Ph.D., University of Pittsburgh
B.S., Cornell University
etricomi (at) psychology.rutgers.edu
Broadly speaking, my research focuses on the influences of affective information on cognitive processing in the brain. The affective qualities of our experience not only produce subjective feelings that may be positive or negative, but also provide information that allows us to shape future behavior. To understand how the consequences of ones decisions can be used to determine future actions, I use functional magnetic resonance imaging (fMRI) to investigate the role of the brains reward processing system in feedback-based learning. My work examines contextual influences on learning and decision making, and the neural systems that underlie these processes. For example, my research indicates that the sensitivity of the striatum, a region in the basal ganglia, to reward-related information depends on factors such as whether one feels a sense of agency in producing an outcome or whether a habit has been formed after extensive experience. This research has important implications for understanding how cognitive processes such as learning and decision making are carried out in the normal brain, as well as for understanding how impairments of the brains reward processing system may give rise to disorders such as addiction and other compulsive behaviors.
Graduate Student, Fourth Year
P.h.D. Candidate - Rutgers University
M.S., Seton Hall University
B.A., Seton Hall University
My broad research interests include the influences of motivation and decision-making processes on cognitive performance, as well as how this relationship is represented within the brain. Currently, I am investigating how to make performance feedback (especially negative feedback) more rewarding – more specifically, how to enhance reward valuation of the relevant information that feedback provides (despite potential costs associated with obtaining it – e.g., being wrong), and how to consequently augment people’s feedback-seeking behavior. In addition to behavioral methods, I utilize functional magnetic resonance imaging (fMRI) to better understand the neural mechanisms of contextual factors that shape the valuation processes underlying this form of decision-making, and their impact on cognitive performance. My goal is to apply this line of work to feedback-based cognitive interventions used within clinical populations, such as multiple sclerosis, as I believe that this research may have implications for optimizing intervention success rate by improving participant engagement.
Graduate Student, First Year
Graduate Student - Rutgers University
B.S., University of Vermont
Broadly, I am interested in the processes by which humans learn and make decisions, the influences of context, feedback, and cognitive biases, and the reasons that individuals or groups act in ways that sabotage their goals. I hope to conduct research that combines psychology and neuroscience methodologies with behavioral economics to expand on what we know about human behavior. More specifically, I am interested in applying this research to study and nudge behavior in many areas including personal goals, health, resource management, substance use and abuse, climate-conscious actions, and more.
Lab Manager / Research Assistant
B.A., Rutgers University, New Brunswick
My scientific interests exist at the intersection of neuroscience and education. Specifically, I am interested in the neural substrates of feedback-seeking behavior and feedback-based learning in the presence of negative feedback. Generally, negative feedback is aversive and is sometimes avoided despite its utility to improve individual work performance. How can we encourage students and those in the work force to seek out negative feedback? Here, I would like to investigate manipulations in feedback timing (e.g. increasing delay between performance and feedback) to encourage feedback-seeking behaviors/feedback-based learning in negative feedback conditions.
Research Assistants as of Spring 2021
Post-baccalaureate Research Assistant
Working with: Chris Cagna