BME PhD Preliminary Exam Announcement for Seungbin Park (M. Dadarlat, advisor) Everyone is invited to attend the public presentation beginning at 10:00am. Title: Decoding multi-limb trajectories of a running mouse from calcium imaging using deep learning Date: March 27, 2024 Time: 10:00 am Location: DLR 221 Advisory committee: Maria Dadarlat (Advisor, BME), Eugenio Culurciello (BME), Young Kim (BME), Joseph Makin (ECE) Abstract: Decoding neural activity into behaviorally-relevant variables such as speech or movement is an essential step in the development of brain-machine interfaces (BMIs) and can be used to clarify the role of distinct brain areas in relation to behavior. Two-photon (2p) calcium imaging provides access to thousands of neurons with single-cell resolution and therefore is a promising tool for next-generation optical BMIs. However, decoding 2p calcium imaging recordings into behavioral variables for use in real-time applications has traditionally been challenging due to the low sampling rate of the signal as well as the indirect and non-linear relationship between the underlying neural activity and the slow fluorescent signal. Here, I aim to decode the continuous multi-limb trajectories of running mice from neural recordings made with 2p calcium imaging over the primary somatosensory cortex and primary motor cortex in a single hemisphere using deep learning. The work demonstrates the feasibility of using deep learning methods to identify and characterize populations of neurons that encode behaviorally-relevant variables. This approach will be critical in the future implementation of neural decoding for next-generation optical BMIs that will improve the lives of patients suffering from neurological injury and disease.