Neuronal synchrony abnormalities associated with subclinical epileptiform activity in early onset Alzheimer's disease

Abstract

Abstract Since the first demonstrations of network hyperexcitability in scientific models of Alzheimer’s disease (AD) a growing body of clinical studies have identified subclinical epileptiform activity and associated cognitive decline in patients with AD. An obvious problem presented in these studies is lack of sensitive measures to detect and quantify network hyperexcitability in human subjects. In this study we examined whether altered neuronal synchrony can be a surrogate marker to quantify network hyperexcitability in patients with AD. Using magnetoencephalography (MEG) at rest, we studied thirty AD patients without subclinical epileptiform activity (AD-EPI−), and twenty AD patients with subclinical epileptiform activity (AD-EPI+), and thirty-five age-matched controls. Presence of subclinical epileptiform activity was assessed in patients with AD by long-term video-electroencephalography (LTM-EEG) and a 1-hour resting magnetoencephalography with simultaneous EEG (M/EEG). Using the resting-state source-space reconstructed MEG signal, in patients and controls we computed the global imaginary coherence in alpha (8–12 Hz) and delta-theta (2–8 Hz) oscillatory frequencies. We found that AD-EPI+ patients have greater reductions in alpha imaginary coherence and greater enhancements in delta-theta imaginary coherence, than AD-EPI− patients and that these changes can distinguish between AD-EPI+ and AD-EPI− patients with high accuracy. Finally, a principal component regression analysis showed that the variance of frequency-specific neuronal synchrony predicts longitudinal changes in Mini Mental State Exam (MMSE), in patients and controls. Our results demonstrate that quantitative neurophysiological measures are sensitive biomarkers of network hyperexcitability and can be used to improve diagnosis and to select appropriate patients for the right therapy in the next generation clinical trials. The current results provide an integrative framework for investigating network hyperexcitability and network dysfunction, together with their cognitive and clinical correlates in patients with AD.