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Neural Systems Engineering and Information Processing Lab
"Our laboratory develops neurotechnology and studies the brain through data-driven modeling, decoding and control of neural dynamics. To do so, we work at the interface of machine learning, statistical signal processing, and control theory to develop algorithmic solutions for problems in basic and clinical neuroscience that involve the collection and modulation of neural signals. Our work combines algorithm development with in vivo experimental implementation and testing, and is conducted in close collaboration with a variety of experimental labs. Our lab has developed brain-machine interfaces to restore lost emotional function in mental disorders and lost motor function in neurological injuries and diseases. Some specific problems of interest include dynamical modeling of high-dimensional multiscale brain data, decoding of cognitive, motor, or mood states from neural signals, and developing closed-loop controllers for neural activity patterns such as closed-loop deep brain stimulation systems. These closed-loop neurotechnologies can enable personalized therapies for a wide range of neurological and neuropsychiatric disorders."