Alzheimer's disease (AD) affects not only memory and cognition but also the body's automatic functions, such as heart rate and blood pressure. These changes reflect the early disruption of the central autonomic network, the system that links the brain and the heart to maintain physiological balance. Electroencephalography (EEG) measures the brain's electrical activity and reveals patterns of cortical slowing and desynchronization, while heart-rate variability (HRV) reflects how flexibly the heart responds to internal and external demands. This narrative review brings together evidence published between 2000 and 2025 on the combined use of EEG and HRV as a single, integrated biomarker for AD. Studies consistently show that EEG-HRV coupling, which reflects how well the brain and heart communicate, provides better accuracy in distinguishing mild cognitive impairment and early AD than either measure alone. The findings reveal a shared loss of co-ordination between neural and autonomic systems, which is a hallmark of neurovisceral decline. The review also identifies key methodological gaps, including inconsistent recording conditions and lack of standardized analytic methods, which currently limit reproducibility. To bridge this gap, a translational roadmap is proposed to outline short-, mid-, and long-term goals for clinical validation, wearable integration, and digital health applications. Together, EEG-HRV coupling represents a scalable, non-invasive, and physiologically grounded tool that could support earlier and personalized monitoring of AD, helping to connect laboratory discovery with real-world clinical care.
Botchway et al. (Fri,) studied this question.