Alzheimer’s disease (AD) and frontotemporal dementia (FTD) are two common forms of dementia, yet distinguishing between them is challenging due to overlapping symptoms. Quantitative electroencephalography (EEG) has emerged as a promising tool in dementia research, offering potential for identifying biosignatures that can differentiate between AD and FTD. In a recent pilot study, researchers identified distinct EEG biosignatures associated with each condition, although further research is needed to confirm these findings and validate their use in distinguishing dementia subtypes.

The study utilized quantitative analysis to reveal that patients with both AD and FTD experienced a slowing of the posterior dominant rhythm (PDR) frequency. However, a key difference was noted: PDR power was significantly reduced in AD patients, while it remained relatively preserved in those with FTD. Additionally, the study indicated that different subtypes of FTD might exhibit unique EEG abnormalities. For example, behavioral-variant FTD showed more pronounced PDR slowing, while primary progressive aphasia FTD was marked by more delayed event-related potential components.

These findings were presented by senior author Chris Berka at the 2024 Alzheimer’s Association International Conference (AAIC), held from July 28 to August 1 in Philadelphia, Pennsylvania. In an interview with NeurologyLive during the conference, Berka, the CEO and cofounder of Advanced Brain Monitoring, discussed how EEG biomarkers could be utilized to differentiate between AD, Lewy body dementia (LBD), and FTD. She also highlighted the challenges of diagnosing FTD, particularly in its early stages, where it is often misclassified. Furthermore, she spoke about the potential for AI and pattern matching to improve the identification of neurodegenerative diseases through EEG data.