PREDICTION OF DEMENTIA IN OLDER ADULTS USING NONLINEAR EEG FEATURES - PROJECT SUMMARY EARLY PREDICTION OF D…
Federal financial assistance recorded from USAspending. This is not a procurement contract.
Assistance award details
- Assistance award identifier
- ASST_NON_R00AG083234_075
- FAIN
- R00AG083234
- Recipient
- THE GENERAL HOSPITAL CORPORATION
- Awarding agency
- Department of Health and Human Services
- Funding agency
- Department of Health and Human Services
- Assistance listing (CFDA)
- 93.866
- Total obligated
- $249,000
- Period
- Jul 15, 2024 – Jul 31, 2029
- Fiscal year
- 2026
- Place of performance state
- MA
- Source file
- FY2026_All_Assistance_Full_20261006.zip
Description
PREDICTION OF DEMENTIA IN OLDER ADULTS USING NONLINEAR EEG FEATURES - PROJECT SUMMARY EARLY PREDICTION OF DEMENTIA CAN PROVIDE A UNIQUE OPPORTUNITY FOR INTERVENTIONS TO PREVENT OR DELAY THE ONSET OF DEMENTIA. THERE IS EVIDENCE THAT ALTERATIONS IN MANY PHYSIOLOGICAL FUNCTIONS PRECEDE THE CLINICAL ONSET OF ALZHEIMERâS DISEASE AND RELATED DEMENTIA. THE HYPOTHESIS BEHIND THIS PROPOSAL IS THAT BRAIN ACTIVITIES ASSESSED BY ELECTROENCEPHALOGRAM (EEG) SIGNALS CAN OFFER PROGNOSTIC VALUE FOR PERSONS AT RISK FOR DEMENTIA. THE GOAL OF THIS PROJECT IS TO DEVELOP EEG BIOMARKERS (EDBS) TO PREDICT FUTURE RISK OF DEMENTIA AND MONITOR THE PROGRESS OF COGNITIVE DECLINE. TO ACHIEVE THE GOAL, THE PI AND HIS TEAM PROPOSE TO INVESTIGATE/ASSESS THE COMPLEX EEG FLUCTUATIONS USING BOTH TRADITIONAL AND NOVEL METHODS DERIVED FROM NONLINEAR DYNAMICS THEORY. DEEP LEARNING (DL) â THE RECENT ADVANCE IN THE FIELD OF ARTIFICIAL INTELLIGENCE â WILL BE USED TO EXTRACT EEG FEATURES FROM MULTIPLE EEG MEASURES AND DEVELOP EDBS FOR THE RISK FOR DEMENTIA. USING THE EXISTING DATASETS OF FOUR COHORTS IN THE NATIONAL SLEEP RESEARCH RESOURCE (NSRR) THAT TOGETHER PROVIDE >8,000 OLDER ADULTS WITH ASSESSMENTS OF OVERNIGHT EEG, COGNITIVE STATUS AND GENETIC DATA, FOUR AIMS WILL BE ADDRESSED. IN AIM 1, DEEP CONVOLUTIONAL NEURON NETWORK MODELS WILL BE BUILT TO CONSTRUCT EDBS USING EEG MEASURES AT DIFFERENT WAKE/SLEEP STAGES TOGETHER (AIM 1A) OR SEPARATELY (AIM 1B). THE EFFECTS OF SEX AND ETHNICITY ON EDBS AND THEIR PERFORMANCE IN PREDICTING DEMENTIA WILL ALSO BE EXAMINED (AIM 1C). IN AIM 2, THE LONGITUDINAL CHANGES IN EDBS AND THEIR ASSOCIATIONS WITH LONGITUDINAL CHANGE IN COGNITION WILL BE DETERMINED. IN AIM 3, GENETIC FACTORS RELATED TO THE RISK FOR ALZHEIMERâS DISEASE (AIM 3A, 3B) AND SLEEP/CIRCADIAN (AIM 3C) WILL BE COMBINED WITH DERIVED EDBS TO IMPROVE THE PREDICTION OF INCIDENT DEMENTIA. IN EXPLORATORY AIM 4, THE LINKS OF EDBS TO NON-COGNITIVE FUNCTIONAL OUTCOMES SUCH AS SLEEP/CIRCADIAN DISTURBANCES AND