Bin He, Ph.D.

Professor, Department of Biomedical Engineering

E-MAIL: binhe@umn.edu


Research Interests:

Multimodal Functional Neuroimaging: Dr. He and his students have developed a unified theory for multimodal neuroimaging integrating the BOLD functional MRI and electrophysiological imaging. Hemodynamic neuroimaging, such as BOLD functional MRI, has high spatial resolution at mm scale but very slow in time. Electrophysiological neuroimaging has high temporal resolution at ms scale but limited spatial resolution. It has been a major frontier in the functional neuroimaging research to attempt to greatly enhance spatio-temporal resolution by integrating functional MRI with electrophysiological imaging. Dr. He and colleagues have recently developed a rigorous theory on neurovascular coupling, which provides a principled way of integrating BOLD functional MRI signals with electrophysiological signals for event-related paradigms. The theory has been tested in human visual system and revealed a dramatic improvement in performance in imaging human visual information pathways. Dr. He and his students have further developed new algorithms to integrate fMRI and EEG/MEG signals for oscillatory brain activity. Currently both theoretical and experimental studies are actively pursued in Dr. He's lab to further develop the high resolution spatio-temporal functional neuroimaging modality, and to study the sensory, motor and cognitive functions of the brain using EEG/fMRI.


Electrophysiological Neuroimaging: Dr. He and colleagues have made significant contributions to high-resolution electrophysiological neuroimaging aiding neurosurgical planning in epilepsy patients. Due to the limited spatial resolution of scalp EEG, it is widely practiced in clinical settings that invasive intracranial recordings are obtained, by placing electrode sensors directly on the surface of or within the brain, to aid neurosurgical planning in patients with intractable epilepsy or brain tumors. Dr. He and his students have developed an innovative epilepsy source imaging methodology, in which causal interactions among sources are identified and imaged from noninvasive EEG recordings. Such imaging provides high spatial resolution in imaging distributed brain sources within the 3-dimensional brain volume and reveals neural interactions and connectivity embedded in the brain networks. Dr. He and colleagues have further developed an ICA based seizure imaging methodology and conducted a rigorous validation study in a group of epilepsy patients to image epileptogenic brain, and demonstrated high consistence between the imaged seizure sources and the epileptogenic zones determined by well established clinical procedures in the same patients. Active research is currently being pursued to further establish electrophysiological neuroimaging as a noninvasive tool aiding surgical planning in epilepsy patients.


Brain-Computer Interface: Dr. He and his students have made made important contributions to brain-computer interface (BCI) research. This work is aimed at developing novel techniques for effectively decoding the intention of human subjects and controlling external devices which may ultimately benefit patients suffering from neurological disorders. Dr. He and his students have developed a time-frequency-spatial approach to extract the extremely weak signals accompanying the “thought” of a human subject using an array of electrode sensors placed over the scalp. This method takes the “signatures” of each individual subject and uses them for optimal decoding of the intention of the human subject. Dr. He has proposed the concept of electrophysiological neuroimaging based brain computer interface – an idea to estimate “virtual” intracranial signals from the noninvasive EEG recordings for substantially improving the performance of noninvasive EEG based brain computer interface. Dr. He and his colleagues have been aggressively investigating the mechanisms associated with motor imagery based BCI by using advanced neuroimaging techniques to delineate the brain sources accompanying motor imagery. Recently, Dr. He and his students have developed a 3-dimensional continuous brain-computer interface system to allow a human subject to control the flight of a virtual helicopter from EEG.

 


Selected Publications:

(For a comprehensive list of recent publications, refer to PubMed, a service provided by the National Library of Medicine.)

  • Hosseini SAH, Sohrabpour A, He B. Electromagnetic source imaging using simultaneous scalp EEG and intracranial EEG: An emerging tool for interacting with pathological brain networks. Clin Neurophysiol. 2018;129:168-187.
  • Petrichella S, Johnson N, He B. The influence of corticospinal activity on TMS-evoked activity and connectivity in healthy subjects: A TMS-EEG study. PLoS One. 2017 Apr 6;12(4):e0174879.
  • Sohrabpour A, Lu Y, Worrell G, He B. Imaging brain source extent from EEG/MEG by means of an iteratively reweighted edge sparsity minimization (IRES) strategy. Neuroimage. 2016;142:27-42.
  • Wu X, Zhang X, Tian J, Schmitter S, Hanna B, Strupp J, Pfeuffer J, Hamm M, Wang D, Nistler J, He B, Vaughan TJ, Ugurbil K, de Moortele PF. Comparison of RF body coils for MRI at 3 T: a simulation study using parallel transmission on various anatomical targets. NMR Biomed. 2015;28:1332-44.
  • Liu J, Zhang X, Schmitter S, Van de Moortele PF, He B. Gradient-based electrical properties tomography (gEPT): A robust method for mapping electrical properties of biological tissues in vivo using magnetic resonance imaging. Magn Reson Med. 2015;74:634-46.
  • He B, Sohrabpour A. Imaging epileptogenic brain using high density EEG source imaging and MRI. Clin Neurophysiol. 2016;127:5-7.
  • Jamison KW, Roy AV, He S, Engel SA, He B. SSVEP Signatures of Binocular Rivalry During Simultaneous EEG and fMRI. J Neurosci Methods. 2015;243:53-62.
  • Sohrabpour A, Lu Y, Kankirawatana P, Blount J, Kim H, He B. Effect of EEG electrode number on epileptic source localization in pediatric patients. Clin Neurophysiol. 2015;126:472-80.
  • Han C, Pogwizd SM, Yu L, Zhou Z, Killingsworth CR, He B. Imaging cardiac activation sequence during ventricular tachycardia in a canine model of nonischemic heart failure. Am J Physiol Heart Circ Physiol. 2015;308:H108-14.
  • Zhang CH, Lu Y, Brinkmann B, Welker K, Worrell G, He B. Lateralization and localization of epilepsy related hemodynamic foci using presurgical fMRI. Clin Neurophysiol. 2015;126:27-38.
  • Zhang X, Van de Moortele PF, Liu J, Schmitter S, He B. Quantitative prediction of radio frequency induced local heating derived from measured magnetic field maps in magnetic resonance imaging: A phantom validation at 7 T. Appl Phys Lett. 2014;105:244101.
  • Yang L, Worrell G, Nelson C, Brinkmann B, He B. Spectral and spatial shifts of postictal slow waves in temporal lobe seizuresr. Brain. 2012;135(Pt 10):3134-43.
  • Zhang P, Jamison K, Engel S, He B, He S. Binocular rivalry requires visual attention. Neuron, 2011;71:362-9.  
  • Yuan H, Perdoni C, Yang L, He B. Differential electrophysiological coupling for positive and negative BOLD responses during unilateral hand movements. J Neurosci. 2011;31: 9585–9593.
  • Yang L, Wilke C, Brinkmann B, Worrell GA, He B: Dynamic imaging of ictal oscillations using non-invasive high-resolution EEG. NeuroImage. 2011;56:1908-1917. 
  • Lai Y, Zhang, X, van Drongelen, W, Korhman, M, Hecox, K, Ni, Y, He B: Noninvasive cortical imaging of epileptiform activities from interictal spikes in pediatric patients, NeuroImage, 2011;54(1):244-252. 
  • He B, Yang L, Wilke C, Yuan H. Electrophysiological imaging of brain activity and connectivity – Challenges and opportunities. IEEE Trans Biomed Eng. 2011;58:1918-1931. (Cover Article).  

Former Graduate Students:

Audrey Royer (Ph.D. 2011, Neuroscience, University of Minnesota).