Over the summer, I contributed to a project at the intersection of psychology and economics. The goal of the project was to find an indication of depression that is more objective and quantitative than a self-report. By examining eye-tracking and mouse-tracking patterns of participants observing a risk of gaining money or losing money, the research goal was to discover biomarkers that indicate levels of depression and can signal risk for severe depression. Participants were given $10 and instructed to choose accepting or rejecting gambles that would affect the amount of money that they would leave the study with.
As an engineering student joining a team consisting of students in cognitive science and the business school, my role in the project was more on the quantitative and analytical part as well as electrical setup. On top of these tasks that suit my skills, I learned very much about topics for which I have received less formal education. I learned about neuroscience and the connection between loss aversion and depression. People with depression are more likely to have a greater degree of loss aversion than people without depression. Every week, members of the lab presented their ongoing research at a lab meeting. I learned about other projects that involve Rhesus macaque monkeys or trends in neuroeconomics. Overall, it was an interesting summer of research where I stepped out of my primary discipline and learned information that I had not and most likely will not learn in the engineering classroom. Participating in this research project allowed me to immerse myself in a specific subject matter. My major is extremely broad, and a smaller concentration within it is computational neuroscience. My research this summer allowed me to use skills from classes I had taken, such as Matlab and Python. The application of these skills has given me real experience in a concentration and shown me what I am capable of doing given my knowledge in a less broad setting.