A core assumption in sensory neuroscience is that neural representations are stable—that the same stimulus will consistently evoke the same pattern of brain activity. However, recent studies, primarily in rodents, have demonstrated that neural representations change gradually over time, a phenomenon known as representational drift.

What changes do these representations undergo, and over what timescales? What drives this drift, and how might it affect perception and behavior?

In our lab, we combine computational modeling with longitudinal neural measurements to investigate how and why neural codes shift in human visual cortex. Our goal is to uncover the mechanisms behind these dynamic changes and understand their role in visual cognition.