Instantaneous Frequency: A New Functional Biomarker for Dynamic Brain Causal Networks
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This study introduces instantaneous frequency (IF) analysis as a novel method for characterizing dynamic brain causal networks from fMRI blood-oxygen-level-dependent (BOLD) signals. Effective connectivity, estimated using dynamic causal modeling (DCM), is analyzed to derive IF sequences, with the average IF across brain regions serving as a potential biomarker for global network oscillatory behavior. Analysis of data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI), Open Access Series of Imaging Studies (OASIS), and Human Connectome Project (HCP) demonstrates the method’s efficacy in distinguishing between clinical and demographic groups, such as cognitive decline stages, sex differences, and sleep quality levels. Statistical analyses reveal significant group differences in IF metrics, highlighting its potential as a sensitive indicator for early diagnosis and monitoring of neurodegenerative and cognitive conditions.
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Highlights
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The study introduces instantaneous frequency (IF) as a novel biomarker derived from dynamic brain effective connectivity, capturing temporal fluctuations in brain networks.
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The proposed IF biomarker effectively differentiates between various clinical stages, such as Mild Cognitive Impairment (MCI) and Alzheimer’s Disease (AD), and demographic factors, including sex and sleep quality.
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The robustness and clinical relevance of the IF biomarker are validated using three independent datasets: ADNI, OASIS, and HCP, demonstrating its potential in cognitive and neurological research.
