Multiscale Models of Age-Specific Neurometabolic Coupling

About This Grant

Cognition is intricately linked to the metabolic processes of the brain, yet existing computational models often overlook the metabolic costs associated with cognitive function. This oversight is critical, especially in neurodegenerative diseases like Alzheimer's, where metabolic dysfunctions play a significant role in cognitive decline. Despite advancements, research biases towards familial AD models have hindered a comprehensive understanding of metabolic changes in aging and late- onset AD, calling for focused investigations into sporadic late-life AD models. Our proposal aims to bridge this gap by comprehensively studying neuro-metabolic coupling using state-of-the-art imaging techniques and computational models. We propose a multifaceted approach involving in vivo microscopy, wide-field imaging, and MRI to elucidate the intricate relationship between neuronal activity and metabolic processes such as oxidative phosphorylation, glucose, lactate, and creatine dynamics. Our specific Aims include (1) Modeling SingleCell Neurometabolic Coupling: Utilizing in vivo two- photon microscopy, we will investigate the astrocyte-neuronal lactate shuttle and quantify the relationship between red blood cell velocity, lactate levels, and neural activity in late-onset AD mouse models. (2) Establishing Cortical Network Models of Neuro-Metabolic Coupling: We will employ multispectral wide-field imaging to examine the role of oxidative phosphorylation in neuronal connectivity, validate computational models with experimental capillary obstructions, and assess sex-specific differences in mitochondrial function. (3) Building a WholeBrain Theory of Neuro-Metabolic Coupling: Through non-invasive brain imaging techniques, we will explore the impact of glucose and creatine metabolism on whole-brain functional connectivity. We will integrate data from animal models and human cohorts to predict Excitation- Inhibition Balance patterns and identify metabolic biomarkers of cognitive decline. This project addresses critical gaps in our understanding of neuro-metabolic coupling in aging and late-onset AD, offering insights into metabolic vulnerabilities and potential targets for personalized therapeutic interventions. Our proposal combines modern neuroscience with multiscale imaging to construct comprehensive models of neuro-metabolic coupling, providing a novel framework for understanding brain function and dysfunction in aging and AD. By integrating data from animal models and human cohorts, we will uncover new insights into the metabolic underpinnings of cognitive decline, advance early diagnosis, and develop more accurate metabolic biomarkers for AD.