David M
- Research Program Mentor
PhD candidate at University of Minnesota - Twin Cities
Expertise
psychology, neuroscience, cognition, reasoning, research methods, computation, statistics, naturalistic behavior, reinforcement learning, neuroeconomics, decision making, memory, navigation, Computational Neuroscience, Decision Making
Bio
Broadly, my work is focused on understanding how the activity of individual and populations of neurons support natural behaviors. In particular, my goal is to determine what generalized principles (like computational and algorithmic architectures) are used by system of neurons to generate patterns of behavior. My passion is to understand the complex interplay between entangled cognitive processes and the computations that explain how neurons produce these processes. Personally, my primary interest is spending time with my two children. Beyond that my hobbies are principally centered around fitness. I enjoy weightlifting and I train for distance running (marathons and such). I also enjoy video games and movies.Project ideas
Comparing organic and artificial neural networks in learning to optimally perform value-based decision making
This project is to design and report on a research project in which a recurrent neural network acts as an agent learning to perform a traditional neuroeconomic choice task. The objective is to understand how the optimized (asymptote) behavior of an RNN reflects the behavior commonly described in the neuroeconomic literature. The implication is to see how well an artificial network described the activity of the organic neural activity recorded from real subjects performing the same task.