Collen-Francqui Start-up Grant (Rose Bruffaerts).

Early and reliable diagnosis of neurodegenerative diseases such as Alzheimer's Disease (AD) and Frontotemporal Degeneration (FTD) is paramount from a clinical point of view, to provide accurate information about the cause of a patient's symptoms and their prognosis. Fluid- and PET-based biomarkers are reliable tools for early diagnosis of AD, but they entail invasive, costly procedures and are not easily accessible to all clinicians. Here, we advocate the development of a new and reliable neurophysiological marker as a suitable triage tool to identify patients with cognitive complaints who are at high risk for AD or FTD. Functional changes, which can be measured using high-density Electroencephalography (hd-EEG), precede structural changes of the brain. In this proposal, we examine hd-EEG in a cohort of patients with neurodegenerative disease (biomarker-proven AD, and non-AD pathologies such as FTD) as well as controls. We previously demonstrated in older adults using multivariate analysis that larger task-related neurophysiological signal changes measured using magnetoencephalography are linked to better cognitive performance. In this project, we validate our approach using hd-EEG and we will develop a multivariate marker reflecting the dynamic neural pattern across the whole brain at the individual level. Using this "neural fingerprint" we test whether we can identify patients with neurodegenerative disease using single-case statistics to validate our multivariate neurophysiological marker for use in clinical practice. The scientific innovation of this project firstly lies in the translation of recent discoveries in cognitive neuroscience to clinical practice for use at the level of a single individual, combined with methodological advances regarding the acquisition and analysis of hd-EEG. Our goal is ultimately to optimize the clinical diagnostic pathway for neurodegeneration, by identifying some individuals as low-risk and providing reassurance to these patients, while prioritizing patients with a high risk of neurodegeneration for more invasive diagnostic procedures. In the future, neurophysiological markers could help to efficiently identify individuals who may benefit from disease-modifying therapy in a clinical trial.

Keywords:NEUROINFORMATICS

Disciplines:Cognitive neuroscience, Neurophysiology