research
some topics of interest I have been working on
Perceptual Organization
I am interested in answering how the brain transforms fragmented retinal inputs into a coherent representation of reality. My research explores the neural mechanisms behind perceptual organization—specifically, how the visual system groups discrete sensory elements into unified objects based on statistical regularities like “common fate”. I aim to uncover the specific inference processes that allow the brain to decide which local signals belong together and which should be segregated as distinct figures against a background.
Motion Segmentation
A central question in my research is how the visual system parses complex dynamic scenes into distinct entities based on differences in velocity. I am particularly focused on understanding how the brain overcomes the physical constraints of receptive fields—the “spatial bottleneck”—to solve the challenge of transparent motion. My goal is to determine the mechanistic rules that dictate whether local motion signals are integrated into a single global flow or preserved as separate, independent surfaces.
Direction Repulsion
I am interested in answering how the visual system employs computational strategies to ensure robust segmentation. Specifically, I investigate how mechanisms like direction repulsion exaggerate the angular difference between overlapping signals to reduce ambiguity. My research seeks to explain how neural populations avoid simply averaging conflicting signals and instead “push” perceived directions apart to ensure that distinct objects remain clearly segregated in the final percept.
Cortico-cortical Interaction for Stable Perception
Finally, I aim to understand how dynamic, recurrent communication between hierarchical brain areas generates a stable visual percept. I am interested in answering how feedback and synergistic interactions between early areas (encoding high-resolution details) and higher areas (encoding global context) resolve sensory noise. My research explores how these resonant circuits refine neural representations over time to maintain a coherent interpretation of the world, even when the input is ambiguous.