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Validation of a Virtual Reality Floor Maze Test to Detect Early Signs of Cognitive Impairment

Award Number: R21AG072469
ORGANIZATION: NATIONAL INSTITUTE ON AGING
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)
PERIOD OF PERFORMANCE START DATE: 09/30/2021
PERIOD OF PERFORMANCE END DATE: 08/31/2025

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Validation of a Virtual Reality Floor Maze Test to Detect Early Signs of Cognitive Impairment - PROJECT SUMMARY/ABSTRACT Early diagnosis and identification of predictors for Alzheimer’s Disease (AD) is crucial as it allows intervention with prevention and treatment strategies when neuronal loss is at its minimum. Spatial navigation is a complex and multi-component skill that gets impaired early in the course of brain diseases and may be considered a relevant, sensitive and specific marker for future clinical progress of AD, even in its preclinical stage. Active spatial navigation assessments allow to identify modifications of gait associated with cognitive decline, and to amplify the difficulty of the test through a dual task effect created by the increased postural demands of walking. This study will validate the first motor-cognitive screening instrument able to extract digital markers in the form of navigational and gait performances in people at risk of developing AD. We propose that a fully immersive Virtual Reality (VR) navigational test has numerous advantages with respect to classical tests because it allows the manipulation of environmental features based on specific needs. We will use a VR version of the Floor Maze Test (VR-FMT) to create virtual mazes with preferred complexity and display them within a commercial VR headset. Cognitively normal adults at low risk and higher risk of developing AD and subjects with amnesic mild cognitive impairment will complete two visits. In the first visit, a battery of neuropsychological tests will be taken. In the second, participants will perform multiple navigations inside the VR-FMT. Two visuals representations (vista and environmental), and two explorations types (real walking and with a joystick) will be tested. Gait will be recorded using VR trackers and a motion capture system. Functional near-infrared spectroscopy (fNIRS) will be used to measure resting-state brain connectivity. In Aim 1 we will validate the gait measures and the manipulations operated by the VR-FMT. We hypothesize that the portable trackers will show comparable validity in measuring gait compared to the optical motion capture system and that participants will show different navigation performance in the walking and the in-place versions and in the environmental and vista spaces versions of the VR-FMT. In Aim 2 we will investigate the ability of the VR-FMT as a test to differentiate the various levels of cognitive impairment. We hypothesize that navigation performance while performing the active version of the VR-FMT in the environmental space would show superior ability to distinguish the groups. Then, a machine learning algorithm will be used to extract the most significant features and classify participants. We hypothesize that both gait and navigation performances would increase the sensitivity of the classifier. In Aim 3 we will explore associations between performance in the VR-FMT, neuropsychological tests, and brain connectivity. We hypothesize that lower navigation performance will be associated with altered brain connectivity and lower psychomotor speed, memory and executive function scores. Findings from this research will set the stage for further longitudinal studies which will be aimed at predicting accumulating AD biomarkers. The long-term goal is to develop an accurate, low-cost, user-friendly, and portable system that can be used to predict cognitive decline.


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: 2025 ( Subtotal = $0 )
2025	2021	UNIVERSITY OF ALABAMA	801 UNIVERSITY BLVD	TUSCALOOSA	AL	35401	TUSCALOOSA	USA	Aging Research	000	1	2/18/2025	NEW	-$1,268
2025	2021	MEDSTAR HEALTH RESEARCH INSTITUTE INC.	10980 GRANTCHESTER WAY 7TH FL	COLUMBIA	MD	21044	HOWARD	USA	Aging Research	001	2	2/18/2025	CHANGE OF GRANTEE / TRAINING INSTITUTION / AWARDING INSTITUTION	$1,268
														Subtotal = $0

Issue Date FY: 2024 ( Subtotal = -$1 )
2024	2021	MEDSTAR HEALTH RESEARCH INSTITUTE INC	6525 BELCREST RD STE 700	HYATTSVILLE	MD	20782	PRINCE GEORGES	USA	Aging Research	002	2	8/28/2024	CHANGE OF GRANTEE / TRAINING INSTITUTION / AWARDING INSTITUTION	$0
2024	2021	MEDSTAR HEALTH RESEARCH INSTITUTE INC	6525 BELCREST RD	HYATTSVILLE	MD	20782	PRINCE GEORGES	USA	Aging Research	001	2	12/15/2023	CHANGE OF GRANTEE / TRAINING INSTITUTION / AWARDING INSTITUTION	$107,482
2024	2021	UNIVERSITY OF ALABAMA	301 ROSE ADMIN BLDG	TUSCALOOSA	AL	35487	TUSCALOOSA	USA	Aging Research	000	1	12/13/2023	NEW	-$107,483
														Subtotal = -$1

Issue Date FY: 2021 ( Subtotal = $355,890 )
2021	2021	UNIVERSITY OF ALABAMA	301 ROSE ADMIN BLDG	TUSCALOOSA	AL	35487	TUSCALOOSA	USA	Aging Research	000	1	9/21/2021	NEW	$355,890
														Subtotal = $355,890

Grand Total All Awards = $355,889

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Validation of a Virtual Reality Floor Maze Test to Detect Early Signs of Cognitive Impairment

Award Number: R21AG072469

ORGANIZATION: NATIONAL INSTITUTE ON AGING

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

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

PERIOD OF PERFORMANCE START DATE: 09/30/2021

PERIOD OF PERFORMANCE END DATE: 08/31/2025

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