Interacción en sistemas biológicos mediante nuevos índices basados en la dinámica no lineal

Premi extraordinari doctorat curs 2010-2011, àmbit d’Enginyeria Enginyeria IndustrialMost biological systems are complex and consist of several interconnected parts whose links can contain additional information which can be hidden from the observer. As a result of the interactions between elements, emergent properties that cannot be explained by the characteristics of isolated elements can arise. Current clinical applications record a high number of different signals that contain information about these physiological systems, providing multichannel data whose interactions can be studied by classical reference methods, generally linear, as the correlation analysis and spectral coherence, and other nonlinear methods that are being defined and developed during recent years, such as nonlinear prediction, entropies, mutual information and phase synchronization. The development, improvement and application of new analytical techniques is a field with obvious social and technological interest, especially when performed by noninvasive techniques, which can improve the processes of rehabilitation and clinical therapy, and also help the development of new diagnostic tools. In this thesis new indexes have been defined in order to evaluate: * The coordination of respiratory muscles in healthy subjects and patients with obstructive sleep apnea syndrome (OSAS) during an effort ventilatory protocol. * The effect on functional connectivity of the brain after administration of a psychoactive drug. * The changes caused by Alzheimer's disease (AD) in the connectivity of the brain. Respiratory muscles provide the mechanical energy that supports respiration. The evaluation of interactions between electromyographic (EMG) and mechanomiographic (MMG) signals of different respiratory muscles, genioglossus, sternomastoid and diaphragm, has allowed the discrimination of coordination patterns of OSAS patients with respect to healthy subjects at low, medium and high respiratory effort during while awake. Analysis and characterization of the electroencephalographic (EEG) and magnetoencephalographic (MEG) signals allows the understanding of brain function to assist in the process of clinical diagnosis of disorders in neurology, psychiatry and pharmacology. In this thesis the interactions within and between different brain regions have been assessed, using new nonlinear indexes which have managed to reflect changes over time in the brain after administration of alprazolam, and to characterize andto differentiate brain connectivity of AD patients with respect to healthy subjects.La mayoría de sistemas biológicos son sistemas complejos que constan de diversas partes interconectadas cuyos vínculos pueden contener información adicional y oculta al observador. Como resultado de estas interacciones entre elementos surgen propiedades emergentes, que no pueden explicarse a partir de las características de los elementos aislados. Las aplicaciones clínicas actuales registran un elevado número de señales diferentes que contienen información sobre estos sistemas fisiológicos, cosa que permite disponer de datos multicanal, cuyas interacciones pueden ser estudiadas mediante métodos clásicos de referencia generalmente lineales, como el análisis de correlación y la coherencia espectral, u otros métodos no lineales que están siendo definidos y desarrollados durante los últimos años, como la predicción no lineal, las entropías, la información mutua o la sincronización de fase. El desarrollo, mejora y aplicación de nuevas técnicas de análisis constituye un campo con evidente interés social y tecnológico, en especial cuando se realiza mediante técnicas no invasivas, que puede proporcionar mejoras en los procesos de rehabilitación y terapia clínica, así como contribuir a desarrollar herramientas de ayuda al diagnóstico. En esta tesis se han definido nuevos índices no lineales que han permitido evaluar: * La coordinación de los músculos respiratorios en sujetos sanos y pacientes con síndrome de apnea obstructiva del sueño (SAOS) durante un protocolo ventilatorio de esfuerzo. * El efecto en la conectividad funcional del cerebro tras la administración de un fármaco psicoactivo. * Los cambios provocados por la enfermedad de Alzheimer (EA) en la conectividad del cerebro. La musculatura respiratoria proporciona la energía mecánica que soporta la respiración. La evaluación de las interacciones entre señales electromiográficas (EMG) y mecanomiográficas (MMG) de diferentes músculos respiratorios -geniogloso, esternocleidomastoideo y diafragma- ha permitido diferenciar el patrón de coordinación de los pacientes con SAOS de los sujetos sanos a niveles bajos, medios y altos de esfuerzo respiratorio durante vigilia. El análisis y caracterización de las señales electroencefalográficas (EEG) y magnetoencefalográficas (MEG) permite la comprensión de la función cerebral para ayudar en el proceso de diagnóstico clínico de disfunciones en neurología, psiquiatría y farmacología. En esta tesis se han evaluado las interacciones en y entre diferentes regiones cerebrales mediante nuevos índices no lineales que han conseguido reflejar los cambios producidos a lo largo del tiempo en el cerebro tras la administración del fármaco alprazolam, así como caracterizar y diferenciar la conectividad cerebral de los pacientes con EA con respecto a sujetos sanos. Las herramientas utilizadas en las aplicaciones mencionadas se basan en las siguientes técnicas de análisis no lineal: * La función de información mutua cruzada, el equivalente no lineal de la función de correlación cruzada, que cuantifica la información compartida entre dos variables aleatorias. * La entropía condicional corregida cruzada, una medida que cuantifica la información restante contenida en una variable aleatoria cuando se conoce totalmente otra variable relacionada, y por lo tanto es una medida complementaria de la información mutua. * La predicción no lineal basada en modelos localmente lineales, una herramienta matemática que permite deducir la evolución de una serie temporal en función de muestras anteriores. Los nuevos índices desarrollados han demostrado la necesidad de evaluar las interacciones en los sistemas biológicos y fisiológicos tanto con métodos lineales como no lineales, para obtener una evaluación más completa de la dinámica subyacente y ayudar en los procesos de diagnóstico de patologías y en el procedimiento de evaluación psicofarmacológica.Award-winningPostprint (published version

Spatial distribution of HD-EMG improves identification of task and force in patients with incomplete spinal cord injury

Background: Recent studies show that spatial distribution of High Density surface EMG maps (HD-EMG) improves the identification of tasks and their corresponding contraction levels. However, in patients with incomplete spinal cord injury (iSCI), some nerves that control muscles are damaged, leaving some muscle parts without an innervation. Therefore, HD-EMG maps in patients with iSCI are affected by the injury and they can be different for every patient. The objective of this study is to investigate the spatial distribution of intensity in HD-EMG recordings to distinguish co-activation patterns for different tasks and effort levels in patients with iSCI. These patterns are evaluated to be used for extraction of motion intention.; Method: HD-EMG was recorded in patients during four isometric tasks of the forearm at three different effort levels. A linear discriminant classifier based on intensity and spatial features of HD-EMG maps of five upper-limb muscles was used to identify the attempted tasks. Task and force identification were evaluated for each patient individually, and the reliability of the identification was tested with respect to muscle fatigue and time interval between training and identification. Results: Three feature sets were analyzed in the identification: 1) intensity of the HD-EMG map, 2) intensity and center of gravity of HD-EMG maps and 3) intensity of a single differential EMG channel (gold standard).; Results show that the combination of intensity and spatial features in classification identifies tasks and effort levels properly (Acc = 98.8 %; S = 92.5 %; P = 93.2 %; SP = 99.4 %) and outperforms significantly the other two feature sets (p < 0.05).; Conclusion: In spite of the limited motor functionality, a specific co-activation pattern for each patient exists for both intensity, and spatial distribution of myoelectric activity. The spatial distribution is less sensitive than intensity to myoelectric changes that occur due to fatigue, and other time-dependent influences.Peer ReviewedPostprint (published version

Prediction of isometric motor tasks and effort levels based on high-density EMG in patients with incomplete spinal cord injury

Objective. The development of modern assistive and rehabilitation devices requires reliable and easy-to-use methods to extract neural information for control of devices. Group-specific pattern recognition identifiers are influenced by inter-subject variability. Based on high-density EMG (HD-EMG) maps, our research group has already shown that inter-subject muscle activation patterns exist in a population of healthy subjects. The aim of this paper is to analyze muscle activation patterns associated with four tasks (flexion/extension of the elbow, and supination/pronation of the forearm) at three different effort levels in a group of patients with incomplete Spinal Cord Injury (iSCI). Approach. Muscle activation patterns were evaluated by the automatic identification of these four isometric tasks along with the identification of levels of voluntary contractions. Two types of classifiers were considered in the identification: linear discriminant analysis and support vector machine. Main results. Results show that performance of classification increases when combining features extracted from intensity and spatial information of HD-EMG maps (accuracy = 97.5%). Moreover, when compared to a population with injuries at different levels, a lower variability between activation maps was obtained within a group of patients with similar injury suggesting stronger task-specific and effort-level-specific co-activation patterns, which enable better prediction results. Significance. Despite the challenge of identifying both the four tasks and the three effort levels in patients with iSCI, promising results were obtained which support the use of HD-EMG features for providing useful information regarding motion and force intentionPeer ReviewedPostprint (author's final draft

Avaliação do efeito da referencia em estudos farmacológicos mediante EEG

Um dos problemas que apresenta o registro de electroencefalogramas (EEG) está relacionado com a referência usada durante a aquisição dos dados. O presente artigo analisa o comportamento de três referências, o promédio mastoides (RPM), o promédio común (RPC) e o método de estandardização do eletrodo de referência (REST), usadas no registro de EEG num estudo farmacológico realizado com alprazolam (medicamento psicoativo). Os resultados foram analisados no dominio frequencial para avaliar a ação do fármaco e através da informação mútua cruzada para investigar a conetividade cerebral. Nenhuma das referências apresenta melhores resultados em todos os casos estudados, REST tem boa atuação nas variáveis espectrais e de conectividade enquanto que as outras duas trabalham melhor só em um dos casos.Postprint (published version

Influence of metallic artifact filtering on MEG signals for source localization during interictal epileptiform activity

Objective. Medical intractable epilepsy is a common condition that affects 40% of epileptic patients that generally have to undergo resective surgery. Magnetoencephalography (MEG) has been increasingly used to identify the epileptogenic foci through equivalent current dipole (ECD) modeling, one of the most accepted methods to obtain an accurate localization of interictal epileptiform discharges (IEDs). Modeling requires that MEG signals are adequately preprocessed to reduce interferences, a task that has been greatly improved by the use of blind source separation (BSS) methods. MEG recordings are highly sensitive to metallic interferences originated inside the head by implanted intracranial electrodes, dental prosthesis, etc and also coming from external sources such as pacemakers or vagal stimulators. To reduce these artifacts, a BSS-based fully automatic procedure was recently developed and validated, showing an effective reduction of metallic artifacts in simulated and real signals (Migliorelli et al 2015 J. Neural Eng. 12 046001). The main objective of this study was to evaluate its effects in the detection of IEDs and ECD modeling of patients with focal epilepsy and metallic interference. Approach. A comparison between the resulting positions of ECDs was performed: without removing metallic interference; rejecting only channels with large metallic artifacts; and after BSS-based reduction. Measures of dispersion and distance of ECDs were defined to analyze the results. Main results. The relationship between the artifact-to-signal ratio and ECD fitting showed that higher values of metallic interference produced highly scattered dipoles. Results revealed a significant reduction on dispersion using the BSS-based reduction procedure, yielding feasible locations of ECDs in contrast to the other two approaches. Significance. The automatic BSS-based method can be applied to MEG datasets affected by metallic artifacts as a processing step to improve the localization of epileptic foci.Postprint (published version

Estudi de la connectivitat cerebral durant la vigília prolongada

En aquest estudi s’avaluen els efectes de la privació de son sobre el senyals electroencefalogràfics de voluntaris sans mitjançant la transferència d’entropia (TE), una tècnica no paramètrica que permet detectar dependències direccionals entre variables. El resultats obtinguts concorden amb la potència en la banda θ, un marcador reconegut relacionat amb la pressió de son. Els màxims efectes de la privació de son es produeixen després de 24 hores sense dormir, període en el qual es produeixen increments de TE localitzats en la regió anterior del cap, mentre que es produeixen disminucions que afecten tot el crani. El valor mitjà d’aquestes disminucions mostra una correlació alta amb la potència theta, de manera que es pot considerar un marcador fiable de la pressió de son, alhora que aporta informació sobre la localització dels canvis produïts i indica una disminució global de la transferència d’informació entre zones

Successful object encoding induces increased directed connectivity in presymptomatic early-onset Alzheimer's disease

Background: Recent studies report increases in neural activity in brain regions critical to episodic memory at preclinical stages of Alzheimer’s disease (AD). Although electroencephalography (EEG) is widely used in AD studies, given its non-invasiveness and low cost, there is a need to translate the findings in other neuroimaging methods to EEG. Objective: To examine how the previous findings using functional magnetic resonance imaging (fMRI) at preclinical stage in presenilin-1 E280A mutation carriers could be assessed and extended, using EEG and a connectivity approach. Methods: EEG signals were acquired during resting and encoding in 30 normal cognitive young subjects, from an autosomal dominant early-onset AD kindred from Antioquia, Colombia. Regions of the brain previously reported as hyperactive were used for connectivity analysis. Results: Mutation carriers exhibited increasing connectivity at analyzed regions. Among them, the right precuneus exhibited the highest changes in connectivity. Conclusion: Increased connectivity in hyperactive cerebral regions is seen in individuals, genetically-determined to develop AD, at preclinical stage. The use of a connectivity approach and a widely available neuroimaging technique opens the possibility to increase the use of EEG in early detection of preclinical AD.Postprint (author's final draft

A novel spatial feature for the identification of motor tasks using high-density electromyography

Estimation of neuromuscular intention using electromyography (EMG) and pattern recognition is still an open problem. One of the reasons is that the pattern-recognition approach is greatly influenced by temporal changes in electromyograms caused by the variations in the conductivity of the skin and/or electrodes, or physiological changes such as muscle fatigue. This paper proposes novel features for task identification extracted from the high-density electromyographic signal (HD-EMG) by applying the mean shift channel selection algorithm evaluated using a simple and fast classifier-linear discriminant analysis. HD-EMG was recorded from eight subjects during four upper-limb isometric motor tasks (flexion/extension, supination/pronation of the forearm) at three different levels of effort. Task and effort level identification showed very high classification rates in all cases. This new feature performed remarkably well particularly in the identification at very low effort levels. This could be a step towards the natural control in everyday applications where a subject could use low levels of effort to achieve motor tasks. Furthermore, it ensures reliable identification even in the presence of myoelectric fatigue and showed robustness to temporal changes in EMG, which could make it suitable in long-term applications.Peer ReviewedPostprint (published version

Evaluation of Respiratory Muscles Activity by means of Cross Mutual Information Function at Different Levels of Ventilatory Effort

Analysis of respiratory muscles activity is an effective technique for the study of pulmonary diseases such as obstructive sleep apnea syndrome (OSAS). Respiratory diseases, especially those associated with changes in the mechanical properties of the respiratory apparatus, are often associated with disruptions of the normally highly coordinated contractions of respiratory muscles. Due to the complexity of the respiratory control, the assessment of OSAS related dysfunctions by linear methods are not sufficient. Therefore, the objective of this study was the detection of diagnostically relevant nonlinear complex respiratory mechanisms. Two aims of this work were: 1) to assess coordination of respiratory muscles contractions through evaluation of interactions between respiratory signals and myographic signals through nonlinear analysis by means of cross mutual information function (CMIF); 2) to differentiate between functioning of respiratory muscles in patients with OSAS and in normal subjects. Electromyographic(EMG) and mechanomyographic (MMG) signals were recorded from three respiratory muscles: genioglossus, sternomastoid and diaphragm. Inspiratory pressure and flow were also acquired. All signals were measured in eight patients with OSAS and eight healthy subjects during an increased respiratory effort while awake. Several variables were defined and calculated from CMIF in order to describe correlation between signals. The results indicate different nonlinear couplings of respiratory muscles in both populations. This effect is progressively more evident at higher levels of respiratory effort

Estudio de la conectividad cerebral mediante transferencia de entropía

En el presente trabajo se estudian los efectos de la privación del sueño sobre las señales electroencefalográficas de voluntarios sanos mediante la transferencia de entropía (TE), una técnica no paramétrica que permite detectar relaciones direccionales entre variables y que no ha sido utilizada antes para el estudio de la vigilia prolongada. Los resultados obtenidos concuerdan con la potencia en la banda ϴ, un marcador reconocido relacionado con la presión de sueño. Los efectos máximos de la privación del sueño se producen a partir de las 24 horas sin dormir. Durante este periodo, se producen incrementos de TE localizados en la zona anterior mientras que los decrementos principalmente se originan en la zona occipital y afectan globalmente al resto del cerebro. El promedio de estos decrementos muestra una fuerte correlación con la potencia ϴ, por lo que se podría considerar como otro marcador fiable de la presión de sueño que, además, proporciona información sobre la localización de los cambios producidos, indicando una disminución de la transferencia de información entre las regiones cerebrales.Peer ReviewedPostprint (author’s final draft