Novel Technologies for Neuropsychological Assessment and Modeling of Cognitive Aging

Abstract: Novel technologies (e.g., virtual/augmented reality; wearable sensors; speech emotion estimation) and methodologies (e.g., artificial intelligence; machine learning) offer promise for assessing and modeling biomarkers of social experiences, activities of daily living in cognitive aging, as well as interventions and rehabilitation of cognitive pathologies. Moreover, neuroinformatics and collaborative knowledge bases can enhance understanding of how aging phenomena vary by race, ethnicity, gender, socioeconomic status, sexual identity, and other diverse populations. Two federally funded projects will be discussed. The first involves novel virtual reality environments for assessing functional capacities in individuals with Alzheimer’s disease or Alzheimer’s disease related dementia. This multi-site study involves a collaborative knowledge base for neuroinformatic analyses of data from these older adults. The second involves computational and statistical modeling of suicide among aging veterans.  These predictive models involve novel methodologies (e.g., artificial intelligence; machine learning) for enhanced understanding of the ways in which suicide risk varies by age, race, ethnicity, gender, socioeconomic status, sexual identity, and other diverse classifiers.