Mapping Dynamic Metabolic Energy Distribution in Brain Networks using fMRI: A Novel Dynamic Time Warping Framework

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Abstract

Understanding how metabolic energy is distributed across brain networks is essential for elucidating healthy brain function and neurological disorders. Research has established the link between blood flow changes and glucose metabolic processes that fuel neural activity. Here, we introduce a novel framework based on the normalized dynamic time warping algorithm robust to neural temporal variability, enabling reliable insights into metabolic energy demands using functional magnetic resonance imaging data. Our findings indicate that healthy brains maintain balanced energy distribution, whereas imbalances are more pronounced in schizophrenia with links to both positive and negative symptoms, particularly during rapid neural processes. Additionally, we identified a dynamic state that supports the brain criticality theory and is associated with higher-order cognitive abilities, demonstrating our framework’s functional and clinical relevance. By linking metabolic energy distribution to neural dynamics, this framework provides a novel way to estimate and quantify the brain’s maintenance of functional balance in a broadly applicable manner for studying brain health and disorders.

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