Valerie Reyna and Charles Brainerd have received a two-year challenge grant from the National Institutes of Health to improve the prediction and diagnosis of cognitive impairment. Memory declines, especially in recall, are hallmarks of healthy aging and conversion to cognitive impairment. The project will use highly sensitive mathematical modeling techniques to improve the ability of clinical recall tests to predict future cognitive impairment and to diagnose current impairment. Their research will focus on one of the most widely used clinical tests of such declines, the Rey Auditory Verbal Learning Test (RAVLT).
The specific aims of the project are to apply mathematical models to RAVLT data in order to: (a) substantially improve the ability of the RAVLT and similar clinical recall tests to predict future impairment and to diagnose current impairment; (b) separate different clinically important components of memory from one another in accordance with current theories of the memory processes that underlie performance on the RAVLT and similar tests; (c) identify the components of memory that differentiate cognitive changes that are associated with normal aging from changes that are associated with conversion to impairment; and (d) provide separate scores for different memory components of RAVLT data, which can be used to better predict behavioral and biological markers of future impairment and to identify current impairment.
The research will consist of 2 phases, spanning 2 years. Both phases will rely on mathematical modeling tools and software that the investigators have previously developed. Preliminary studies have shown that RAVLT-type tests are inherently noisy measures of impairment because 3 different memory processes are responsible for performance, but only 1 of them (gist-based reconstruction) is responsible for conversion to impairment. The investigators will look at the effectiveness of modeling tools to remove this noise.
The first phase will establish whether noise-free scores improve the ability to separate groups of subjects that differ on biological markers of impairment, behavioral markers of impairment, and clinical diagnoses of impairment. This question will be investigated using a very large sample of subjects who participated in the Aging, Demographics, and Memory Study (ADAMS) portion of NIA’s Healthy Retirement Study. The second phase will establish whether noise-free scores improve the ability to differentiate individual people who differ in biological markers of impairment, behavioral markers of impairment, and clinical diagnoses of impairment. This question will be investigated in a longitudinal study of 200 adults (aged 70 and above) who will be administered a neuropsychological test battery as well as 3 versions of the RAVLT, spaced at 6-month intervals.