Modelling brain metabolism with interacting nonautonomous phase oscillators

Traditional brain models have focused primarily on electrical signalling, offering valuable insights but often overlooking the crucial role of metabolism within the neurovascular unit. Existing metabolic models tend to be highly detailed and mass-based, relying on strict conservation laws that limit their applicability to the brain's thermodynamically open environment. In this study, we present a novel, phenomenological model of neuronal energy metabolism using a network of coupled Kuramoto oscillators. This nonautonomous phase dynamics framework captures complex, time-dependent interactions and allows for multiple synchronization states among metabolic processes. Our model captures key features consistent with healthy neurovascular dynamics, despite not being directly fitted to empirical data from resting-state brains and reveals how disruptions in metabolic synchrony may contribute to dementia-related pathology. By emphasizing the importance of metabolic coordination in the neurovascular unit, this work provides a versatile methodological foundation for future brain modelling efforts.