Personalized modeling of neurodegeneration determines dementia severity from EEG recordings

Abstract

INTRODUCTIONEarly identification of dementia is necessary for a timely onset of therapeutic care. However, cortical structural alterations associated with early dementia are difficult to disclose. METHODS: We developed a cortical model of dementia-related neurodegeneration accounting for slowing of local dynamics and global connectivity degradation. We collected EEG recordings at rest from subjects in healthy (HC), Subjective Cognitive Decline (SCD), and Mild Cognitive Impairment (MCI) condition. For each patient, we estimated neurodegeneration model parameters based on individual EEG recordings. RESULTS: Our model outperformed standard EEG analysis not only in discriminating between HC and MCI conditions (F1 score 0.95 vs 0.85) but also in identifying SCD patients with biological hallmarks of Alzheimer’s disease in the cerebrospinal fluid (recall 0.87 vs 0.50). DISCUSSION: Personalized neurodegeneration models could both support classification of MCI and assess the risk of progression from SCD to Alzheimer based only on economical and non-invasive EEG recordingClinicalTrials.govIdentifierNCT05569083