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Zhongming Liu

Publications and source records attributed to Zhongming Liu.

9 recordsLinked to original sources
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

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

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

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↗
PubMed2005

Noninvasive three-dimensional electrocardiographic imaging of ventricular activation sequence.

Imaging the myocardial activation sequence is critical for improved diagnosis and treatment of life-threatening cardiac arrhythmias. It is desirable to reveal the underlying cardiac electrical activity throughout the three-dimensional (3-D) myocardium (rather than just the endocardial or epicardial surface) from noninvasive body surface potential measurements. A new 3-D electrocardiographic imaging technique (3-DEIT) based on the boundary element method (BEM) and multiobjective nonlinear optimization has been applied to reconstruct the cardiac activation sequences from body surface potential maps. Ultrafast computerized tomography scanning was performed for subsequent construction of the torso and heart models. Experimental studies were then conducted, during left and right ventricular pacing, in which noninvasive assessment of ventricular activation sequence by means of 3-DEIT was performed simultaneously with 3-D intracardiac mapping (up to 200 intramural sites) using specially designed plunge-needle electrodes in closed-chest rabbits. Estimated activation sequences from 3-DEIT were in good agreement with those constructed from simultaneously recorded intracardiac electrograms in the same animals. Averaged over 100 paced beats (from a total of 10 pacing sites), total activation times were comparable (53.3 +/- 8.1 vs. 49.8 +/- 5.2 ms), the localization error of site of initiation of activation was 5.73 +/- 1.77 mm, and the relative error between the estimated and measured activation sequences was 0.32 +/- 0.06. The present experimental results demonstrate that the 3-D paced ventricular activation sequence can be reconstructed by using noninvasive multisite body surface electrocardiographic measurements and imaging of heart-torso geometry. This new 3-D electrocardiographic imaging modality has the potential to guide catheter-based ablative interventions for the treatment of life-threatening cardiac arrhythmias.

Algorithms↗
PubMed2005

Classification of motor imagery tasks for brain-computer interface applications by means of two equivalent dipoles analysis.

We have developed a novel approach using source analysis for classifying motor imagery tasks. Two-equivalent-dipoles analysis was proposed to aid classification of motor imagery tasks for brain-computer interface (BCI) applications. By solving the electroencephalography (EEG) inverse problem of single trial data, it is found that the source analysis approach can aid classification of motor imagination of left- or right-hand movement without training. In four human subjects, an averaged accuracy of classification of 80% was achieved. The present study suggests the merits and feasibility of applying EEG inverse solutions to BCI applications from noninvasive EEG recordings.

Action Potentials↗
PubMed2005

[Research and development of a piezoelectric immunosensor for detecting Treponema pallidum].

We utilized polyethylenimine (PEI) and Glu solution to immobilize the antibody of Treponema Pallidum on the silver electrode of piezoelectric quartz crystal and detect the standard antigen solution at different concentration. The antibody keeps the intrinsic Y type molecular structure revealed by AFM. The resonant range of the sensor is between 5 x 10(-5) - 1.25 x 10(-4) g/mL and the correlation coefficient is 0.9976, the optimal resonance pH is 7.5. We found the sensor having good selectivity in comparison with the method using BSA. At last, a discussion on the reproducibility of the sensor is presented.

Antibodies, Bacterial↗