Neuroscience

Na Ji’s research bridges neuroscience and optical physics, advancing structural and functional imaging of live brains by developing microscopy tools utilizing adaptive optics, Bessel beams, infinity mirrors, and machine learning. These innovations enable high-throughput, deep-brain imaging of synaptic activity and action potentials across hundreds of neurons. Her lab uses these methods to uncover new insights into visual processing in mice and collaborates widely across multiple disciplines including basic and translational neuroscience, plant biology, and material research and engineering.

My research focuses on understanding the neural mechanisms that support natural behaviors, including navigation, social interaction, communication, and movement. To address these questions, my lab uses bats, whose extraordinary behavioral abilities allow rigorous studies of brain function under natural conditions. We develop and apply cutting-edge technologies for recording and analyzing neural circuits in freely behaving and flying animals. By combining neuroscience, engineering, ethology, and computation, our work aims to uncover how the brain generates flexible, adaptive behavior in the...

Paul Selvin does advance fluorescence microscopy, with ultimate sensitivity (down to a single molecule level) and with super-resolution (down to a nanometer). He looks at molecular motors which move around inside of a cell and transport things; he also works in neuroscience, trying to understand what a memory is, where it is stored, why it disappears, and diseases which afflict us.

Host: Ehud Isacoff
Home Institution: University of Illinois, Urbana-Champaign

Neural network models have revolutionized artificial intelligence, yet the mathematical foundations of their success remain unclear. My research investigates the learning dynamics of neural networks to understand how inductive biases emerge through training and how networks extract meaningful representations from data. Integrating insights from statistics, physics, and neuroscience, I aim to uncover fundamental mathematical principles governing learning in both artificial and natural intelligence.