Integrating Experimental and Computational Models to Study the Prefrontal Microcircuit Changes During Aging and Alzheimer's Disease

The overarching goal of this proposal is to determine and predict microcircuit changes in the prefrontal cortex (PFC) during healthy aging and disease progression in Alzheimer’s disease (AD), by integrating empirical in vivo calcium imaging recording, computational simulation modeling, and calcium imaging-based neural decoding.

Functional magnetic resonance imaging studies have suggested disruptions among different brain regions in AD patients. However, PFC microcircuit changes during normal aging and AD initiation and propagation, and how these changes relate to cognitive dysfunctions in AD are poorly understood. We will take a multidisciplinary approach capitalizing on our team’s expertise in

miniscope in vivo calcium imaging, simulation modeling and graph theory-based network analysis, and neural decoding. Real-time calcium imaging from awake behaving animals makes it possible to directly visualize the PFC microcircuit changes during aging and dementia. Simulation modeling helps to tease out the primary degeneration and secondary compensatory

effects on a microcircuit. Calcium imaging-based neural decoding is a powerful multivariate approach that integrates empirical and computational microcircuit data to understand normal aging and AD pathogenesis processes. Together, we will perform empirical and computational studies simultaneously to determine the impacts of normal aging and various AD related

pathologies on the PFC microcircuit. We believe that our strategies will revolutionize our understanding of aging and AD disease progression, and help developing new effective treatments for AD.