Dynamic inverse problem solution using a kalman filter smoother for neuronal activity estimation

En este artículo se presenta un método de estimación de la actividad neuronal sobre el cerebro usando un filtro de Kalman con suavizado, que tiene en cuenta en la solución del problema inverso, la variabilidad dinámica de la serie de tiempo. Este método es aplicado sobre un modelo realista de la cabeza, calculado con elementos finitos de frontera. Se presenta un análisis comparativo entre diferentes métodos de estimación y el método propuesto sobre señales EEG simuladas para diferentes condiciones de relación señal a ruido. La solución del problema inverso se hace utilizando computación de alto desempeño y se presenta una evaluación delcosto computacional para cada método. Como resultado, el filtro de Kalman con suavizado presenta un mejor desempeño en la tarea de estimación comparado con la solución estática regularizada, y la solución dinámica sin suavizado.This article presents an estimation method of neuronal activity into the brain using a Kalman smoother approach that takes into account in the solution of the inverse problem the dynamic variability of the time series. This method is applied over a realistic head model calculated with the boundary element method. A comparative analysis for the dynamic estimation methods is made up from simulated EEG signals for several noise conditions. The solution of the inverse problem is achieved by using high performance computing techniques and an evaluation of the computational cost is performed for each method. As a result, the Kalman smoother approach presents better performance in the estimation task than the regularized static solution, and the direct Kalman filter

Entrenamiento Discriminativo Maximizando una Distancia entre Modelos de Clases

En este trabajo se presenta una técnica de entrenamiento discriminativo para modelos ocultos de Markov, orientado a la detección de patologías en señales de voz. La técnica busca maximizar el área que encierra la curva ROC (Receiver Operating Characteristic curve) ajustando los parámetros de modelo, empleando como función objetivo la distancia entre las medias de las funciones de densidad de probabilidad subyacentes asociadas a cada clase. Como resultado se obtiene una mejora en el desempeño del sistema de clasificación comparada con diferentes criterios de entrenamiento.This paper presents an approach that improves discriminative training criterion for Hidden Markov Models, and it is oriented to voice pathological identification. This technique aims at maximizing the Area under the Receiver Operating Characteristic curve by adjusting the model parameters using as objective function the distance between the means of the underlying probability densities functions associated with each class. As result we obtain an improvement in the performance of the classification system compared with different training criteria

High prevalence of radiolucent periapical lesions amongst patients with inherited coagulation disorders

Apical periodontitis (AP) is an inflammatory lesion around the apex of a tooth caused by bacterial infection of the pulp canal system. AP appears radiographically as a radiolucent periapical lesion (RPL). The elective treatment for teeth with AP is root canal treatment (RCT). No study is available about the frequency of RPL and RCT in patients with inherited coagulation disorders (ICD). The aim of this study was to investigate the prevalence of RPL and RCT in patients with ICD and control subjects. In a cross-sectional study, the radiographic records of 58 patients with haemophilia A, haemophilia B or von Willebrand's disease (study group) and 58 control subjects were examined. The frequency of RPL and RCT was assessed using digital panoramic radiographs and the Periapical Index. RPL in one or more teeth was found in 67.2% of patients with ICD and in 48.3% of control subjects (odds ratio = 2.20; P = 0.038). At least one RCT was found in 34.5% and 65.5% of subjects in the study and control groups respectively (odds ratio = 0.28; P = 0.001). Multivariate logistic regression analysis indicated that subjects with ICD had RPL with higher likelihood than control subjects (odds ratio = 7.4; P = 0.0005). Patients with ICD disorders showed a significantly higher prevalence of RPL and lower frequency of RCT than control patients. © 2013 Blackwell Publishing Ltd. PMID: 23320531 [PubMed - indexed for MEDLINE

Replica Cluster Variational Method: the Replica Symmetric solution for the 2D random bond Ising model

We present and solve the Replica Symmetric equations in the context of the Replica Cluster Variational Method for the 2D random bond Ising model (including the 2D Edwards-Anderson spin glass model). First we solve a linearized version of these equations to obtain the phase diagrams of the model on the square and triangular lattices. In both cases the spin-glass transition temperatures and the tricritical point estimations improve largely over the Bethe predictions. Moreover, we show that this phase diagram is consistent with the behavior of inference algorithms on single instances of the problem. Finally, we present a method to consistently find approximate solutions to the equations in the glassy phase. The method is applied to the triangular lattice down to T=0, also in the presence of an external field.Comment: 22 pages, 11 figure

Characterizing and Improving Generalized Belief Propagation Algorithms on the 2D Edwards-Anderson Model

We study the performance of different message passing algorithms in the two dimensional Edwards Anderson model. We show that the standard Belief Propagation (BP) algorithm converges only at high temperature to a paramagnetic solution. Then, we test a Generalized Belief Propagation (GBP) algorithm, derived from a Cluster Variational Method (CVM) at the plaquette level. We compare its performance with BP and with other algorithms derived under the same approximation: Double Loop (DL) and a two-ways message passing algorithm (HAK). The plaquette-CVM approximation improves BP in at least three ways: the quality of the paramagnetic solution at high temperatures, a better estimate (lower) for the critical temperature, and the fact that the GBP message passing algorithm converges also to non paramagnetic solutions. The lack of convergence of the standard GBP message passing algorithm at low temperatures seems to be related to the implementation details and not to the appearance of long range order. In fact, we prove that a gauge invariance of the constrained CVM free energy can be exploited to derive a new message passing algorithm which converges at even lower temperatures. In all its region of convergence this new algorithm is faster than HAK and DL by some orders of magnitude.Comment: 19 pages, 13 figure

Reduction of power line interference in electrocardiographic signals by dual Kalman filtering

[EN] This paper presents a filter for reducing powerline interference in electrocardiographic signals (ECG), based on dual parameter and state estimation using with a Kalman filter. Two models were used to represent power-line interference and ECG signal. Both models were combined to simulate the ECG signal whose state was estimated for separating the ECG signal from the interference. The proposed algorithm was fine-tuned and compared using a set of tests relying on the QT arrhythmia database. Tuning tests were done for tracking clean ECG; these results were used for setting the algorithm¿s parameters for later filtering tests. Exhaustive filtering tests were carried out on artificially corrupted database registers for given signal to noise ratios; performance curves were thus obtained, leading to comparing the proposed algorithm with other filtering methods. The proposed algorithm was compared to an recursive infinite impulse response filter (IIR) and a Kalman filter based on a simpler model. A filtering algorithm was thus obtained which is robust for changes in interference amplitude and keeps these properties for different types of ECG morphologies.[ES] En este artículo se presenta el desarrollo de un filtro para la reducción de la interferencia de línea de potencia en señales electrocardiográficas (ECG), basado en estimación dual de parámetros y de estado, empleando la filtración Kalman, en el cual se consideran modelos independientes entre la interferencia de línea de potencia y la señal ECG. Ambos modelos son combinados para simular la señal ECG medida sobre la que se realiza la estimación de estado para separar la señal de la interferencia. El algoritmo propuesto es sintonizado y comparado en un conjunto de pruebas realizadas sobre la base de datos QT de electrocardiografía. Inicialmente se hacen pruebas de sintonización del algoritmo para el rastreo de la señal ECG limpia, cuyos resultados son utilizados después para las pruebas de filtrado. Luego se llevan a cabo pruebas exhaustivas sobre la base de datos QT en la filtración de interferencia de línea de potencia, la cual ha sido introducida artificialmente en los registros, para una relación de señal a ruido (SNR) dada, obteniendo así curvas del desempeño del algoritmo, que permiten a su vez comparar con el desempeño de otros algoritmos de filtración, a saber, un filtro notch recursivo de respuesta infinita al impulso (IIR) y un filtro de Kalman, basado en un modelo más simple para la señal ECG. Como resultado, se demuestra que el algoritmo de filtrado obtenido es robusto a los cambios de amplitud de la interferencia; además, conserva sus propiedades para los diferentes tipos de morfologías de señales ECG normales y patológicas.Este trabajo se realiza en el marco del proyecto de la DIMA Técnicas de Computación de Alto Rendimiento en la Interpretación Automatizada de Imágenes Médicas y Bioseñales.Avendaño-Valencia, LD.; Avendaño, LE.; Ferrero De Loma-Osorio, JM.; Castellanos-Domínguez, G. (2007). Reducción de interferencia de línea de potencia en señales electrocardiográficas mediante el filtro dual de Kalman. Ingeniería e Investigación. 27(3):77-88. http://hdl.handle.net/10251/150636S778827

Transverse Phase Locking for Vortex Motion in Square and Triangular Pinning Arrays

We analyze transverse phase locking for vortex motion in a superconductor with a longitudinal DC drive and a transverse AC drive. For both square and triangular arrays we observe a variety of fractional phase locking steps in the velocity versus DC drive which correspond to stable vortex orbits. The locking steps are more pronounced for the triangular arrays which is due to the fact that the vortex motion has a periodic transverse velocity component even for zero transverse AC drive. All the steps increase monotonically in width with AC amplitude. We confirm that the width of some fractional steps in the square arrays scales as the square of the AC driving amplitude. In addition we demonstrate scaling in the velocity versus applied DC driving curves at depinning and on the main step, similar to that seen for phase locking in charge-density wave systems. The phase locking steps are most prominent for commensurate vortex fillings where the interstitial vortices form symmetrical ground states. For increasing temperature, the fractional steps are washed out very quickly, while the main step gains a linear component and disappears at melting. For triangular pinning arrays we again observe transverse phase locking, with the main and several of the fractional step widths scaling linearly with AC amplitude.Comment: 10 pages, 14 postscript figure

Evaluation of CNV detection tools for NGS panel data in genetic diagnostics

Although germline copy-number variants (CNVs) are the genetic cause of multiple hereditary diseases, detecting them from targeted next-generation sequencing data (NGS) remains a challenge. Existing tools perform well for large CNVs but struggle with single and multi-exon alterations. The aim of this work is to evaluate CNV calling tools working on gene panel NGS data and their suitability as a screening step before orthogonal confirmation in genetic diagnostics strategies. Five tools (DECoN, CoNVaDING, panelcn.MOPS, ExomeDepth, and CODEX2) were tested against four genetic diagnostics datasets (two in-house and two external) for a total of 495 samples with 231 single and multi-exon validated CNVs. The evaluation was performed using the default and sensitivity-optimized parameters. Results showed that most tools were highly sensitive and specific, but the performance was dataset dependant. When evaluating them in our diagnostics scenario, DECoN and panelcn.MOPS detected all CNVs with the exception of one mosaic CNV missed by DECoN. However, DECoN outperformed panelcn.MOPS specificity achieving values greater than 0.90 when using the optimized parameters. In our in-house datasets, DECoN and panelcn.MOPS showed the highest performance for CNV screening before orthogonal confirmation. Benchmarking and optimization code is freely available at https://github.com/TranslationalBioinformaticsIGTP/CNVbenchmarkeR

Melting and transverse depinning of driven vortex lattices in the periodic pinning of Josephson junction arrays

We study the non-equilibrium dynamical regimes of a moving vortex lattice in the periodic pinning of a Josephson junction array (JJA) for {\it finite temperatures} in the case of a fractional or submatching field. We obtain a phase diagram for the current driven JJA as a function of the driving current I and temperature T. We find that when the vortex lattice is driven by a current, the depinning transition at $T_p(I)$ and the melting transition at $T_M(I)$ become separated even for a field for which they coincide in equilibrium. We also distinguish between the depinning of the vortex lattice in the direction of the current drive, and the {\it transverse depinning} in the direction perpendicular to the drive. The transverse depinning corresponds to the onset of transverse resistance in a moving vortex lattice at a given temperature $T_{tr}$. For driving currents above the critical current we find that the moving vortex lattice has first a transverse depinning transition at low T, and later a melting transition at a higher temperature, $T_{M}>T_{tr}$.Comment: 17 pages, 19 figure