Biomedical subjects

Bin He

Publications and source records attributed to Bin He.

At least 19 recordsLinked to original sources

PubMed2026

Precisely designed keystone metabolites boost shrimp disease resistance by recruiting symbionts via the lipoxin A4-AP-1 pathway.

BACKGROUND: Gut metabolites and symbionts are indispensable for host health, yet the precise identification of keystone metabolites and construction of synthetic microbial communities (SynComs) to enhance disease resistance remains limited. RESULTS: Using Litopenaeus vannamei as a model, we identified pyruvic acid and DL-glutamine (1:2) as keystone metabolites by borrowing the microbial ecology principles of bio-indicators and driver taxa. Dietary supplementation with these metabolites sufficiently protected shrimp from white feces syndrome (WFS). Multi-omics analyses demonstrated that keystone metabolites exerted positive effects by enriching beneficial Ruegeria lacuscaerulensis, Bacillus subtilis and Nioella nitratireducens, strengthening the gut network stability, and enhancing shrimp immunity, which collectively potentiated WFS resistance. The recruited three strains were consumers and producers of the two keystone metabolites, and discriminative strains between healthy and diseased shrimp across global datasets. A SynCom constructed from the three strains (4:3:2) replicated the efficacy of keystone metabolites. Both keystone metabolites and SynCom elevated shrimp gut and hepatopancreas lipoxin A4 (LXA4) levels, which suppressed the pro-inflammatory transcription factor AP-1, as validated by in vivo inhibition assay. CONCLUSIONS: Our findings demonstrate that precisely designed keystone metabolites enhance shrimp disease resistance through the recruitment of key symbionts-LXA4-AP-1 axis. The rationally designed keystone metabolites and SynCom are compelling biocontrol solutions in improving host disease resistance. Video Abstract.

Animals↗

PubMed2007

Comparison of different cortical connectivity estimators for high-resolution EEG recordings.

The aim of this work is to characterize quantitatively the performance of a body of techniques in the frequency domain for the estimation of cortical connectivity from high-resolution EEG recordings in different operative conditions commonly encountered in practice. Connectivity pattern estimators investigated are the Directed Transfer Function (DTF), its modification known as direct DTF (dDTF) and the Partial Directed Coherence (PDC). Predefined patterns of cortical connectivity were simulated and then retrieved by the application of the DTF, dDTF, and PDC methods. Signal-to-noise ratio (SNR) and length (LENGTH) of EEG epochs were studied as factors affecting the reconstruction of the imposed connectivity patterns. Reconstruction quality and error rate in estimated connectivity patterns were evaluated by means of some indexes of quality for the reconstructed connectivity pattern. The error functions were statistically analyzed with analysis of variance (ANOVA). The whole methodology was then applied to high-resolution EEG data recorded during the well-known Stroop paradigm. Simulations indicated that all three methods correctly estimated the simulated connectivity patterns under reasonable conditions. However, performance of the methods differed somewhat as a function of SNR and LENGTH factors. The methods were generally equivalent when applied to the Stroop data. In general, the amount of available EEG affected the accuracy of connectivity pattern estimations. Analysis of 27 s of nonconsecutive recordings with an SNR of 3 or more ensured that the connectivity pattern could be accurately recovered with an error below 7% for the PDC and 5% for the DTF. In conclusion, functional connectivity patterns of cortical activity can be effectively estimated under general conditions met in most EEG recordings by combining high-resolution EEG techniques, linear inverse estimation of the cortical activity, and frequency domain multivariate methods such as PDC, DTF, and dDTF.

Analysis of Variance↗

PubMed2007

Human herpesvirus 8: serovprevalence and correlates in tumor patients from Xinjiang, China.

Human herpesvirus 8 (HHV-8), also known as Kaposi's sarcoma-associated herpesvirus, is etiologically associated with Kaposi's sarcoma and other lymphoproliferative diseases. Although HHV-8 prevalence exhibits considerable variation in different geographic regions and populations, the incidence of Kaposi's sarcoma appear to increase in areas with a high prevalence rate. In this study, an enzyme-linked immunosorbent assay based on mixed antigens of HHV-8 ORF(73), ORF(65), and K8.1 in the antigenic region was established and used to determine viral prevalence estimates and risk factors associated with HHV-8 infection. Of 482 tumor patients studied, the overall seropositivity of HHV-8 was 25.5%. Notably, Han people, who were immigrants or descendents of immigrants from inland of China, exhibited 26.4% seropositivity. This is similar to that observed in Uygur people, a local ethnic group with a high prevalence of HHV-8 infection and incidence of Kaposi's sarcoma. While there was no significant difference in patients with different tumors, HHV-8 seroprevalence was higher in individuals with malignant diseases. Logistic regression analysis suggests that the age is a risk factor associated with HHV-8 infection, with prevalence increasing from 12.5% under 20-27.5% above 50. These results suggest that unlike other parts of mainland of China, Xinjiang is an area with a high prevalence of HHV-8 infection.

Adolescent↗

PubMed2006

Ictal source analysis: localization and imaging of causal interactions in humans.

We propose a new integrative approach to characterize the structure of seizures in the space, time, and frequency domains. Such characterization leads to a new technical development of ictal source analysis for the presurgical evaluation of epilepsy patients. The present new ictal source analysis method consists of three parts. First, a three-dimensional source scanning procedure is performed by a spatio-temporal FINE source localization method to locate the multiple sources responsible for the time evolving ictal rhythms at their onsets. Next, the dynamic behavior of the sources is modeled by a multivariate autoregressive process (MVAR). Lastly, the causal interaction patterns among the sources as a function of frequency are estimated from the MVAR modeling of the source temporal dynamics. The causal interaction patterns indicate the dynamic communications between sources, which are useful in distinguishing the primary sources responsible for the ictal onset from the secondary sources caused by the ictal propagation. The present ictal analysis strategy has been applied to a number of seizures from five epilepsy patients, and their results are consistent with observations from either MRI lesions or SPECT scans, which indicate its effectiveness. Each step of the ictal source analysis is statistically evaluated in order to guarantee the confidence in the results.

Brain↗

PubMed2006

Spatial resolution of EEG cortical source imaging revealed by localization of retinotopic organization in human primary visual cortex.

The aim of the present study is to investigate the spatial resolution of electroencephalography (EEG) cortical source imaging by localizing the retinotopic organization in the human primary visual cortex (V1). Retinotopic characteristics in V1 obtained from functional magnetic resonance imaging (fMRI) study were used as reference to assess the spatial resolution of EEG since fMRI can discriminate small changes in activation in visual field. It is well known that the activation of the early C1 component in the visual evoked potential (VEP) elicited by pattern onset stimuli coincides well with the activation in the striate cortex localized by fMRI. In the present experiments, we moved small circular checkerboard stimuli along horizontal meridian and compared the activations localized by EEG cortical source imaging with those from fMRI. Both fMRI and EEG cortical source imaging identified spatially correlated activity within V1 in each subject studied. The mean location error, between the fMRI-determined activation centers in V1 and the EEG source imaging activation peak estimated at equivalent C1 components (peak latency: 74.8+/-10.6 ms), was 7 mm (25% and 75% percentiles are 6.45 mm and 8.4 mm, respectively), which is less than the change in fMRI activation map by a 3 degrees visual field change (7.8 mm). Moreover, the source estimates at the earliest major VEP component showed statistically good correlation with those obtained by fMRI. The present results suggest that the spatial resolution of the EEG cortical source imaging can correctly discriminate cortical activation changes in V1 corresponding to less than 3 degrees visual field changes.

Adult↗

PubMed2006

The VP35 protein of Ebola virus inhibits the antiviral effect mediated by double-stranded RNA-dependent protein kinase PKR.

The VP35 protein of Ebola virus is a viral antagonist of interferon. It acts to block virus or double-stranded RNA-mediated activation of interferon regulatory factor 3, a transcription factor that facilitates the expression of interferon and interferon-stimulated genes. In this report, we show that the VP35 protein is also able to inhibit the antiviral response induced by alpha interferon. This depends on the VP35 function that interferes with the pathway regulated by double-stranded RNA-dependent protein kinase PKR. When expressed in a heterologous system, the VP35 protein enhanced viral polypeptide synthesis and growth in Vero cells pretreated with alpha/beta interferon, displaying an interferon-resistant phenotype. In correlation, phosphorylation of PKR and eIF-2alpha was suppressed in cells expressing the VP35 protein. This activity of the VP35 protein was required for efficient viral replication in PKR+/+ but not PKR-/- mouse embryo fibroblasts. Furthermore, VP35 appears to be a RNA binding protein. Notably, a deletion of amino acids 1 to 200, but not R312A substitution in the RNA binding motif, abolished the ability of the VP35 protein to confer viral resistance to interferon. However, the R312A substitution rendered the VP35 protein unable to inhibit the induction of the beta interferon promoter mediated by virus infection. Together, these results show that the VP35 protein targets multiple pathways of the interferon system.

Animals↗

PubMed2006

Comparison of conventional, model-based quantitative planar, and quantitative SPECT image processing methods for organ activity estimation using In-111 agents.

Accurate quantification of organ radionuclide uptake is important for patient-specific dosimetry. The quantitative accuracy from conventional conjugate view methods is limited by overlap of projections from different organs and background activity, and attenuation and scatter. In this work, we propose and validate a quantitative planar (QPlanar) processing method based on maximum likelihood (ML) estimation of organ activities using 3D organ VOIs and a projector that models the image degrading effects. Both a physical phantom experiment and Monte Carlo simulation (MCS) studies were used to evaluate the new method. In these studies, the accuracies and precisions of organ activity estimates for the QPlanar method were compared with those from conventional planar (CPlanar) processing methods with various corrections for scatter, attenuation and organ overlap, and a quantitative SPECT (QSPECT) processing method. Experimental planar and SPECT projections and registered CT data from an RSD Torso phantom were obtained using a GE Millenium VH/Hawkeye system. The MCS data were obtained from the 3D NCAT phantom with organ activity distributions that modelled the uptake of (111)In ibritumomab tiuxetan. The simulations were performed using parameters appropriate for the same system used in the RSD torso phantom experiment. The organ activity estimates obtained from the CPlanar, QPlanar and QSPECT methods from both experiments were compared. From the results of the MCS experiment, even with ideal organ overlap correction and background subtraction, CPlanar methods provided limited quantitative accuracy. The QPlanar method with accurate modelling of the physical factors increased the quantitative accuracy at the cost of requiring estimates of the organ VOIs in 3D. The accuracy of QPlanar approached that of QSPECT, but required much less acquisition and computation time. Similar results were obtained from the physical phantom experiment. We conclude that the QPlanar method, based on 3D organ VOIs and accurate models of the projection process, provided a substantial increase in accuracy of organ activity estimates from planar images compared to CPlanar processing and had accuracy approaching that of QSPECT.

Algorithms↗

PubMed2006

3D source localization of interictal spikes in epilepsy patients with MRI lesions.

The present study aims to accurately localize epileptogenic regions which are responsible for epileptic activities in epilepsy patients by means of a new subspace source localization approach, i.e. first principle vectors (FINE), using scalp EEG recordings. Computer simulations were first performed to assess source localization accuracy of FINE in the clinical electrode set-up. The source localization results from FINE were compared with the results from a classic subspace source localization approach, i.e. MUSIC, and their differences were tested statistically using the paired t-test. Other factors influencing the source localization accuracy were assessed statistically by ANOVA. The interictal epileptiform spike data from three adult epilepsy patients with medically intractable partial epilepsy and well-defined symptomatic MRI lesions were then studied using both FINE and MUSIC. The comparison between the electrical sources estimated by the subspace source localization approaches and MRI lesions was made through the coregistration between the EEG recordings and MRI scans. The accuracy of estimations made by FINE and MUSIC was also evaluated and compared by R(2) statistic, which was used to indicate the goodness-of-fit of the estimated sources to the scalp EEG recordings. The three-concentric-spheres head volume conductor model was built for each patient with three spheres of different radii which takes the individual head size and skull thickness into consideration. The results from computer simulations indicate that the improvement of source spatial resolvability and localization accuracy of FINE as compared with MUSIC is significant when simulated sources are closely spaced, deep, or signal-to-noise ratio is low in a clinical electrode set-up. The interictal electrical generators estimated by FINE and MUSIC are in concordance with the patients' structural abnormality, i.e. MRI lesions, in all three patients. The higher R(2) values achieved by FINE than MUSIC indicate that FINE provides a more satisfactory fitting of the scalp potential measurements than MUSIC in all patients. The present results suggest that FINE provides a useful brain source imaging technique, from clinical EEG recordings, for identifying and localizing epileptogenic regions in epilepsy patients with focal partial seizures. The present study may lead to the establishment of a high-resolution source localization technique from scalp-recorded EEGs for aiding presurgical planning in epilepsy patients.

Action Potentials↗

PubMed2006

Effects of fMRI-EEG mismatches in cortical current density estimation integrating fMRI and EEG: a simulation study.

OBJECTIVE: Multimodal functional neuroimaging by combining functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) has been studied to achieve high-resolution reconstruction of the spatiotemporal cortical current density (CCD) distribution. However, mismatches between these two imaging modalities may occur due to their different underlying mechanisms. The aim of the present study is to investigate the effects of different types of fMRI-EEG mismatches, including fMRI invisible sources, fMRI extra regions and fMRI displacement, on the fMRI-constrained cortical imaging in a computer simulation based on realistic-geometry boundary-element-method (BEM) model. METHODS: Two methods have been adopted to integrate the synthetic fMRI and EEG data for CCD imaging. In addition to the well-known 90% fMRI-constrained Wiener filter approach (Liu AK, Belliveau JW, Dale AM. PNAS 1998;95:8945-8950.), we propose a novel two-step algorithm (referred to as 'Twomey algorithm') for fMRI-EEG integration. In the first step, a 'hard' spatial prior derived from fMRI is imposed to solve the EEG inverse problem with a reduced source space; in the second step, the fMRI constraint is removed and the source estimate from the first step is re-entered as the initial guess of the desired solution into an EEG least squares fitting procedure with Twomey regularization. Twomey regularization is a modified Tikhonov technique that attempts to simultaneously minimize the distance between the desired solution and the initial estimate, and the residual errors of fitness to EEG data. The performance of the proposed Twomey algorithm has been evaluated both qualitatively and quantitatively along with the lead-field normalized minimum norm (WMN) and the 90% fMRI-weighted Wiener filter approach, under repeated and randomized source configurations. Point spread function (PSF) and localization error (LE) are used to measure the performance of different imaging approaches with or without a variety of fMRI-EEG mismatches. RESULTS: The results of the simulation show that the Twomey algorithm can successfully reduce the PSF of fMRI invisible sources compared to the Wiener estimation, without losing the merit of having much lower PSF of fMRI visible sources relative to the WMN solution. In addition, the existence of fMRI extra sources does not significantly affect the accuracy of the fMRI-EEG integrated CCD estimation for both the Wiener filter method and the proposed Twomey algorithm, while the Twomey algorithm may further reduce the chance of occurring spurious sources in the extra fMRI regions. The fMRI displacement away from the electrical source causes enlarged localization error in the imaging results of both the Twomey and Wiener approaches, while Twomey gives smaller LE than Wiener with the fMRI displacement ranging from 1-2 cm. With less than 2 cm fMRI displacement, the LEs for the Twomey and Wiener approaches are still smaller than in the WMN solution. CONCLUSIONS: The present study suggests that the presence of fMRI invisible sources is the most problematic factor responsible for the error of fMRI-EEG integrated imaging based on the Wiener filter approach, whereas this approach is relatively robust against the fMRI extra regions and small displacement between fMRI activation and electrical current sources. While maintaining the above advantages possessed by the Wiener filter approach, the Twomey algorithm can further effectively alleviate the underestimation of fMRI invisible sources, suppress fMRI spurious sources and improve the robustness against fMRI displacement. Therefore, the Twomey algorithm is expected to improve the reliability of multimodal cortical source imaging against fMRI-EEG mismatches. SIGNIFICANCE: The proposed method promises to provide a useful alternative for multimodal neuroimaging integrating fMRI and EEG.

Analysis of Variance↗

PubMed2006

A new magnetic resonance electrical impedance tomography (MREIT) algorithm: the RSM-MREIT algorithm with applications to estimation of human head conductivity.

We have developed a new magnetic resonance electrical impedance tomography (MREIT) algorithm, the RSM-MREIT algorithm, for noninvasive imaging of the electrical conductivity distribution using only one component of magnetic flux density. The proposed RSM-MREIT algorithm uses the response surface methodology (RSM) algorithm for optimizing the conductivity distribution through minimizing the errors between the measured and calculated magnetic flux densities. A series of computer simulations has been conducted to assess the performance of the proposed RSM-MREIT algorithm to estimate electrical conductivity values of the scalp, the skull and the brain tissue, in a three-shell piecewise homogeneous head model. Computer simulation studies were conducted in both a spherical and realistic-geometry head model with a single variable (the brain-to-skull conductivity ratio) and three variables (the conductivity of the brain, the skull, and the scalp). The relative error between the target and estimated head conductivity values was less than 12% for both the single-variable and three-variable simulations. These promising simulation results demonstrate the feasibility of the proposed RSM-MREIT algorithm in estimating electrical conductivity values in a piecewise homogeneous head model of the human head, and suggest that the RSM-MREIT algorithm merits further investigation.

Algorithms↗

PubMed2006

Biodegradable heparin-loaded microspheres: carrier molecular composition and microsphere structure.

Microspheres of amphiphilic triblock polymers PLLA-PEG-PLLA were investigated as carriers for heparin delivery. Two series of PLLA-PEG-PLLA triblock were synthesized and prepared into microspheres with heparin loaded. The microspheres were hollow and the surface morphology varied from smooth to porous. The pore size increased with increasing PEG content. The microsphere size distribution showed that higher PEG content increased the average microsphere size. The release rate of heparin was closely related to the surface morphology of the microspheres. DSC spectra showed that both cold crystalline temperature (Tc) and crystalline melting temperature (Tm) of heparin-loaded microspheres were related to the copolymer composition and the Tc was lower than those of corresponding pure microspheres. [IMAGES: SEE TEXT]

Anticoagulants↗

PubMed2006

Functional cortical source imaging from simultaneously recorded ERP and fMRI.

Feasibility of continuously and simultaneously recording visual evoked potentials (VEPs) with fMRI was assessed by quantitatively comparing cortical source images by means of receiver operating characteristic (ROC) curve analysis. The averaged EEG source images coincided well with simultaneously acquired fMRI activations. Strong correlation was found between the cortical source images of VEPs recorded inside and outside the scanner. Application of fMRI prior information strengthened correlation between estimated source images as well as resulted in source estimates with higher spatial resolution. The present results demonstrate that reliable cortical source images can be acquired during simultaneous fMRI scanning and they may be used for multimodal functional source imaging studies.

Adult↗

PubMed2006

A cortical potential imaging study from simultaneous extra- and intracranial electrical recordings by means of the finite element method.

In the present study, we have validated the cortical potential imaging (CPI) technique for estimating cortical potentials from scalp EEG using simultaneously recorded electrocorticogram (ECoG) in the presence of strong local inhomogeneity, i.e., Silastic ECoG grid(s). The finite element method (FEM) was used to model the realistic postoperative head volume conductor, which includes the scalp, skull, cerebrospinal fluid (CSF) and brain, as well as the Silastic ECoG grid(s) implanted during the surgical evaluation in epilepsy patients, from the co-registered magnetic resonance (MR) and computer tomography (CT) images. A series of computer simulations were conducted to evaluate the present FEM-based CPI technique and to assess the effect of the Silastic ECoG grid on the scalp EEG forward solutions. The present simulation results show that the Silastic ECoG grid has substantial influence on the scalp potential forward solution due to the distortion of current pathways in the presence of the extremely low conductive materials. On the other hand, its influence on the estimated cortical potential distribution is much less than that on the scalp potential distribution. With appropriate numerical modeling and inverse estimation techniques, we have demonstrated the feasibility of estimating the cortical potentials from the scalp EEG with the implanted Silastic ECoG gird(s), in both computer simulations and in human experimentation. In an epilepsy patient undergoing surgical evaluation, the cortical potentials were reconstructed from the simultaneously recorded scalp EEG, in which main features of spatial patterns during interictal spike were preserved and over 0.75 correlation coefficient value was obtained between the recorded and estimated cortical potentials. The FEM-based CPI technique provides a means of connecting the simultaneous recorded ECoG and the scalp EEG and promises to become an effective tool to evaluate and validate CPI techniques using clinic data.

Algorithms↗

PubMed2006

Three-dimensional myocardial activation imaging in a rabbit model.

This study evaluated a recently developed three-dimensional (3-D) electrocardiographic imaging (3DECI) approach in a closed-chest rabbit model. First, the performance and sensitivity of parameters of 3DECI were evaluated using a geometrically realistic rabbit heart-torso model. Second, a 3-D intracardiac mapping procedure was evaluated based on the heart-torso rabbit model. Third, comparisons were made among the forward-simulated ventricular activation sequence, the activation sequence derived by the intracardiac mapping, and the 3DECI inverse solution. Finally, the present procedures were tested in vivo in a rabbit, in which the relative error between the measured and imaged activation sequence was 0.20 and the localization error was 5.1 mm. The present simulation and experimental results suggest the merits of the 3DECI imaging approach, and the validity of intracardiac mapping as a tool to evaluate the 3DECI.

Animals↗

PubMed2006

Estimation of number of independent brain electric sources from the scalp EEGs.

In electromagnetic source analysis, many source localization strategies require the number of sources as an input parameter (e.g., spatio-temporal dipole fitting and the multiple signal classification). In the present study, an information criterion method, in which the penalty functions are selected based on the spatio-temporal source model, has been developed to estimate the number of independent dipole sources from electromagnetic measurements such as the electroencephalogram (EEG). Computer simulations were conducted to evaluate the effects of various parameters on the estimation of the source number. A three-concentric-spheres head model was used to approximate the head volume conductor. Three kinds of typical signal sources, i.e., the damped sinusoid sources, sinusoid sources with one frequency band and sinusoid sources with two separated frequency bands, were used to simulate the oscillation characteristics of brain electric sources. The simulation results suggest that the present method can provide a good estimate of the number of independent dipole sources from the EEG measurements. In addition, the present simulation results suggest that choosing the optimal penalty function can successfully reduce the effect of noise on the estimation of number of independent sources. The present study suggests that the information criterion method may provide a useful means in estimating the number of independent brain electrical sources from EEG/MEG measurements.

Action Potentials↗

PubMed2006

Spatio-temporal EEG source localization using a three-dimensional subspace FINE approach in a realistic geometry inhomogeneous head model.

The subspace source localization approach, i.e., first principle vectors (FINE), is able to enhance the spatial resolvability and localization accuracy for closely-spaced neural sources from EEG and MEG measurements. Computer simulations were conducted to evaluate the performance of the FINE algorithm in an inhomogeneous realistic geometry head model under a variety of conditions. The source localization abilities of FINE were examined at different cortical regions and at different depths. The present computer simulation results indicate that FINE has enhanced source localization capability, as compared with MUSIC and RAP-MUSIC, when sources are closely spaced, highly noise-contaminated, or inter-correlated. The source localization accuracy of FINE is better, for closely-spaced sources, than MUSIC at various noise levels, i.e., signal-to-noise ratio (SNR) from 6 dB to 16 dB, and RAP-MUSIC at relatively low noise levels, i.e., 6 dB to 12 dB. The FINE approach has been further applied to localize brain sources of motor potentials, obtained during the finger tapping tasks in a human subject. The experimental results suggest that the detailed neural activity distribution could be revealed by FINE. The present study suggests that FINE provides enhanced performance in localizing multiple closely spaced, and inter-correlated sources under low SNR, and may become an important alternative to brain source localization from EEG or MEG.

Algorithms↗

PubMed2006

Noninvasive reconstruction of three-dimensional ventricular activation sequence from the inverse solution of distributed equivalent current density.

We propose a new electrocardiographic (ECG) inverse approach for imaging the three-dimensional (3-D) ventricular activation sequence based on the modeling and estimation of the equivalent current density throughout the entire volume of the ventricular myocardium. The spatio-temporal coherence of the ventricular excitation process has been utilized to derive the activation time from the estimated time course of the equivalent current density. In the present study, we explored four different linear inverse algorithms (the minimum norm and weighted minimum norm estimates in combination with two regularization schemes: the instant-by-instant regularization and the isotropy method) to estimate the current density at each time instant during the ventricular depolarization. The activation time at any given location within the ventricular myocardium was determined as the time point with the occurrence of the maximum local current density estimate. Computer simulations were performed to evaluate this approach using single- and dual-site pacing protocols in a physiologically realistic cellular automaton heart model. The performance and stability of the proposed approach was evaluated with respect to the various levels of measurement noise (0, 5, 10, 20, 40, and 60 microV), the various numbers of ECG electrodes and the modeling errors on the torso geometry and heart position. The simulation results demonstrate that: 1) the single-site paced 3-D activation sequence can be well reconstructed from 200-channel body surface potential maps with additive Gaussian white noise of 20 microV (correlation coefficient = 0.90, relative error = 0.19, and localization error = 5.49 mm); 2) a higher imaging accuracy can be obtained when the activation is initiated from the left/right ventricle (LV/RV) compared to from the septum; 3) the isotropy method gives rise to a better performance than the conventional instant-by-instant regularization; 4) a decreased imaging accuracy results from a larger noise level, a fewer number of electrodes, or the volume conductor modeling errors; however, a reasonable imaging accuracy can still be obtained with a 60 microV noise level, 64 electrodes, or mild errors on both the torso geometry and heart position, respectively; 5) the dual-site paced 3-D activation sequence can be imaged when the two sites are paced either simultaneously or with a time delay of 20 ms; 6) two pacing sites can be resolved and localized in the imaged 3-D activation sequence when they are located at the contralateral sides of ventricles or at the ventricular lateral wall and the apex, respectively.

Body Surface Potential Mapping↗

PubMed2006

An enhanced time-frequency-spatial approach for motor imagery classification.

Human motor imagery (MI) tasks evoke electroencephalogram (EEG) signal changes. The features of these changes appear as subject-specific temporal traces of EEG rhythmic components at specific channels located over the scalp. Accurate classification of MI tasks based upon EEG may lead to a noninvasive brain-computer interface (BCI) to decode and convey intention of human subjects. We have previously proposed two novel methods on time-frequency feature extraction, expression and classification for high-density EEG recordings (Wang and He 2004; Wang, Deng, and He, 2004). In the present study, we refined the above time-frequency-spatial approach and applied it to a one-dimensional "cursor control" BCI experiment with online feedback. Through offline analysis of the collected data, we evaluated the capability of the present refined method in comparison with the original time-frequency-spatial methods. The enhanced performance in terms of classification accuracy was found for the proposed approach, with a mean accuracy rate of 91.1% for two subjects studied.

Adult↗