Using large publicly available databases, my research also examines how sleep influences cognitive function and how this relationship is shaped by factors such as aging and physical activity (e.g., sleep tends to affect cognition less in older adults than in younger adults). In addition, by computing genetic susceptibility from genome-wide association studies (GWAS) and genomic data, I investigate how genotype–phenotype relationships (e.g., genetic risk for major depressive disorder and its expression in diagnosis or self-reported symptoms) are moderated by environmental factors, including physical exercise, neighborhood disorder, and religious belief.
I am interested in identifying the environmental features that make wayfinding most challenging, and in testing whether simplifying these features in virtual reality (VR) can improve real-world navigation. In a series of studies, my team has developed and evaluated different types of navigation aids, showing that their effectiveness varies across individuals depending on sense of direction, cognitive profile, and sex. Building on this work, my future research will focus on designing customized spatial navigation training—particularly for older adults—to boost confidence, enhance wayfinding in complex environments, and promote independent living.
My research examines how acute stress shapes learning and decision-making. In particular, I investigate whether stress affects rigid learning (repeating familiar behaviors) differently from flexible learning (adapting to task structure), and how stress alters the use of declarative memory to guide value-based choices. Using VR, fMRI, cardiovascular recordings and computational modeling, I aim to provide an integrated understanding of how stress influences the interaction between learning, memory, and decision-making across the adult lifespan.