Network-Level Characterization of Hippocampal Disruptions in Alzheimer's Disease Using Large-Scale Electrophysiology.

Abstract

Alzheimer's disease (AD), a progressive neurodegenerative disorder, is projected to affect over 130 million people globally by 2050. While extensive efforts have focused on targeting molecular hallmarks such as amyloid-beta (Aβ) plaques and tau pathology, network-level dysfunction remains a critical but underexplored component of AD progression. Disruptions in hippocampal-cortical (HC) circuit activity emerge early in AD, compromising memory processing and cognitive functions. Characterizing these disruptions requires high-resolution platforms capable of capturing network-wide spatiotemporal dynamics. To address this, we implemented a high-density microelectrode array (HD-MEA) biosensor to assess large-scale electrophysiological activity in ex vivo hippocampal slices from well-established APPand APPmouse models. Our approach quantifies hippocampal oscillatory disturbances and examines their modulation by saffron, a natural compound with reported neuroprotective properties. Results indicate that hippocampal network activity is progressively impaired in APPmice, particularly in sharp-wave ripple (SWR) and multi-unit activity (MUA) patterns. The HD-MEA platform provides a scalable tool for investigating AD-associated network dysfunctions and exploring potential modulatory interventions.