Bin He

University of Minnesota Duluth, Duluth, Minnesota, United States

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Publications (286)813.45 Total impact

  • [Show abstract] [Hide abstract]
    ABSTRACT: Ventricular arrhythmias represent one of leading causes for sudden cardiac death, a significant problem in public health. Noninvasive imaging of cardiac electric activities associated with ventricular arrhythmias plays an important role in better our understanding of the mechanisms and optimizing the treatment options. The present study aims to rigorously validate a novel three-dimensional (3-D) cardiac electrical imaging (3-DCEI) technique with the aid of 3-D intra-cardiac mapping during paced rhythm and ventricular tachycardia (VT) in the rabbit heart. Body surface potentials and intramural bipolar electrical recordings were simultaneously measured in a closed-chest condition in thirteen healthy rabbits. Single-site pacing and dual-site pacing were performed from ventricular walls and septum. VTs and premature ventricular complexes (PVCs) were induced by intravenous norepinephrine (NE). The non-invasively imaged activation sequence correlated well with invasively measured counterparts, with a correlation coefficient of 0.72 and a relative error of 0.30 averaged over all paced beats and NE-induced PVCs and VT beats. The averaged distance from imaged site of initial activation to measured site determined from intra-cardiac mapping was ∼5mm. These promising results suggest that 3-DCEI is feasible to non-invasively localize the origins and image activation sequence of focal ventricular arrhythmias.
    Conference proceedings: ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference 08/2011; 2011:1684-7. DOI:10.1109/IEMBS.2011.6090484
  • Ardalan Aarabi, Bin He
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    ABSTRACT: In this study, we report our development of a patient-specific rule-based seizure prediction system. Five univariate and one bivariate nonlinear measures were extracted from non-overlapping 10-second segments of intracranial EEG (iEEG) data recorded using both depth electrodes in the brain and subdural electrodes over the cortical surface. Nonlinear features representing the specific characteristic properties of EEG signal were then integrated spatio-temporally in a way to predict to predict seizure with high sensitivity. The present system was tested on 58 hours of iEEG data containing ten seizures recorded in two patients with medically intractable focal epilepsy. Within a prediction horizon of 30 and 60 minutes, our method showed an average sensitivity of 90% and 96.5% with an average false prediction rate of 0.06/h and 0.055/h, respectively. The present results suggest that such a rule-based system can become potentially a useful approach for predicting seizures prior to onset.
    Conference proceedings: ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference 08/2011; 2011:2566-9. DOI:10.1109/IEMBS.2011.6090709
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    ABSTRACT: Today's brain-computer interfaces (BCIs) record the electrical signal from the cortex and use that signal to control an external device, such as a computer cursor, wheelchair, or neuroprosthetic. Two control strategies used by BCIs, process control and goal selection, differ in the amount of assistance the BCI system provides the user. This paper looks at non-invasive studies that directly compare goal selection to process control. In these studies, the assistance provided by a BCI using goal selection 1) increased the user's performance with the BCI and 2) resulted in an EEG signal that was more conducive to good performance.
    Conference proceedings: ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference 08/2011; 2011:4235-8. DOI:10.1109/IEMBS.2011.6091051
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    ABSTRACT: Electroencephalogram (EEG) is an important component of the pre-surgical evaluation in the treatment of medically intractable epilepsy. However, clinical EEG uses 19 to 32 electrodes that significantly limits its localization ability. Recent development of dense-array recording techniques has suggested that increased spatial sampling rate improves the accuracy of source localization. In the current study, we proposed a 76-channel EEG system for the long-term monitoring of epilepsy patients, and proposed a dynamic seizure imaging (DSI) technique to image the ictal rhythmic activity that may evolve through time, space and frequency. We tested the system in a cohort of 8 patients and our results show that the DSI estimated the seizure activity in good correlation with intracranial recordings, successful surgery outcomes and other clinical evidence. The proposed dense-array recording and DSI imaging approach enable a non-invasive but quantitative imaging of continuous seizure activity. The results suggest that DSI may potentially be useful to assist the pre-surgical evaluation in patients with intractable epilepsy.
    Conference proceedings: ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference 08/2011; 2011:8271-4. DOI:10.1109/IEMBS.2011.6092039
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    ABSTRACT: Being noninvasive, low-risk and inexpensive, EEG is a promising methodology in the application of human Brain Computer Interface (BCI) to help those with motor dysfunctions. Here we employed a center-out task paradigm to study the decoding of hand velocity in the EEG recording. We tested the hypothesis using a linear regression model and found a significant correlation between velocity and the low-pass filtered EEG signal (<2 Hz). The low-pass filtered EEG was not only tuned to the direction but also phase-locked to the amplitude of velocity. This suggests an EEG form of the neuronal population vector theory, which is considered to encode limb kinematic information, and provides a new method of BCI implementation.
    Conference proceedings: ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference 08/2011; 2011:6335-8. DOI:10.1109/IEMBS.2011.6091564
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    ABSTRACT: An interocular conflict arises when different images are presented to each eye at the same spatial location. The visual system resolves this conflict through binocular rivalry: observers consciously perceive spontaneous alternations between the two images. Visual attention is generally important for resolving competition between neural representations. However, given the seemingly spontaneous and automatic nature of binocular rivalry, the role of attention in resolving interocular competition remains unclear. Here we test whether visual attention is necessary to produce rivalry. Using an EEG frequency-tagging method to track cortical representations of the conflicting images, we show that when attention was diverted away, rivalry stopped. The EEG data further suggested that the neural representations of the dichoptic images combined without attention. Thus, attention is necessary for dichoptic images to be engaged in sustained rivalry and may be generally required for resolving conflicting, potentially ambiguous input and giving a single interpretation access to consciousness.
    Neuron 07/2011; 71(2):362-9. DOI:10.1016/j.neuron.2011.05.035 · 15.98 Impact Factor
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    ABSTRACT: It is of importance to image electrical activity and properties of biological tissues. Recently hybrid imaging modality combing ultrasound scanning and source imaging through the acoustoelectric (AE) effect has generated considerable interest. Such modality has the potential to provide high spatial resolution current density imaging by utilizing the pressure-induced AE resistivity change confined at the ultrasound focus. In this study, we investigate a novel three-dimensional (3D) ultrasound current source density imaging approach using unipolar ultrasound pulses. Utilizing specially designed unipolar ultrasound pulses and by combining AE signals associated to the local resistivity changes at the focusing point, we are able to reconstruct the 3D current density distribution with the boundary voltage measurements obtained while performing a 3D ultrasound scan. We have shown in computer simulation that using the present method it is feasible to image with high spatial resolution an arbitrary 3D current density distribution in an inhomogeneous conductive media.
    Physics in Medicine and Biology 07/2011; 56(13):3825-42. DOI:10.1088/0031-9155/56/13/006 · 2.92 Impact Factor
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    ABSTRACT: Localization of the source of cardiac ectopic activity has direct clinical benefits for determining the location of the corresponding ectopic focus. In this study, a recently developed current-density (CD)-based localization approach was experimentally evaluated in noninvasively localizing the origin of the cardiac ectopic activity from body-surface potential maps (BSPMs) in a well-controlled experimental setting. The cardiac ectopic activities were induced in four well-controlled intact pigs by single-site pacing at various sites within the left ventricle (LV). In each pacing study, the origin of the induced ectopic activity was localized by reconstructing the CD distribution on the endocardial surface of the LV from the measured BSPMs and compared with the estimated single moving dipole (SMD) solution and precise pacing site (PS). Over the 60 analyzed beats corresponding to ten pacing sites (six for each), the mean and standard deviation of the distance between the locations of maximum CD value and the corresponding PSs were 16.9 mm and 4.6 mm, respectively. In comparison, the averaged distance between the SMD locations and the corresponding PSs was slightly larger (18.4 ± 3.4 mm). The obtained CD distribution of activated sources extending from the stimulus site also showed high consistency with the endocardial potential maps estimated by a minimally invasive endocardial mapping system. The present experimental results suggest that the CD method is able to locate the approximate site of the origin of a cardiac ectopic activity, and that the distribution of the CD can portray the propagation of early activation of an ectopic beat.
    Physics in Medicine and Biology 07/2011; 56(13):4161-76. DOI:10.1088/0031-9155/56/13/027 · 2.92 Impact Factor
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    ABSTRACT: Unlocking the dynamic inner workings of the brain continues to remain a grand challenge of the 21st century. To this end, functional neuroimaging modalities represent an outstanding approach to better understand the mechanisms of both normal and abnormal brain functions. The ability to image brain function with ever increasing spatial and temporal resolution has made a significant leap over the past several decades. Further delineation of functional networks could lead to improved understanding of brain function in both normal and diseased states. This paper reviews recent advancements and current challenges in dynamic functional neuroimaging techniques, including electrophysiological source imaging, multimodal neuroimaging integrating fMRI with EEG/MEG, and functional connectivity imaging.
    IEEE transactions on bio-medical engineering 07/2011; 58(7):1918-31. DOI:10.1109/TBME.2011.2139210 · 2.23 Impact Factor
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    ABSTRACT: The coupling between neural cellular activity and blood oxygen level-dependent (BOLD) signal is of critical importance to the interpretation of fMRI. Largely unknown, however, is the degree to which different neuronal events (i.e., excitation and inhibition) maintain or disrupt the neural-hemodynamic relationship, especially in humans. In the present study, we compared local electroencephalographic (EEG) oscillations and the positive/negative BOLD responses of simultaneously recorded data from healthy human volunteers performing unilateral finger tapping at graded rates. By quantifying the single-trial modulations of EEG using source imaging, we tested for their correlation with positive BOLD response (PBR) and negative BOLD response (NBR) after coregistering their spatial locations. PBR was found to be overlapped with and correlated to the decrease of alpha (8-13 Hz) and beta (13-30 Hz) band EEG in the contralateral sensorimotor cortex. Regional EEG modulations at the sensorimotor cortex further predicted a spatially distributed and interconnected network of motor-related cortical areas. Alternatively, no significant correlation was found at the ipsilateral sensorimotor cortex between the NBR and EEG despite their spatial overlapping. This differential electrophysiological coupling of the positive and negative BOLD responses suggests that the underlying neuronal events may not only influence the direction of the signal change but also the neural-hemodynamic relationship.
    The Journal of Neuroscience : The Official Journal of the Society for Neuroscience 06/2011; 31(26):9585-93. DOI:10.1523/JNEUROSCI.5312-10.2011 · 6.75 Impact Factor
  • Yakang Dai, Bin He
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    ABSTRACT: eConnectome (electrophysiological Connectome) is an open-source MATLAB software platform with graphical user interfaces for mapping and imaging brain functional connectivity from electrophysiological signals including EEG, ECoG and MEG. We introduce the software platform and report the newly included functionality of MEG connectivity analysis. Simulated and real MEG data were analyzed using the eConnectome. The results indicate the validity of the eConnectome for brain activity and connectivity mapping from MEG data.
    Noninvasive Functional Source Imaging of the Brain and Heart & 2011 8th International Conference on Bioelectromagnetism (NFSI & ICBEM), 2011 8th International Symposium on; 06/2011
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    ABSTRACT: Predominant components in electro- or magneto-encephalography (EEG/MEG) are scalp projections of synchronized neuronal electrical activity distributed over cortical structures. Reconstruction of cortical sources underlying EEG/MEG can thus be achieved with the use of the cortical current density (CCD) model. We have developed a sparse electromagnetic source imaging method based on the CCD model, named as the variation-based cortical current density (VB-SCCD) algorithm, and have shown that it has much enhanced performance in reconstructing extended cortical sources in simulations (Ding 2009 Phys. Med. Biol. 54 2683-97). The present study aims to evaluate the performance of VB-SCCD, for the first time, using experimental data obtained from six participants. The results indicate that the VB-SCCD algorithm is able to successfully reveal spatially distributed cortical sources behind motor potentials induced by visually cued repetitive finger movements, and their dynamic patterns, with millisecond resolution. These findings of motor sources and cortical systems are supported by the physiological knowledge of motor control and evidence from various neuroimaging studies with similar experiments. Furthermore, our present results indicate the improvement of cortical source resolvability of VB-SCCD, as compared with two other classical algorithms. The proposed solver embedded in VB-SCCD is able to handle large-scale computational problems, which makes the use of high-density CCD models possible and, thus, reduces model misspecifications. The present results suggest that VB-SCCD provides high resolution source reconstruction capability and is a promising tool for studying complicated dynamic systems of brain activity for basic neuroscience and clinical neuropsychiatric research.
    Journal of Neural Engineering 06/2011; 8(3):036008. DOI:10.1088/1741-2560/8/3/036008 · 3.42 Impact Factor
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    ABSTRACT: A brain-computer interface (BCI) can be used to accomplish a task without requiring motor output. Two major control strategies used by BCIs during task completion are process control and goal selection. In process control, the user exerts continuous control and independently executes the given task. In goal selection, the user communicates their goal to the BCI and then receives assistance executing the task. A previous study has shown that goal selection is more accurate and faster in use. An unanswered question is, which control strategy is easier to learn? This study directly compares goal selection and process control while learning to use a sensorimotor rhythm-based BCI. Twenty young healthy human subjects were randomly assigned either to a goal selection or a process control-based paradigm for eight sessions. At the end of the study, the best user from each paradigm completed two additional sessions using all paradigms randomly mixed. The results of this study were that goal selection required a shorter training period for increased speed, accuracy, and information transfer over process control. These results held for the best subjects as well as in the general subject population. The demonstrated characteristics of goal selection make it a promising option to increase the utility of BCIs intended for both disabled and able-bodied users.
    Journal of Neural Engineering 06/2011; 8(3):036012. DOI:10.1088/1741-2560/8/3/036012 · 3.42 Impact Factor
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    ABSTRACT: Three-dimensional (3-D) mapping of the ventricular activation is of importance to better understand the mechanisms and facilitate management of ventricular arrhythmias. The goal of this study was to develop and evaluate a 3-D cardiac electrical imaging (3DCEI) approach for imaging myocardial electrical activation from the intracavitary electrograms (EGs) and heart-torso geometry information over the 3-D volume of the heart. The 3DCEI was evaluated in a swine model undergoing intracavitary noncontact mapping (NCM). Each animal's preoperative MRI data were acquired to construct the heart-torso model. NCM was performed with the Ensite 3000 system during acute ventricular pacing. Subsequent 3DCEI analyses were performed on the measured intracavitary EGs. The estimated initial sites (ISs) were compared to the precise pacing locations, and the estimated activation sequences (ASs) and EGs were compared to those recorded by the NCM system over the endocardial surface. In total, six ventricular sites from two pigs were paced. The averaged localization error of IS was 6.7 ± 2.6 mm. The endocardial ASs and EGs as a subset of the estimated 3-D solutions were consistent with those reconstructed from the NCM system. The present results demonstrate that the intracavitary-recording-based 3DCEI approach can well localize the sites of initiation and can obtain physiologically reason able ASs as well as EGs in an in vivo setting under control/paced conditions. This study suggests the feasibility of tomographic imaging of 3-D ventricular activation and 3-D EGs from intracavitary recordings.
    IEEE Transactions on Biomedical Engineering 05/2011; DOI:10.1109/TBME.2010.2097598 · 2.23 Impact Factor
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    ABSTRACT: Magnetoacoustic tomography with magnetic induction (MAT-MI) was recently introduced as a noninvasive electrical conductivity imaging approach with high spatial resolution close to ultrasound imaging. In this study, we test the feasibility of the MAT-MI method for breast tumor imaging using numerical modeling and computer simulation. Using the finite element method, we have built three-dimensional numerical breast models with varieties of embedded tumors for this simulation study. In order to obtain an accurate and stable forward solution that does not have numerical errors caused by singular MAT-MI acoustic sources at conductivity boundaries, we first derive an integral forward method for calculating MAT-MI acoustic sources over the entire imaging volume. An inverse algorithm for reconstructing the MAT-MI acoustic source is also derived with spherical measurement aperture, which simulates a practical setup for breast imaging. With the numerical breast models, we have conducted computer simulations under different imaging parameter setups and all the results suggest that breast tumors that have large conductivity in contrast to the surrounding tissue as reported in the literature may be readily detected in the reconstructed MAT-MI images. In addition, our simulations also suggest that the sensitivity of imaging breast tumors using the presented MAT-MI setup depends more on the tumor location and the conductivity contrast between the tumor and its surrounding tissue than on the tumor size.
    Physics in Medicine and Biology 03/2011; 56(7):1967-83. DOI:10.1088/0031-9155/56/7/004 · 2.92 Impact Factor
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    ABSTRACT: Imaging cardiac excitation within ventricular myocardium is important in the treatment of cardiac arrhythmias and might help improve our understanding of arrhythmia mechanisms. This study sought to rigorously assess the imaging performance of a 3-dimensional (3D) cardiac electrical imaging (3DCEI) technique with the aid of 3D intracardiac mapping from up to 216 intramural sites during paced rhythm and norepinephrine (NE)-induced ventricular tachycardia (VT) in the rabbit heart. Body surface potentials and intramural bipolar electrical recordings were simultaneously measured in a closed-chest condition in 13 healthy rabbits. Single-site pacing and dual-site pacing were performed from ventricular walls and septum. VTs and premature ventricular complexes (PVCs) were induced by intravenous NE. Computed tomography images were obtained to construct geometry models. The noninvasively imaged activation sequence correlated well with invasively measured counterpart, with a correlation coefficient of 0.72 ± 0.04, and a relative error of 0.30 ± 0.02 averaged over 520 paced beats as well as 73 NE-induced PVCs and VT beats. All PVCs and VT beats initiated in the subendocardium by a nonreentrant mechanism. The averaged distance from the imaged site of initial activation to the pacing site or site of arrhythmias determined from intracardiac mapping was ∼5 mm. For dual-site pacing, the double origins were identified when they were located at contralateral sides of ventricles or at the lateral wall and the apex. 3DCEI can noninvasively delineate important features of focal or multifocal ventricular excitation. It offers the potential to aid in localizing the origins and imaging activation sequences of ventricular arrhythmias, and to provide noninvasive assessment of the underlying arrhythmia mechanisms.
    Heart rhythm: the official journal of the Heart Rhythm Society 03/2011; 8(8):1266-72. DOI:10.1016/j.hrthm.2011.03.014 · 4.92 Impact Factor
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    ABSTRACT: Scalp electroencephalography (EEG) has been established as a major component of the pre-surgical evaluation for epilepsy surgery. However, its ability to localize seizure onset zones (SOZ) has been significantly restricted by its low spatial resolution and indirect correlation with underlying brain activities. Here we report a novel non-invasive dynamic seizure imaging (DSI) approach based upon high-density EEG recordings. This novel approach was particularly designed to image the dynamic changes of ictal rhythmic discharges that evolve through time, space and frequency. This method was evaluated in a group of 8 epilepsy patients and results were rigorously validated using intracranial EEG (iEEG) (n=3) and surgical outcome (n=7). The DSI localized the ictal activity in concordance with surgically resected zones and ictal iEEG recordings in the cohort of patients. The present promising results support the ability to precisely and accurately image dynamic seizure activity from non-invasive measurements. The successful establishment of such a non-invasive seizure imaging modality for surgical evaluation will have a significant impact in the management of medically intractable epilepsy.
    NeuroImage 03/2011; 56(4):1908-17. DOI:10.1016/j.neuroimage.2011.03.043 · 6.13 Impact Factor
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    Chenguang Liu, Bin He
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    ABSTRACT: A new algorithm for 3-D imaging of the activation sequence from noninvasive body surface potentials is proposed. After formulating the nonlinear relationship between the 3-D activation sequence and the body surface recordings during activation, the extended Kalman filter (EKF) is utilized to estimate the activation sequence in a recursive way. The state vector containing the activation sequence is optimized during iteration by updating the error variance/covariance matrix. A new regularization scheme is incorporated into the "predict" procedure of EKF to tackle the ill-posedness of the inverse problem. The EKF-based algorithm shows good performance in simulation under single-site pacing. Between the estimated activation sequences and true values, the average correlation coefficient (CC) is 0.95, and the relative error (RE) is 0.13. The average localization error (LE) when localizing the pacing site is 3.0 mm. Good results are also obtained under dual-site pacing (CC = 0.93, RE = 0.16, and LE = 4.3 mm). Furthermore, the algorithm shows robustness to noise. The present promising results demonstrate that the proposed EKF-based inverse approach can noninvasively estimate the 3-D activation sequence with good accuracy and the new algorithm shows good features due to the application of EKF.
    IEEE transactions on bio-medical engineering 03/2011; 58(3):541-9. DOI:10.1109/TBME.2010.2066564 · 2.23 Impact Factor
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    ABSTRACT: We have developed a MATLAB-based toolbox, eConnectome (electrophysiological connectome), for mapping and imaging functional connectivity at both the scalp and cortical levels from the electroencephalogram (EEG), as well as from the electrocorticogram (ECoG). Graphical user interfaces were designed for interactive and intuitive use of the toolbox. Major functions of eConnectome include EEG/ECoG preprocessing, scalp spatial mapping, cortical source estimation, connectivity analysis, and visualization. Granger causality measures such as directed transfer function and adaptive directed transfer function were implemented to estimate the directional interactions of brain functional networks, over the scalp and cortical sensor spaces. Cortical current density inverse imaging was implemented using a generic realistic geometry brain-head model from scalp EEGs. Granger causality could be further estimated over the cortical source domain from the inversely reconstructed cortical source signals as derived from the scalp EEG. Users may implement other connectivity estimators in the framework of eConnectome for various applications. The toolbox package is open-source and freely available at under the GNU general public license for noncommercial and academic uses.
    Journal of neuroscience methods 02/2011; 195(2):261-9. DOI:10.1016/j.jneumeth.2010.11.015 · 1.96 Impact Factor
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    ABSTRACT: Magnetoacoustic tomography with magnetic induction (MAT-MI) is an imaging technique under development to achieve imaging of electrical impedance contrast in biological tissues with spatial resolution close to ultrasound imaging. However, previously reported MAT-MI experimental results are obtained either from low salinity gel phantoms, or from normal animal tissue samples. In this study, we report the experimental study on the performance of the MAT-MI imaging method for imaging in vitro human liver tumor tissue. The present promising experimental results suggest the feasibility of MAT-MI to image electrical impedance contrast between the cancerous tissue and its surrounding normal tissues.
    Applied Physics Letters 01/2011; 98(2):23703. DOI:10.1063/1.3543630 · 3.52 Impact Factor

Publication Stats

4k Citations
813.45 Total Impact Points


  • 1970–2015
    • University of Minnesota Duluth
      • Department of Psychology
      Duluth, Minnesota, United States
  • 2012
    • Southeast University (China)
      Nan-ching-hsü, Jiangxi Sheng, China
  • 2011
    • Mayo Clinic - Rochester
      • Department of Neurology
      Рочестер, Minnesota, United States
  • 1995–2011
    • University of Illinois at Chicago
      • • Department of Bioengineering
      • • Department of Electrical and Computer Engineering
      Chicago, Illinois, United States
  • 2008
    • Illinois Institute of Technology
      Chicago, Illinois, United States
  • 2004–2008
    • Zhejiang University
      • College of Electrical Engineering
      Hangzhou, Zhejiang Sheng, China
  • 2007
    • Jiangsu Polytechnic university
      Wujin, Jiangsu Sheng, China
  • 2004–2007
    • Niigata University
      • Department of Biocybernetics
      Niahi-niigata, Niigata, Japan
  • 2005
    • Institute of Electrical & Electronics Engineers
      Saint Paul, Minnesota, United States
    • Sapienza University of Rome
      • Department of Computer Science
      Roma, Latium, Italy
  • 2002
    • University of Chicago
      Chicago, Illinois, United States