Hyun Dong Lee

Recent findings reveal that the brain’s internal representation of the external world undergoes large-scale changes over time, a phenomenon termed representational drift. To understand how the brain maintains stable computation despite ongoing internal fluctuations and whether these drifts play a pivotal role in neural computation, such as learning and memory, I am developing novel state space models for dissecting various elements of drifts with different timescales and examining how different contexts affect drift rates. A better understanding of drift is also pivotal in improving brain-computer interfaces, which still suffer from gradual degradation in decoding performance due to their inability to adapt to drift.