Variational Bayesian inversion of the equivalent current dipole model in EEG/MEG

In magneto- and electroencephalography (M/EEG), spatial modelling of sensor data is necessary to make inferences about underlying brain activity. Most source reconstruction techniques belong to one of two approaches: point source models, which explain the data with a small number of equivalent current dipoles and distributed source or imaging models, which use thousands of dipoles. Much methodological research has been devoted to developing sophisticated Bayesian source imaging inversion schemes, while dipoles have received less such attention. Dipole models have their advantages; they are often appropriate summaries of evoked responses or helpful first approximations. Here, we propose a variational Bayesian algorithm that enables the fast Bayesian inversion of dipole models. The approach allows for specification of priors on all the model parameters. The posterior distributions can be used to form Bayesian confidence intervals for interesting parameters, like dipole locations. Furthermore, competing models (e.g., models with different numbers of dipoles) can be compared using their evidence or marginal likelihood. Using synthetic data, we found the scheme provides accurate dipole localizations. We illustrate the advantage of our Bayesian scheme, using a multi-subject EEG auditory study, where we compare competing models for the generation of the N100 component.     

Overview of dipole source localization

Truly accurate dipole source localization relies on having (1) reliable, artifact-free EP/ERP (or magnetoelectroencephalogram) data to start with; (2) landmark and electrode position data obtained with a three-dimensional digitizer; (3) MRI (or CT) data from the same subject (with a means to measure the same landmarks); (4) the capability to apply different dipole and volume conductor models; and (5) the ability to coregister the functional and anatomic data to display the final source solutions. Most important is to have a thorough understanding of the fundamental principles of the localization programs and neurophysiologic processes. Localization programs are simply tools. Used incorrectly, they can yield meaningless results. Used correctly, they can provide a window into neurophysiologic functioning that is not available through any other means.     

Cluster significance testing using the bootstrap

Many of the statistical methods currently employed to analyze fMRI data depend on a response template. However, the true form of the hemodynamic response, and thereby the response template, is often unknown. Consequently, cluster analysis provides a complementary, template-free method for exploratory analysis of multidimensional fMRI data sets. Clustering algorithms currently being applied to fMRI data separate the data into a predefined number of clusters (k). A poor choice of k will result in erroneously partitioning well-defined clusters. Although several clustering algorithms have been successfully applied to fMRI data, techniques for statistically testing cluster separation are still lacking. To address this problem we suggest a method based on Fisher's linear discriminant and the bootstrap. Also introduced in this paper is a measure based on the projection of multidimensional data from two clusters onto the vector, maximizing the ratio of the between- to the within-cluster sums of squares. The resulting one-dimensional distribution may be readily visualized and used as a heuristic for estimating cluster homogeneity. These methods are demonstrated for the self-organizing maps clustering algorithm when applied to event-related fMRI data.     

Probabilistic streamline q-ball tractography using the residual bootstrap

Q-ball imaging has the ability to discriminate multiple intravoxel fiber populations within regions of complex white matter architecture. This information can be used for fiber tracking; however, diffusion MR is susceptible to noise and multiple other sources of uncertainty affecting the measured orientation of fiber bundles. The proposed residual bootstrap method utilizes a spherical harmonic representation for high angular resolution diffusion imaging (HARDI) data in order to estimate the uncertainty in multimodal q-ball reconstructions. The accuracy of the q-ball residual bootstrap technique was examined through simulation. The residual bootstrap method was then used in combination with q-ball imaging to construct a probabilistic streamline fiber tracking algorithm. The residual bootstrap q-ball fiber tracking algorithm is capable of following the corticospinal tract and corpus callosum through regions of crossing white matter tracts in the centrum semiovale. This fiber tracking algorithm is an improvement upon prior diffusion tensor methods and the q-ball data can be acquired in a clinically feasible time frame.     

Identifying true cortical interactions in MEG using the nulling beamformer

Modeling functional brain interaction networks using non-invasive EEG and MEG data is more challenging than using intracranial recording data. This is because most interaction measures are not robust to the cross-talk (interference) between cortical regions, which may arise due to the limited spatial resolution of EEG/MEG inverse procedures. In this article, we describe a modified beamforming approach to accurately measure cortical interactions from EEG/MEG data, designed to suppress cross-talk between cortical regions. We estimate interaction measures from the output of the modified beamformer and test for statistical significance using permutation tests. Since the underlying neuronal sources and their interactions are unknown in real MEG data, we demonstrate the performance of the proposed beamforming method in a novel simulation scheme, where intracranial recordings from a macaque monkey are used as neural sources to simulate realistic MEG signals. The advantage of this approach is that local field potentials are more realistic representations of true neuronal sources than simulation models and therefore are more suitable to indicate the performance of our nulling beamforming method.     

mRNALocater: Enhance the prediction accuracy of eukaryotic mRNA subcellular localization by using model fusion strategy

1. Download : Download high-res image (111KB)
2. Download : Download full-size image

     

Localization of realistic cortical activity in MEG using current multipoles

We present a novel approach to MEG source estimation based on a regularized first-order multipole solution. The Gaussian regularizing prior is obtained by calculation of the sample mean and covariance matrix for the equivalent moments of realistic simulated cortical activity. We compare the regularized multipole localization framework to the classical dipole and general multipole source estimation methods by evaluating the ability of all three solutions to localize the centroids of physiologically plausible patches of activity simulated on the surface of a human cerebral cortex. The results, obtained with a realistic sensor configuration, a spherical head model, and given in terms of field and localization error, depict the performance of the dipolar and multipolar models as a function of variable source surface area (50-500 mm(2)), noise conditions (20, 10, and 5 dB SNR), source orientation (0-90 degrees ), and source depth (3-11 cm). We show that as the sources increase in size, they become less accurately modeled as current dipoles. The regularized multipole systematically outperforms the single dipole model, increasingly so as the spatial extent of the sources increases. In addition, our simulations demonstrate that as the orientation of the sources becomes more radial, dipole localization accuracy decreases substantially, while the performance of the regularized multipole model is far less sensitive to orientation and even succeeds in localizing quasi-radial source configurations. Furthermore, our results show that the multipole model is able to localize superficial sources with higher accuracy than the current dipole. These results indicate that the regularized multipole solution may be an attractive alternative to current-dipole-based source estimation methods in MEG.     

Summarizing benchmarks in the national database of nursing quality indicators using bootstrap confidence intervals

When summarizing the benchmarks for nursing quality indicators with confidence intervals around the means, bounds too high or too low are sometimes found due to small sample size or violation of the normality assumption. Transforming the data or truncating the confidence intervals at realistic values can solve the problem of out of range values. However, truncation does not improve upon the non-normality of the data, and transformations are not always successful in normalizing the data. The percentile bootstrap has the advantage of providing realistic bounds while not relying upon the assumption of normality and may provide a convenient way of obtaining appropriate confidence intervals around the mean for nursing quality indicators.     

Consistent and precise localization of brain activity in human primary visual cortex by MEG and fMRI

The tomographic localization of activity within human primary visual cortex (striate cortex or V1) was examined using whole-head magnetoencephalography (MEG) and 4-T functional magnetic resonance imaging (fMRI) in four subjects. Circular checkerboard pattern stimuli with radii from 1.8 to 5.2 degrees were presented at eccentricity of 8 degrees and angular position of 45 degrees in the lower quadrant of the visual field to excite the dorsal part of V1 which is distant from the V1/V2 border and from the fundus of the calcarine sulcus. Both fMRI and MEG identified spatially well-overlapped activity within the targeted area in each subject. For MEG, in three subjects a very precise activation in V1 was identified at 42 ms for at least one of the two larger stimulus sizes (radii 4.5 and 5.2 degrees ). When this V1 activity was present, it marked the beginning of a weak wave of excitations in striate and extrastriate areas which ended at 50 ms (M50). The beginning of the next wave of activations (M70) was also marked by a brief V1 activation, mainly between 50 and 60 ms. The mean separation between V1 activation centers identified by fMRI and the earliest MEG activation was 3-5 mm.     

MEG localization of rolandic spikes with respect to SI and SII cortices in benign rolandic epilepsy

The purpose of this study was to study the relationship between interictal spike sources and somatosensory cortices in benign rolandic epilepsy of childhood (BREC) using a whole-scalp neuromagnetometer. We recorded spontaneous magnetoencephalography (MEG) and EEG signals and cortical somatosensory-evoked magnetic fields (SEFs) to electric stimulation of the median nerve in 9 children with BREC. Interictal rolandic discharges (RDs) and SEFs were analyzed by equivalent current dipole (ECD) modeling. Based on the orientation and locations of corresponding ECDs, we compared generators of RDs with primary (SI) and second somatosensory cortices (SII). Our results showed that RDs and SII responses had similar ECD orientation on the magnetic field maps. The ECDs of RDs were localized 15.3 +/- 1.9 and 12.2 +/- 2.8 mm anterior to SI and SII, respectively. The spatial distance on average from the location of RDs to SII (21.9 +/- 1.6 mm) cortex was significantly shorter than to SI cortex (29.7 +/- 1.7 mm) (P<0.01, Wilcoxon signed-rank test). In conclusion, the cortical generators for RDs in patients with BREC are localized in the precentral motor cortex, closer to hand SII than to SI cortex.     

MEG imaging of sensorimotor areas using inter-trial coherence in vibrotactile steady-state responses

We utilized a novel analysis technique to identify brain areas that activate synchronously during the steady-state interval of responses to vibrotactile stimulation of the right index finger. The inter-trial coherence at the stimulation rate (23 Hz) was determined for whole-brain neural activity estimates based on a linearly-constrained minimum variance beamformer applied to the MEG data. Neural activity coherent with the stimulus occurred in the contralateral primary somatosensory cortex in all subjects, and matched well with equivalent dipole modeling of the same data. Subsets of subjects exhibited additional loci of strongly coherent activity in the contralateral primary motor cortex, posterior parietal cortex, and supplementary motor area, as well as in deeper brain structures above the brainstem. An activation delay of 7 ms from deep structures to cortical areas was estimated based on the mean phase at each coherent neural source within a single subject. This new approach - volumetric mapping of the statistical parameter of inter-trial coherence in steady-state oscillations - broadens the range of MEG beamformer applications specifically for identifying brain areas that are synchronized to repetitive stimuli.     

Comparison of spike-triggered functional MRI BOLD activation and EEG dipole model localization.

We studied six patients with localization-related epilepsy, frequent interictal epileptiform discharges, and positive spike-triggered blood oxygen level-dependent functional MRI (BOLD-fMRI) findings. EEG source analysis solutions based on 64-channel EEG recorded in a separate session outside the scanner were obtained using dipole models and compared to the BOLD localization. The BOLD and structural images were coregistered, allowing the measurement of distances between the generator models and BOLD activation(s) and structural lesion when present. In all cases dipole models could be found that explained a sufficient amount of the data and that were anatomically concordant with the BOLD localization. In the five cases with structural abnormality visible on T1 scans, the BOLD activation overlapped or was in close proximity to the abnormality. The overall mean distance between the main moving dipole and the center of the nearest BOLD activation was 3.5 and 2.2 cm for the negative and positive peaks, respectively, including one case of a deep BOLD activation, in which the distance was 5 cm. In conclusion, the degree of agreement between the BOLD and EEG source localization indicates that the combination of these two noninvasive techniques offers the possibility of advancing the study of the generators of epileptiform electrical activity.     

精神分裂症住院患者抗精神病药使用现状调查

目的探讨抗精神病药在精神分裂症住院患者中的使用现状．为临床合理用药提供帮助。方法对5年来在我院住院的474例精神分裂症、分裂样精神病患者应用抗精神病药物的临床资料进行回顾性分析。结果利培酮使用率由1998年的22．39％上升到2002年的81.08％,氯氮平由1998年的76．47％下降到2002年的29．73％,氯丙嗪、舒必利、奋乃静也有明显下降;单一用药由1998年的63．24％上升到2002年的72．07％;两种药物联用占25．53％,3种联用占3．16％;联合用药由1998年的36．76％下降至2002年的28．83％;2000年前氯氮平与舒必利联用最多,2000年后利培酮与氯氮平联用最多。结论新型抗精神病药物在临床替代传统药物的速度明显加快,且逐渐趋于单一化用药。     

Multiresolution imaging of MEG cortical sources using an explicit piecewise model

Imaging neural generators from MEG magnetic fields is often considered as a compromise between computationally-reasonable methodology that usually yields poor spatial resolution on the one hand, and more sophisticated approaches on the other hand, potentially leading to intractable computational costs. We approach the problem of obtaining well-resolved source images with unexcessive computation load with a multiresolution image model selection (MiMS) technique. The building blocks of the MiMS source model are parcels of the cortical surface which can be designed at multiple spatial resolutions with the combination of anatomical and functional priors. Computation charge is reduced owing to 1) compact parametric models of the activation of extended brain parcels using current multipole expansions and 2) the optimization of the generalized cross-validation error on image models, which is closed-form for the broad class of linear estimators of neural currents. Model selection can be complemented by any conventional imaging approach of neural currents restricted to the optimal image support obtained from MiMS. The estimation of the location and spatial extent of brain activations is discussed and evaluated using extensive Monte-Carlo simulations. An experimental evaluation was conducted with MEG data from a somatotopic paradigm. Results show that MiMS is an efficient image model selection technique with robust performances at realistic noise levels.     

超声辅助定位胸椎水平的准确性及影响因素分析

目的探讨超声辅助定位法定位胸椎水平的准确性,并与体表标志触诊法进行比较。方法选择我院择期行脊柱手术的患者48例,术前由一名熟练掌握触诊定位的麻醉医师通过体表标志触诊法定位第7颈椎(C7)棘突后,向尾侧依次触诊直至确定第7胸椎(T7)棘突位置并标记为T7a。然后由另一名熟练掌握脊柱超声的麻醉医师使用低频凸阵探头放置于颈椎水平横切面上下扫查,确定C7棘突后继续向尾侧扫查确定T1棘突和横突位置并标记,再依次扫查确定T7横突位置并标记为T7b。最后由同一脊柱外科医师通过C臂机拍摄图像确定T7的准确位置,以判定T7a和T7b的定位是否正确。探讨体质量指数(BMI)和年龄对两种定位方法准确性的影响。结果超声辅助定位法准确率为85.4%,显著高于体表标志触诊法(52.1%),差异有统计学意义(P<0.05);超声辅助定位法相较于体表标志触诊法降低了个体差异对定位的影响;BMI和年龄对两种定位方法准确率的影响比较差异均无统计学意义。结论超声辅助定位法优于体表标志触诊法,有重要的临床应用价值。     

Improved localization accuracy in stochastic super-resolution fluorescence microscopy by K-factor image deshadowing

Localization of a single fluorescent particle with sub-diffraction-limit accuracy is a key merit in localization microscopy. Existing methods such as photoactivated localization microscopy (PALM) and stochastic optical reconstruction microscopy (STORM) achieve localization accuracies of single emitters that can reach an order of magnitude lower than the conventional resolving capabilities of optical microscopy. However, these techniques require a sparse distribution of simultaneously activated fluorophores in the field of view, resulting in larger time needed for the construction of the full image. In this paper we present the use of a nonlinear image decomposition algorithm termed K-factor, which reduces an image into a nonlinear set of contrast-ordered decompositions whose joint product reassembles the original image. The K-factor technique, when implemented on raw data prior to localization, can improve the localization accuracy of standard existing methods, and also enable the localization of overlapping particles, allowing the use of increased fluorophore activation density, and thereby increased data collection speed. Numerical simulations of fluorescence data with random probe positions, and especially at high densities of activated fluorophores, demonstrate an improvement of up to 85% in the localization precision compared to single fitting techniques. Implementing the proposed concept on experimental data of cellular structures yielded a 37% improvement in resolution for the same super-resolution image acquisition time, and a decrease of 42% in the collection time of super-resolution data with the same resolution.OCIS codes: (180.2520) Fluorescence microscopy, (100.0100) Image processing, (100.3010) Image reconstruction techniques, (100.6640) Superresolution     

Accurate reconstruction of temporal correlation for neuronal sources using the enhanced dual-core MEG beamformer

Beamformer spatial filters are commonly used to explore the active neuronal sources underlying magnetoencephalography (MEG) recordings at low signal-to-noise ratio (SNR). Conventional beamformer techniques are successful in localizing uncorrelated neuronal sources under poor SNR conditions. However, the spatial and temporal features from conventional beamformer reconstructions suffer when sources are correlated, which is a common and important property of real neuronal networks. Dual-beamformer techniques, originally developed by Brookes et al. to deal with this limitation, successfully localize highly-correlated sources and determine their orientations and weightings, but their performance degrades at low correlations. They also lack the capability to produce individual time courses and therefore cannot quantify source correlation. In this paper, we present an enhanced formulation of our earlier dual-core beamformer (DCBF) approach that reconstructs individual source time courses and their correlations. Through computer simulations, we show that the enhanced DCBF (eDCBF) consistently and accurately models dual-source activity regardless of the correlation strength. Simulations also show that a multi-core extension of eDCBF effectively handles the presence of additional correlated sources. In a human auditory task, we further demonstrate that eDCBF accurately reconstructs left and right auditory temporal responses and their correlations. Spatial resolution and source localization strategies corresponding to different measures within the eDCBF framework are also discussed. In summary, eDCBF accurately reconstructs source spatio-temporal behavior, providing a means for characterizing complex neuronal networks and their communication.     

Parathyroid adenoma: accuracy of preoperative localization by high-resolution real-time sonography

To assess the accuracy of high-resolution sonography of the parathyroid glands, a consecutive series of sonograms in 58 patients was reviewed. The study population was limited to patients thought clinically to have primary hyperparathyroidism and likely to have one enlarged adenomatous gland. Patients with renal failure or other evidence of secondary hyperparathyroidism were excluded. Typical sonographic features of parathyroid adenoma were observed. An overall accuracy of 92% was obtained for the identification of surgically confirmed parathyroid gland enlargement due to adenoma.     

Detection of very high correlation in the alpha band between temporal regions of the human brain using MEG

It is generally believed that alpha band (8-12 Hz) electric and magnetic activity in the area of the left and right temporal regions in the human brain are at best poorly correlated. There are no previous reports of very high alpha band correlation between left and right temporal regions by magnetoencephalography (MEG) or electroencephalography (EEG). We present whole head magnetoencephalography (MEG) results that demonstrate that, for temporal channels in the majority of healthy subjects tested, the alpha band signals are highly to very highly correlated and are antiparallel in direction. A correlation as high as -0.97 was found for a limited time in one subject. We suggest that the correlation found may be the consequence of strong direct or indirect coupling between homologue areas in left and right temporal regions rather than a common source. The correlation may provide a valuable index of loss of connectivity in the brain due to disease as well providing valuable insight to brain function and deserves further investigation.     

探讨经腹超声造影与内镜超声联合应用对胰岛素瘤的术前定位的价值

目的 探讨经腹超声造影及超声内镜两种方法 联合对胰岛素瘤的术前定位的准确性.方法 44例明确诊断为胰岛素瘤的患者在我院进行胰岛素瘤术前定位,其中包括CT平扫加增强、超声造影、内镜超声,对比分析经腹超声造影及内镜超声联合应用与增强CT在胰岛素瘤定位诊断的准确性.结果 44例胰岛素瘤均经外科手术治疗;41例患者进行了术前CT平扫及增强CT检查,其中23例患者的肿瘤定位准确,准确率为56.1%,33例患者联合超声造影与内镜超声定位,30例患者定位准确(90.9%),联合超声造影与内镜超声的定位准确性与CT平扫加增强定位准确性存在统计学差异(P<0.05).结论 与CT平扫加增强比较,联合应用超声造影及内镜超声两种方法 可以显著提高胰岛细胞瘤定位诊断的准确性,值得在临床上进一步推广应用.