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Deep learning for prediction of Mild Cognitive Impairment and Dementia of the Alzheimer's type

Award Number: R21AG082204
ORGANIZATION: NATIONAL INSTITUTE ON AGING
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)
PERIOD OF PERFORMANCE START DATE: 06/01/2023
PERIOD OF PERFORMANCE END DATE: 02/28/2025

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Deep learning for prediction of Mild Cognitive Impairment and Dementia of the Alzheimer's type - ABSTRACT Alzheimer’s disease and associated dementias are major public health challenges with a multifold increase in prevalence expected in the coming decades. Alzheimer’s disease is increasingly recognized as having network- level effects and interactions. In this project, we will develop a deep learning model to learn the latent representation of functional neuroimaging, in order to disentangle the underlying sources and better reconstruct the data. Deep learning approaches in fMRI have faced a common challenge on generalizability and explainability. To address these issues, the system will learn representations that can be decoded and interpreted as spatial patterns and temporal dynamics of brain networks; and be readily generalizable to different subjects, brain states, behavioral tasks, and disease conditions without a need to redesign or retrain the system from scratch. The proposed focus on Alzheimer’s disease is the first step in exploiting this notion for clinical application. We will leverage both publicly available large data (e.g., Human Connectome Project-Aging, Alzheimer’s Disease Neuroimaging Initiative) as well as the well-characterized longitudinal cohort of the NIA P30-funded Michigan Alzheimer’s Disease Research Center (MADRC); this cohort undergoes annual neurological and neuropsychological evaluations and is particularly unique since it consists of ~45% African Americans. This research is particularly relevant for ethnic minority populations since African Americans are almost twice as likely to develop cognitive decline as Non-Hispanic white Americans; yet most of what has been learned about dementia biomarkers is based on study samples that are primarily Non-Hispanic white Americans. The overall goal of this project is to develop an enhanced deep learning model for improved data representation, subtype classification and prediction of clinical behavioral measures and apply it to the domain of mild cognitive impairment (MCI) and dementia of the Alzheimer’s Type (DAT).


Issue Date FY	Funding FY	Legal Entity Name	Legal Entity Address	Legal Entity City	Legal Entity State	Legal Entity Zip Code	Legal Entity COUNTY	Legal Entity COUNTRY	Assistance Listing	Award Code	Budget Year	Action Date	Action Type	Action Amount

Issue Date FY: 2024 ( Subtotal = $185,034 )
2024	2024	REGENTS OF THE UNIVERSITY OF MICHIGAN	1109 GEDDES AVE, SUITE 3300	ANN ARBOR	MI	48109	WASHTENAW	USA	Aging Research	001	2	7/3/2024	NON-COMPETING CONTINUATION	$18,504
2024	2024	REGENTS OF THE UNIVERSITY OF MICHIGAN	1109 GEDDES AVE, SUITE 3300	ANN ARBOR	MI	48109	WASHTENAW	USA	Aging Research	000	2	1/31/2024	NON-COMPETING CONTINUATION	$166,530
														Subtotal = $185,034

Issue Date FY: 2023 ( Subtotal = $224,509 )
2023	2023	REGENTS OF THE UNIVERSITY OF MICHIGAN	503 THOMPSON STREET	ANN ARBOR	MI	48109	WASHTENAW	USA	Aging Research	000	1	5/23/2023	NEW	$224,509
														Subtotal = $224,509

Grand Total All Awards = $409,543

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Deep learning for prediction of Mild Cognitive Impairment and Dementia of the Alzheimer's type

Award Number: R21AG082204

ORGANIZATION: NATIONAL INSTITUTE ON AGING

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)

PERIOD OF PERFORMANCE START DATE: 06/01/2023

PERIOD OF PERFORMANCE END DATE: 02/28/2025

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