The Brain Representations Lab studies how the human brain transforms visual input into meaningful perception. Every moment, the eyes deliver a rich and rapidly changing stream of information to the brain. Yet seeing is not simply a matter of registering shapes, colors, and motion: visual experience depends on how the brain organizes this information, connects it to meaning, and adapts it to our current needs and state.

We investigate the neural representations that support human vision: how visual information is encoded in the brain, how these codes change over time, and how they are shaped by internal states such as attention, arousal, and alertness. A central focus of our work is the dynamic nature of neural representations. Rather than assuming that the same image always produces the same pattern of brain activity, we ask how and why visual codes may drift over time, and what these changes mean for perception and behavior.

Our research uses large-scale, open fMRI datasets (and some electrophysiology datasets as well), which we analyze with data-driven methods, computational modeling, and simulations. We also conduct behavioral and psychophysics experiments with concurrent eye-tracking and pupillometry in our lab. By combining these approaches, we aim to uncover the principles that govern visual representations in the brain and understand how their stability, flexibility, and moment-to-moment dynamics enable us to see and make sense of the world.