Bin He, PhD
Carnegie Mellon University
Trustee Professor of Biomedical Engineering
Title: Dynamic Brain Imaging and Brain-Computer Interface
Abstract: Mapping the spatio-temporal distribution of brain activation with high spatial and temporal resolution is crucial for understanding the brain and aiding in the clinical diagnosis and management of brain disorders. We will discuss our recent work on estimating and imaging of dynamic brain source distributions from high-density EEG/MEG, leveraging ML/AI and computational neural mass models. We will demonstrate its application in imaging dynamic epileptic brains, validated against invasive intracranial EEG recordings and surgical resection outcomes. We will also discuss the principles and state-of-the-art advancements in brain-computer interfaces using noninvasive EEG. Through novel machine learning algorithms, we showcase the decoding of human “intention,” enabling individuals to control the flight of a drone and a robotic arm through mere thought, as recorded by and decoded from noninvasive EEG signals. Our recent study also highlights the potential of transcranial focused ultrasound neuromodulation to further enhance the performance of EEG brain-computer interfaces.
Bio: Bin He is a Trustee Professor of Biomedical Engineering at Carnegie Mellon University. His current research interests lie in neuroengineering, encompassing electrophysiological source imaging, brain-computer interface, and neuromodulation. He serves as the Editor of the textbook “Neural Engineering,” initially published in 2005 and updated to its 3rd edition in 2020. He is a Fellow of the National Academy of Inventors, the International Academy of Medical and Biological Engineering (IAMBE), IEEE, AIMBE, and BMES. He serves as the Editor-in-Chief of the IEEE Reviews in Biomedical Engineering and has previously held leadership positions as the Past President of IEEE Engineering in Medicine and Biology Society and as the Past Chair of IAMBE.