Enhanced Data Covariance Estimation Using Weighted Combination of Multiple Gaussian Kernels for Improved M/EEG Source Localization.

In the recent past, estimating brain activity with magneto/electroencephalography (M/EEG) has been increasingly employed as a noninvasive technique for understanding the brain functions and neural dynamics. However, one of the main open problems when dealing with M/EEG data is its non-Gaussian and nonstationary structure. In this paper, we introduce a methodology for enhancing the data covariance estimation using a weighted combination of multiple Gaussian kernels, termed WM-MK, that relies on the Kullback-Leibler divergence for associating each kernel weight to its relevance. From the obtained results of validation on nonstationary and non-Gaussian brain activity (simulated and real-world EEG data), WM-MK proves that the accuracy of the source estimation raises by more effectively exploiting the measured nonlinear structures with high time and space complexity.

Reconstruction of Neural Activity from EEG Data Using Dynamic Spatiotemporal Constraints.

We present a novel iterative regularized algorithm (IRA) for neural activity reconstruction that explicitly includes spatiotemporal constraints, performing a trade-off between space and time resolutions. For improving the spatial accuracy provided by electroencephalography (EEG) signals, we explore a basis set that describes the smooth, localized areas of potentially active brain regions. In turn, we enhance the time resolution by adding the Markovian assumption for brain activity estimation at each time period. Moreover, to deal with applications that have either distributed or localized neural activity, the spatiotemporal constraints are expressed through [Formula: see text] and [Formula: see text] norms, respectively. For the purpose of validation, we estimate the neural reconstruction performance in time and space separately. Experimental testing is carried out on artificial data, simulating stationary and non-stationary EEG signals. Also, validation is accomplished on two real-world databases, one holding Evoked Potentials and another with EEG data of focal epilepsy. Moreover, responses of functional magnetic resonance imaging for the former EEG data have been measured in advance, allowing to contrast our findings. Obtained results show that the [Formula: see text]-based IRA produces a spatial resolution that is comparable to the one achieved by some widely used sparse-based estimators of brain activity. At the same time, the [Formula: see text]-based IRA outperforms other similar smooth solutions, providing a spatial resolution that is lower than the sparse [Formula: see text]-based solution. As a result, the proposed IRA is a promising method for improving the accuracy of brain activity reconstruction.

Entropy-based multichannel measure of stationarity for characterization of motor imagery patterns.

We propose a novel approach for measuring the stationarity level of multichannel time-series. This measure is based on stationarity definition over time-varying spectra and aims to quantify the relationship between local (single-channel dynamics) and global (multichannel dynamics) stationarity. With the purpose of separate among several motor/imagery tasks, we asssume that movement imagination implies an increase on the EEG variability, consequently, as discriminant features, we first compute the non-stationary components of input signals, and we further obtain its stationary level throughout the proposed measure. To assess the separability level of the proposed features, we employ the t-student test. Obtained results evidence that our measure is able to accurately detect brain areas projected on the scalp where motor tasks are performed.

Feature selection for discrimination of fractionation levels in atrial electrograms.

Radiofrequency catheter ablation of atrial fibrillation (AF) guided by complex fractionated atrial electrograms (CFAE) is associated with a high AF termination rate in paroxysmal AF, but not in persistent. CFAE does not always identify favorable sites for persistent AF ablation. Studies suggest that only high fractionation level should be used as a target site for ablation. Nonetheless, there are not a standardized criterion to defined fractionation levels. Therefore, a better characterization of the signal is required providing a set of more powerful features that should be extracted from CFAE. Due to the apparent difference among fractionation classes in terms of their stochastic variability, we test time-domain and time-frequency based feature extraction approaches. Also, we carried out the symmetrical uncertainty-based feature selection to determine the most relevant features which improve discrimination of fractionation levels. Obtained results on a tested real electrogram database show that most relevant features in time-domain are related with time intervals and not with amplitudes. Nonetheless, time-frequency features obtained more information from the signal and this representation is likely a better suitable discriminating approach, particularly to detect high fractionated electrograms with a sensitivity and specificity of 83.0% and 93.6%, respectively.

Identification of brain networks using time-varying spatial constraints of neural activity reconstruction.

Electroencephalographic (EEG) data give a direct non-invasive measurement of neural brain activity. Nevertheless, the common assumption about EEG stationarity (time-invariant process) is a strong limitation for understanding real behavior of underlying neural networks. Here, we propose an approach for finding networks of brain regions connected by functional associations (functional connectivity) that vary along the time. To this end, we compute a set of a priori spatial dictionaries that represent brain areas with similar temporal stochastic dynamics, and then, we model relationship between areas as a time-varying process. We test our approach in both simulated and real EEG data where results show that inherent interpretability provided by the time-varying process can be useful to describe underlying neural networks.

Local binary fitting energy solution by graph cuts for MRI segmentation.

This paper proposes a new solution for local binary fitting energy minimization based on graph cuts for automatic brain structure segmentation on magnetic resonance images. The approach establishes an effective way to embed the energy formulation into a directed graph, such that the energy is minimized by maximizing the graph flow. Proposed and conventional solutions are compared by segmenting the well-known BrainWeb synthetic brain Magnetic Resonance Imaging database. Achieved results show an improvement on the computational cost (about 10 times shorter) while maintaining the segmentation accuracy (96%).

[Functional results of surgery for cervical stenosis]. / Resultados funcionales de la cirugía del conducto cervical estrecho.

INTRODUCTION: Cervical stenosis refers to the narrowing of the spinal canal or the intervertebral foramina at different anatomic levels, secondary to pathologic processes of the vertebral elements. Surgical management is used when conservative management fails. The anterior and posterior approaches are the most frequently used ones, and the surgical options resulting from these approaches are: anterior cervical diskectomy plus fusion, anterior corporectomy plus fusion, laminoplasty, laminectomy and arthroplasty. MATERIAL AND METHOD: This is an ambispective study conducted in 195 patients with a diagnosis of cervical stenosis who required surgical treatment at our hospital from January 1995 to January 2007. The neck disability index questionnaire was applied, as well as the Nurick scale. Descriptive statistics was used with frequency and percentage measures. RESULTS: The review of the National Rehabilitation Institute electronic records from January 1st 1995 to December 31st 2007 showed that 195 patients underwent surgery for cervical stenosis. Females were predominant. The most affected age group was 46-55 years. The most frequently affected level was C5-C6. A significant improvement was seen in the neck disability index due to pain and the Nurick scale. CONCLUSION: According to world literature, mean age of patients with cervical stenosis is 57.2 years, and the most compromised levels were C4-C5 and C5-C6. Improvement was evident according to the neck disability index and the Nurick scale.

Production levels and health status in Iberian piglets at weaning.

The aim of this study was to describe the postweaning growth of Iberian piglets and its relationship with the occurrence of diarrhea. To assess these factors in response to different weaning ages, a total of 360 pure-breed Iberian piglets were studied. Three trials were conducted with 120 piglets from 24 litters randomly assigned to be weaned at 28 or 42 d of age (12 litters and 60 piglets each). In each trial and from each weaning age, 4 groups of 15 piglets were assembled with different sexes and sizes (3 litters by group and 5 animals from each litter; 12 replicates and 180 piglets/weaning age). The duration of study period was 42 d and all animals were weighed weekly from 21 to 63 d of age. Food intake and fecal consistency were examined with the same frequency. General linear models and chi-square procedure was used with SPSS statistical package to perform the analysis with a confidence interval of 95% (P < 0.005). Pearson and Spearman analyses were conducted to examine relationships between variables. At the beginning (P = 0.798) and end of the study (P = 0.450) there were no significant differences between piglet weights. After weaning, there were differences in food intake and in conversion rates (P < 0.001), but there were no differences in ADG for the whole study period (P = 0.335). All groups experienced a similar decline in production rates during the first week after weaning and similar recovery times during the next weeks. Both weaning groups had a similar overall prevalence (P = 0.044) and incidence of diarrheal onset (P = 0.467), and regression analysis showed relationships between postweaning diarrhea and the overall prevalence of piglets before weaning (P < 0.01) and food intake during first week postweaning (P < 0.01). Therefore, weaning age has a similar influence on postweaning growth and on postweaning diarrhea in Iberian piglets.

Extraction of stationary components in biosignal discrimination.

Biosignal recordings are widely used in the medical environment to support the evaluation and the diagnosis of pathologies. Nevertheless, the main difficulty lies in the non-stationary behavior of the biosignals, difficulting the obtention of patterns characterizing the changes in physiological or pathological states. Thus, the obtention of the stationary and non-stationary components of a biosignal is still an open issue. This work proposes a methodology to detect time-homogeneities based on time-frequency analysis with aim to extract the non-stationary behavior of the biosignal. Results show an increase in the stationarity and in the distance between classes of the reconstructions from the enhanced time-frequency representations. The stationary components extracted with the proposed approach can be used to solve biosignal classification problems.

Effect of latency on clustering of P300 recordings for ADHD discrimination.

This paper is focused on testing the latency contribution as regards the quality of formed groups for discriminating between healthy and attention deficit hyperactivity disorder children. To this end, two different cases are considered: nonaligned original recordings and aligned signals according to P300 position. For latter case, a novel approach to conduct time location of P300 component is introduced, which is based on derivative of event-related potential signals. The used database holds event-related potentials registered in auditory and visual oddball paradigm. Several experiments are carried out testing both configurations of considered data matrix. For grouping input data matrices, the k-means clustering technique is employed. To assess the quality of formed clusters and the relevance for clustering of latency-based features, relative values of distances between centroids and data points are computed in order to apprise separability and compactness of estimated clusters. Experimental results show that time localization of P300 component is not a decisive feature in formation of compact and well-defined groups within a discrimination framework for two considered data classes under certain conditions.

On determining available stochastic features by spectral splitting in obstructive sleep apnea detection.

Heart rate variability (HRV) is one of the promising directions for a simple and noninvasive way for obstructive sleep apnea syndrome detection. The time-frequency representations has been proposed before to investigate the non-stationary properties of the HRV during either transient physiological or pathological episodes. Within the framework of the filter-banked feature extraction, estimation of the spectral splitting for stochastic features extraction is an open issue. Usually, this splitting is fixed empirically without taking into account the actual informative distribution of time-frequency representations. In the present work, a relevance-based approach that aims to find a priori a boundaries in the frequency domain for the spectral splitting upon t-f planes is proposed. Results show that the approach is able to find the most informative frequency bands, achieving accuracy rate over 75%.

Complexity-based analysis for the detection of heart murmurs.

While a healthy human heart produce a rhythmic pattern of sounds, some heart disorder induce deviations perceived as abnormal sounds called murmurs. Despite many murmurs can be considered harmless, other constitute the first basis of a heart disorder. In this sense, a correct diagnosis remains essential; however, due to the subjectivity on using human ear to make diagnosis, automatic detection systems appear as useful tools for helping medical specialists on improving diagnosis accuracy. Complexity analysis has become one important tool for the study of physiological signals, because tracking sudden alteration on the inherent complexity on biological processes might be useful for detecting pathologies. The present paper presents a complexity-based analysis methodology, which uses regularity features for the detection of heart murmurs, including Approximate Entropy, Sample Entropy, Gaussian Kernel Approximate Entropy, and Fuzzy Entropy. The results show the high discriminative power, up to 90%, of the Gaussian Kernel Approximate Entropy and Fuzzy Entropy for the proposed labour.

Reduction of irrelevant and redundant data from TFRs for EEG signal classification.

Time-frequency representations (TFR) are one of the most popular characterization methods for non-stationary biosignals. Despite of their potential advantages, these representations suffer of large quantity of redundant and irrelevant data which makes them difficult to use for classification purposes. In this work, a methodology for reduction of irrelevant and redundant data is explored. This approach consists on removing irrelevant data, applying a relevance measure on the t-f plane that measures the dependence of each t-f point with the class labels. Then, principal component analysis (PCA) and partial least squares (PLS) are used as non-supervised and supervised linear decomposition approaches to reduce redundancy of remaining t-f points. Results show that the proposed methodology improves the performance of classifier up to 3% when no relevance and redundancy on TFRs is reduced.

Stromal cell-derived receptor 2 and cytochrome b561 are functional ferric reductases.

Iron has a variety of functions in cellular organisms ranging from electron transport and DNA synthesis to adenosine triphosphate (ATP) and neurotransmitter synthesis. Failure to regulate the homeostasis of iron can lead to cognition and demyelination disorders when iron levels are deficient, and to neurodegenerative disorders when iron is in excess. In this study we show that three members of the b561 family of predicted ferric reductases, namely mouse cytochrome b561 and mouse and fly stromal cell-derived receptor 2 (SDR2), have ferric reductase activity. Given that a fourth member, duodenal cytochrome b (Dcytb), has previously been shown to be a ferric reductase, it is likely that all remaining members of this family also exhibit this activity. Furthermore, we show that the rat sdr2 message is predominantly expressed in the liver and kidney, with low expression in the duodenum. In hypotransferrinaemic (hpx) mice, sdr2 expression in the liver and kidney is reduced, suggesting that it may be regulated by iron. Moreover, we demonstrate the presence of mouse sdr2 in the choroid plexus and in the ependymal cells lining the four ventricles, through in situ hybridization analysis.

Cloning and developmental expression analysis of ltd-1, the Caenorhabditis elegans homologue of the mouse kyphoscoliosis (ky) gene.

We have characterized the developmental expression pattern of the Caenorhabditis elegans homologue of the mouse ky gene. The Ky protein has a putative key function in muscle development and has homologues in invertebrates, fungi and a cyanobacterium. The C. elegans Ky homologue gene has been named ltd-1 for LIM and transglutaminase domains gene. The LTD-1::GFP construct is expressed in developing hypodermal cells from the twofold stage embryo through adulthood. These data define the ltd-1 gene as a novel marker for C. elegans epithelial cell development.

Transmural extent of acute myocardial infarction predicts long-term improvement in contractile function.

BACKGROUND: Previous animal studies have demonstrated that the transmural extent of acute myocardial infarction defined by contrast-enhanced MRI (ceMRI) relates to early restoration of flow and future improvements in contractile function. We tested the hypothesis that ceMRI would have similar predictive value in humans. METHODS AND RESULTS: Twenty-four patients who presented with their first myocardial infarction and were successfully revascularized underwent cine and ceMRI of their heart within 7 days (scan 1) of the peak MB band of creatine kinase. Cine MRI was repeated 8 to 12 weeks later (scan 2). The transmural extent of infarction on scan 1 and wall thickening on both scans were determined using a 72-segment model. A total of 524 of 1571 segments (33%) were dysfunctional on scan 1. Improvement in segmental contractile function on scan 2 was inversely related to the transmural extent of infarction on scan 1 (P=0.001). Improvement in global contractile function, as assessed by ejection fraction and mean wall thickening score, was not predicted by peak creatine kinase-MB (P=0.66) or by total infarct size, as defined by MRI (P=0.70). The best predictor of global improvement was the extent of dysfunctional myocardium that was not infarcted or had infarction comprising <25% of left ventricular wall thickness (P<0.005 for ejection fraction, P<0.001 for mean wall thickening score). CONCLUSION: In patients with acute myocardial infarction, the transmural extent of infarction defined by ceMRI predicts improvement in contractile function.

Visualisation of presence, location, and transmural extent of healed Q-wave and non-Q-wave myocardial infarction.

BACKGROUND: A technical advance in contrast-enhanced magnetic resonance imaging (MRI) has significantly improved image quality. We investigated whether healed myocardial infarction can be visualised as hyperenhanced regions with this new technique, and whether assessment of the transmural extent of infarction yields new physiological data. METHODS: 82 MRI examinations were carried out in three groups: patients with healed myocardial infarction; patients with non-ischaemic cardiomyopathy; and healthy volunteers. Patients with healed myocardial infarction were prospectively enrolled after enyzmatically proven necrosis and imaged 3 months (SD 1) or 14 months (7) later. The MRI procedure used a segmented inversion-recovery gradient-echo sequence after gadolinium administration. Findings were compared with those of coronary angiography, electrocardiography, cine MRI, and creatine kinase measurements. FINDINGS: 29 (91%) of 32 patients with infarcts imaged at 3 months (13 non-Q-wave) and all of 19 imaged at 14 months (eight non-Q-wave) showed hyperenhancement. In patients in whom the infarct-related-artery was identified by angiography, 24 of 25 imaged at 3 months and all of 14 imaged at 14 months had hyperenhancement in the appropriate territory. None of the 20 patients with non-ischaemic cardiomyopathy or the 11 healthy volunteers showed hyperenhancement. Irrespective of the presence or absence of Q waves, the majority of patients with hyperenhancement had only non-transmural involvement. Normal left-ventricular contraction was shown in seven patients examined at 3 months and three examined at 14 months, but in these cases hyperenhancement was limited to the subendocardium. INTERPRETATION: The presence, location, and transmural extent of healed Q-wave and non-Q-wave myocardial infarction can be accurately determined by contrast-enhanced MRI.

Type 2 intramolecular nitroso Diels-Alder reaction. Synthesis and structure of bridgehead oxazinolactams.

[reaction--see text] The type 2 intramolecular Diels-Alder cycloaddition utilizing N-acylnitroso dienophiles provides an efficient entry into bridged oxazinolactams. In contrast to the bimolecular counterpart, the reaction is completely regioselective. Structural characterization of the cycloadducts allows for evaluation of the olefin distortion and the degree of pyramidalization of the bridgehead oxazinolactam.

GGAs: a family of ADP ribosylation factor-binding proteins related to adaptors and associated with the Golgi complex.

Formation of intracellular transport intermediates and selection of cargo molecules are mediated by protein coats associated with the cytosolic face of membranes. Here, we describe a novel family of ubiquitous coat proteins termed GGAs, which includes three members in humans and two in yeast. GGAs have a modular structure consisting of a VHS domain, a region of homology termed GAT, a linker segment, and a region with homology to the ear domain of gamma-adaptins. Immunofluorescence microscopy showed colocalization of GGAs with Golgi markers, whereas immunoelectron microscopy of GGA3 revealed its presence on coated vesicles and buds in the area of the TGN. Treatment with brefeldin A or overexpression of dominant-negative ADP ribosylation factor 1 (ARF1) caused dissociation of GGAs from membranes. The GAT region of GGA3 was found to: target a reporter protein to the Golgi complex; induce dissociation from membranes of ARF-regulated coats such as AP-1, AP-3, AP-4, and COPI upon overexpression; and interact with activated ARF1. Disruption of both GGA genes in yeast resulted in impaired trafficking of carboxypeptidase Y to the vacuole. These observations suggest that GGAs are components of ARF-regulated coats that mediate protein trafficking at the TGN.