Peter Duggins

PhD Student in Systems Design Engineering


In my masters thesis, I developed methods for constructing functional models from biophysically-detailed neurons. It is my hope that these techniques can be used to simulate and study a wide range of biophysical mechanisms in the brain that were previously inaccessible with simple neuron models, as well as reduce our reliance on animal experiments and human trials when designing treatments for mental disorders. I also view this is as a necessary step in understanding the neuromodulatory control that emotional systems exert over other cognitive processes.

In my doctoral thesis, I studied the neural and cognitive mechanisms of learning and decision making, with a particular focus on social cognition. I built spiking neural models of fear conditioning in the amygdala, inference and decision making under time pressure, and reinforcement learning in social games. My long-term goal is to build and train biologically- and cognitively-realistic agents, then use these agents to simulate artificial societies and study large-scale social and political phenomenon.



Journal Articles

Conference and Workshop Papers