In an interview with Neurology Live, Advanced Brain Monitoring CEO Chris Berka shares insights from a pilot study that found how electroencephalography (EEG) can be used to differentiate between FTD, Alzheimer’s disease, and Lewy body dementia (LBD).

Berka was one of many presenters at the 2024 Alzheimer’s Association International Conference whose work featured FTD. In her conversation with Neurology Live, Berka highlighted how her research into EEG could address some of the challenges of diagnosing FTD.

“What’s interesting about FTD is that it is difficult to distinguish, especially in the early stages, from [Alzheimer’s] and LBD,” Berka said. “Our goal with quantitative EEG is to provide clinicians and researchers with a method to differentiate these dementia subtypes as early as possible.”

In the pilot study, Berka and her colleagues identified unique EEG biosignatures tied to FTD, Alzheimer’s, and LBD. The researchers studied the distribution of EEG signals across the scalp, monitoring the changes that occur in alpha brain waves when someone closes their eyes and goes from an eyes-open resting state to an eyes-closed one. When in the eyes-closed resting state, alpha brain waves, crucial for maintaining a balance between relaxation and alertness, become most dominant in the posterior region of the brain, where the visual cortex is.

This alpha brain wave activity is known as event-related potential activity. In Berka’s study, event-related potential activity refers to the brain’s electrical activity relating to going from the eyes-open resting state to the eyes-closed resting state.

Berka says they have found there are distinct rhythms in the posterior region of the brain in each of the three dementias. “While overall alpha activity is suppressed in [Alzheimer’s], the posterior dominance of the alpha rhythm remains intact, even in the later stages of the disease.” Like Alzheimer’s, in FTD, “we still see the posterior dominant rhythm, but the peak of the rhythm becomes slower and slower. This slowing of the posterior dominant rhythm indicates cognitive decline or progression.” LBD stands in sharp contrast to both Alzheimer’s and FTD because, “the posterior dominance of the alpha rhythm is completely obliterated.”

While the pilot study provided valuable data, more research is needed to understand better how EEG biomarkers can be utilized and how early they can be detected in disorder progression. Berka notes that while resting-state EEG readings are helpful, readings taken during memory and attention tasks are more sensitive to the presence of and differences between neurodegenerative diseases.

According to Berka, the behavioral variant of FTD primarily affects the frontal region first, but they have seen “seen indications of this in our event-related potential activity, which helps differentiate the behavioral variant from primary progressive aphasia (PPA), which affects speech production and understanding. In the PPA variant, we see relatively normal resting-state data, but differences emerge in the event-related potentials, particularly those over the temporal-parietal region.”

Berka says that while EEG is not a complete diagnostic solution, it is a helpful tool for clinical neurologists to differentiate between FTD and other conditions easily and without much cost. Berka notes that EEG can provide additional diagnostic information earlier in progression as a component of a clinician’s toolkit. With interventions for FTD being most effective in early progression, timely diagnosis is crucial.

“What we’re hoping is that these electrophysiological profiles will provide a more definitive set of biomarkers,” Berka noted. “We aim to offer clinicians biomarkers associated with mild cognitive impairment, [Alzheimer’s], and LBD, and now we’re adding FTD to that list. We’ve already had discussions with one of our clinicians who observed that a patient’s profile closely resembled our behavioral variant FTD cohort. It’s in the early stage, but with more data, we can enhance pattern matching with AI.”

Researchers are exploring diverse and accessible tools for diagnosing and differentiating between FTD and other dementias. In a previously published study, researchers evaluated the use of machine learning and clinically gathered data to classify and discriminate FTD and Alzheimer’s disease in underrepresented groups.

Are you or a loved one navigating the challenging process of getting an FTD diagnosis? The recently updated Find Support page on AFTD’s website features an interactive map to help you find an FTD expert in your state or nearby. If you have questions or concerns, AFTD’s HelpLine is here to support you: contact the HelpLine at 1-866-507-7222 or info@theaftd.org.