Development of Neurocognitive Eye Tracking for Rapid Screening of Mild Cognitive Impairment

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Project Summary Alzheimer’s Disease (AD) affects an estimated 5.8 million adults in the U.S. By 2030 this number is expected to increase almost 45% to 8.4 million and without new treatment or interventions, by 2050 there will be more than 13.8 million seniors living with Alzheimer’s dementia in the U.S. (Alzheimer's Association, 2019). AD is associated with a spectrum of neurocognitive signs and symptoms that lead to significant morbidity and mortality, and the lack of readily-available screening for neurocognitive decline has led to a situation where most dementia cases are detected and diagnosed when the disease becomes overt, adding risk to patients in early stages of degenerative disease and burdening the healthcare system with additional costs. Our Phase I SBIR project will develop novel oculometric (i.e., eye-movement-based) technologies for functional assessment of neural circuits, useful as a monitoring biomarker during healthy aging and to the monitor progression of healthy aging, mild cognitive impairment (MCI) and AD. The clinical significance and market need for improved assessment of MCI and AD is established by three main points. First, and most importantly, a large number of seniors are living with undetected dementia (Sternberg et al., 2000) and only sixteen percent of seniors undergo cognitive screening on a yearly basis (Alzheimer's Association, 2019) indicating a need for new techniques, methods, and technologies. Second, progress in development of effective drugs for AD is hindered by outdated, subjective outcome measures (Mehta et al., 2017). Third, monitoring biomarkers are needed to assess effects of lifestyle interventions (Kivipelto et al., 2018) and other modifiable risk factors for dementia (Livingston et al., 2017). Together, these gaps, limitations, and encouraging possibilities necessitate the development of novel biomarkers of central nervous system (CNS) function. Our team will develop a battery of eye-movement-based tests tuned to the specific cognitive impairments that arise in MCI and AD, to be implemented using the neuroFit ONE oculometric R&D platform. We will also use neuroFit ONE to prototype a novel computational architecture for eye-tracking appropriate for use with diverse patient populations, suitable for incorporation into consumer electronic devices. Our goal is to develop a suite of oculometric tools suitable for medical and consumer use: high-sensitivity medical devices for use in the clinic and a consumer-grade solution for distribution in electronic devices (e.g., virtual reality headsets).