We investigate how distributed brain activity gives rise to cognition and behavior, build transferable models of brain signals, and connect these insights to adaptive AI and real-time interaction with the brain.
Large-scale brain network modeling, neural decoding, naturalistic neuroscience, and individual differences.
General-purpose representations for fMRI, EEG, and multimodal signals through self-supervised and transferable learning.
Neural principles for continual learning, compositionality, efficient attention, and adaptive computation.
BCI, real-time decoding, neurofeedback, and neuromodulation to examine changes in neural activity and behavior.
The approaches below connect these four research directions.