Grant: Fellowship - Priority Announcement: Aging

Human brain aging involves a variety of cellular and synaptic changes, but how these changes affect impairments in brain activity remains poorly understood. The growing availability of human data provides opportunities for exploring the impact of aging brain cells. New computational models that can generate simulated EEG brain signals and mimic small parts of the human brain, i.e., human microcircuits, can help us examine how aging brain cells affects brain activity, which is impossible to link directly in real humans. Our team has identified key changes with age (loss of inhibitory cells, loss of synapses, and changes in synaptic composition), and my proposed project will integrate these changes by tuning parameters in detailed human microcircuit models. We can then see how these changes influence brain activity by studying patterns of simulated brain cells and how they process information, which often declines with age. Lastly, using simulated EEG brain signals I will develop diagnostic tools that can estimate the levels of inhibitory cell loss, synaptic composition, and synapse loss with age. Changes in these brain signals with age in live humans have not yet been directly linked to cellular changes. With these models we will thus develop tools that estimate human cellular and synaptic aging from patient EEG brain signals. This work will circumvent the challenges in studying how aging in the brain can lead to cognitive impairments and will facilitate the design of new diagnostics and treatments that target the cellular and synaptic changes underlying cognitive decline in aging.