Biotechnology, Brown University
Alex’s undergraduate research at BrainGate focused on detecting differences in recorded neural features based on the task context in which brain-computer interfaces are used. By examining differences in user-generated signals during completion of analogous tasks using different end-effectors, he aimed to find feature patterns that help identify when a user intends to interact with one effector over another (e.g. a robotic arm vs. a computer cursor). This work could help lead to multi-effector systems where the user is able to seamlessly switch between end-effectors. Alex graduated in 2018 with an Sc.B. in Neuroscience.
While pursuing his Sc.M. in Biotechnology (class of 2019), Alex helped develop a minimally biased method for neural state space construction based on the intrinsic activity of neural ensembles. The goal of this work was to represent and identify different neural states experienced over the course of long-term recordings while also uncovering interesting neural phenomena otherwise masked by explicit models. Overall, these directions contribute to the overarching goal of developing a system to increase a user’s autonomy during long-term, chronic system use.