# Naturalistic driving as a functional neurobehavioral marker of preclinical and symptomatic Alzheimer disease

> **NIH NIH R01** · WASHINGTON UNIVERSITY · 2020 · $1,317,171

## Abstract

PROJECT SUMMARY/ABSTRACT
 Our long-term goal is to accurately identify who is at risk of driving decline, to establish whether driving
behavior can be used as a functional, neurobehavioral biomarker of Alzheimer disease (AD), to forecast when
driving decline will occur, to intervene before the time of decline, and to prevent a significant number of
crashes, injuries, and death. Our findings indicate that the long preclinical stage of AD, as reflected in amyloid
and tau imaging and cerebrospinal fluid (CSF) biomarkers among cognitively normal older adults, is associated
with poorer driving performance on a road test, as well as with fewer trips made in a personal vehicle. This
project will test the extent to which an in-vehicle datalogger, measuring everyday driving behavior continuously,
reflects underlying neuropathological AD and is associated with prevalent and incident cognitive impairment.
 This research is significant because 36 million licensed drivers are aged 65 years or older, and the
number of older adults in the United States is expected to double by 2050, when 1 in 4 drivers will be 65+. Our
work suggests that changes in driving, an instrumental activity of daily living that involves both cognitive and
functional abilities, may reflect neuropathological AD and precede the emergence of dementia symptoms.
 Our Specific Aims will (1) Use established cerebrospinal fluid (CSF) and imaging biomarkers to define
preclinical AD and test the ability of the Driving Real-world In-Vehicle Evaluation System (DRIVES) to
distinguish persons with and without preclinical AD among cognitively normal individuals, and assess the ability
of this system to predict the future onset of dementia, (2) Test the ability of the DRIVES data to distinguish
cognitively normal persons from those with dementia cross-sectionally, and to examine driving behavior over
time for both groups, (3) Determine whether the DRIVES data, combined with cognitive, health, and functional
data from older adults, can improve prediction of incident cognitive impairment and dementia.
 To test these Specific Aims, we have assembled a multidisciplinary team with expertise in AD,
neuroimaging biomarkers (amyloid and tau), fluid biomarkers (CSF and blood), naturalistic driving, spatial
navigation, cognitive and brain aging, and longitudinal biostatistical methods. We will capitalize on existing
institutional infrastructure to longitudinally follow 300 cognitively normal older adults and 50 older adults with
mild or very mild dementia, to create a cohort of 350 individuals. This cohort will be followed using a naturalistic
driving methodology that will capture their driving behaviors on a daily basis. Their cognition will be tested
annually using the Clinical Dementia Rating and various neuropsychological measures.
 Once obtained, this knowledge can be used to map driving as a neurobehavioral biomarker that may be
monitored and used for clinical trials and interventions throughout disease pro...

## Key facts

- **NIH application ID:** 10040061
- **Project number:** 1R01AG068183-01
- **Recipient organization:** WASHINGTON UNIVERSITY
- **Principal Investigator:** Ganesh M Babulal
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $1,317,171
- **Award type:** 1
- **Project period:** 2020-09-15 → 2025-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10040061

## Citation

> US National Institutes of Health, RePORTER application 10040061, Naturalistic driving as a functional neurobehavioral marker of preclinical and symptomatic Alzheimer disease (1R01AG068183-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10040061. Licensed CC0.

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