivity is estimated using dynamic causal modeling (DCM).
• IF sequences are derived from DCM, with average IF serving as a key metric.
• Analysis includes data from Alzheimer's Disease Neuroimaging Initiative, Open Access Series of Imaging Studies, and Human Connectome Project.

Main Results:

• Demonstrates efficacy in distinguishing between clinical and demographic groups.
• Identifies significant group differences in IF metrics across cognitive decline stages (normal control, MCI, AD), sex, and sleep quality.
• Highlights IF's sensitivity in detecting variations in brain network dynamics.

Conclusions:

• IF analysis is a promising, sensitive indicator for early diagnosis and monitoring of neurodegenerative and cognitive conditions.
• Average IF shows potential as a biomarker for global network oscillatory behavior.
• The method effectively differentiates groups based on cognitive status, sex, and sleep quality.