The diagnosis and monitoring of cognitive symptoms in Alzheimer's disease and related dementias (ADRD) requires valid and reliable assessment of cognitive change. Current limitations in traditionally used testing measures include the length of testing, low engagement, day-to day variability, few data points, and limits in the ability to identify subtle differences in normal individuals at risk for cognitive decline. Many of the currently available computerized assessment tools either (1) have not been updated to incorporate current cognitive neuroscience theory (2) do not target measures associated with the earliest neuroanatomical changes in brain aging and neurodegeneration and/or (3) do not capitalize on the benefits of digital technology to maximize valid and reliable cognitive data collection. Mobile and sensitive measures for detection of subtle cognitive change in preclinical Alzheimer's Disease (AD) along with biomarker measures of molecular pathology and neurodegeneration will combine to identify individuals who will benefit most from interventions. This project will include development and validation of two, engaging, user-friendly and empirically based cognitive assessment tasks and create the Mobile Cognitive App Performance Platform (mCAPP). The two cognitive tests will comprise: (1) a memory card game (already designed and pilot-tested) that includes similar pairs of objects and increasing memory load and (2) an executive functioning and processing speed test using a code completion game. The cognitive tests will include a high-ceiling and low floor to capture a range of ability, burst testing to increase reliability of the data, gamified design to increase engagement and motivation, and mobile- based design for capturing data in all environments. The mCAPP will be validated in a well-characterized cohort of older adults with normal cognition in the Penn Alzheimer's Disease Center. The cohort will concurrently complete a neuropsychological battery, high resolution structural MRI and amyloid PET imaging through funded P32 and R01 projects, which will be leveraged in this study to understand the relationships between cognitive performance and neuroimaging biomarker status. Structural imaging targets will include areas of the medial temporal lobe implicated in the earliest stages of preclinical Alzheimer's disease. The purpose of the mCAPP is to collect reliable and valid cognitive data to detect very early signs of AD-related cognitive change and remotely track response to interventions. Remotely administered, engaging cognitive tests that are sensitive to the earliest changes in individuals at risk for AD have the potential to expand our knowledge of cognition in aging, lead to early detection of cognitive variability, monitor change over time and change as a result of intervention. This project will facilitate collection of data to support larger studies with the mCAPP and career development opportunities in ADRD research for the early career principal investigator.
As preclinical Alzheimer's Disease (AD) becomes a more common target of intervention studies, there is an increased demand for cognitive assessments that are sensitive to very early cognitive change. This study will develop the mobile Cognitive App Performance Platform (mCAPP), with tasks based on current theories of cognitive neuroscience and focused on areas of domain-specific cognitive deficits known to be impacted early in AD. The mCAPP will be validated in a cohort of carefully characterized individuals with neuropsychological and neuroimaging biomarker data in order to leverage existing data and create a tool that has the potential to reduce study participation burden, gamify the experience to increase engagement, and provide an opportunity to collect cognitive data frequently and quickly for the purpose of cognitive screening and monitoring cognitive change during intervention trials in preclinical AD.
