Affective Valence Detection from EEG Signals Using Wrapper Methods

In this work, a novel valence recognition system applied to EEG signals is presented. It consists of a feature extraction block followed by a wrapper classification algorithm. The proposed feature extraction method is based on measures of relative energies computed in short‐time intervals and certain frequency bands of EEG signal segments time‐locked to the stimuli presentation. These measures represent event‐related desynchronization/synchronization of underlying brain neural networks. The subsequent feature selection and classification steps comprise a wrapper technique based on two different classification approaches: an ensemble classifier, i.e., a random forest of classification trees and a support vector machine algorithm. Applying a proper importance measure from the classifiers, the feature elimination has been used to identify the most relevant features of the decision making both for intrasubject and intersubject settings, using single trial signals and ensemble averaged signals, respectively. The proposed methodologies allowed us to identify a frontal region and a beta band as the most relevant characteristics, extracted from the electrical brain activity, in order to determine the affective valence elicited by visual stimuli

Feature Extraction and Classification of Biosignals - Emotion Valence Detection from EEG Signals

In thisworkavalencerecognitionsystembasedonelectroencephalogramsispresented.Theperformanceof the systemisevaluatedfortwosettings:singlesubjects(intra-subject)andbetweensubjects(inter-subject). The featureextractionisbasedonmeasuresofrelativeenergiescomputedinshorttimeintervalsandcertain frequencybands.Thefeatureextractionisperformedeitheronsignalsaveragedoveranensembleoftrialsor on single-trialresponsesignals.Thesubsequentclassificationstageisbasedonanensembleclassifier,i.e.a random forestoftreeclassifiers.Theclassificationisperformedconsideringtheensembleaverageresponsesof all subjects(inter-subject)orconsideringthesingle-trialresponsesofsinglesubjects(intra-subject).Applying a properimportancemeasureoftheclassifier,featureeliminationhasbeenusedtoidentifythemostrelevant features of the decision making.info:eu-repo/semantics/publishedVersio

Individual EEG differences in affective valence processing in women with low and high neuroticism

Objective: In this study, individual differences in brain electrophysiology during positive and negative affective valence processing in women with different neuroticism scores are quantified. Methods: Twenty-six women scoring high and low on neuroticism participated on this experiment. A support vector machine (SVM)-based classifier was applied on the EEG single trials elicited by high arousal pictures with negative and positive valence scores. Based on the accuracy values obtained from subject identification tasks, the most distinguishing EEG channels among participants were detected, pointing which scalp regions show more distinct patterns. Results: Significant differences were obtained, in the EEG heterogeneity between positive and negative valence stimuli, yielding higher accuracy in subject identification using negative pictures. Regarding the topographical analysis, significantly higher accuracy values were reached in occipital areas and in the right hemisphere (p < 0:001). Conclusions: Mainly, individual differences in EEG can be located in parietooccipital regions. These differences are likely to be due to the different reactivity and coping strategies to unpleasant stimuli in individuals with high neuroticism. In addition, the right hemisphere shows a greater individual specificity. Significance: An SVM-based classifier asserts the individual specificity and its topographical differences in electrophysiological activity for women with high neuroticism compared to low neuroticism

EEG study on affective valence elicited by novel and familiar pictures using ERD/ERS and SVM-RFE

EEG signals have been widely explored in emotional processing analyses, both in time and frequency domains. However, in such studies, habituation phenomenon is barely considered in the discrimination of different emotional responses. In this work, spectral features of the event-related potentials (ERPs) are studied by means of event-related desynchronization/synchronization computation. In order to determine the most relevant ERP features for distinguishing how positive and negative affective valences are processed within the brain, support vector machine-recursive feature elimination is employed. The proposed approach was applied for investigating in which way the familiarity of stimuli affects the affective valence processing as well as which frequency bands and scalp regions are more involved in this process. In a group composed of young adult women, results prove that parietooccipital region and theta band are especially involved in the processing of novelty in emotional stimuli

Interconnection among River Flow Levels, Sediments Loads and Tides Conditions and Its Effect on the Coastal Wetlands Reduction

When the river supplies water to vulnerable environments, such as marshlands, it is vital to establish the expected impact mostly under a changing climate, and moreover, if a dam is being projected to solve energy demands. Soil characteristics, specifically sediment composition, are exposed to changes that modify this type of ecosystem and are rarely investigated. For this, a discharge period for an average historical year was analyzed to evaluate the magnitudes of the flows, with or without a dam. Also, it helped to identify the modification of the hydrodynamic regime between the sea and the lagoon system, particularly during the dry season but also checking the behavior in the rainy season. Results showed that the main problem with the construction of the dam on the San Pedro-Mezquital river would be the effect of a controlled flow that reaches the wetlands of the alluvial plains, affecting the sediment load in the estuarine and coastal ecology. However, after a readjustment period, the dam neither significantly changes the previous flood conditions of the coastal plain nor the sediment load will be a problem. However, if an additional sediment load is required to maintain the coastal microhabitats, there are different ways to provide it

Quantitative electroencephalography reveals different physiological profiles between benign and remitting-relapsing multiple sclerosis patients

<p>Abstract</p> <p>Background</p> <p>A possible method of finding physiological markers of multiple sclerosis (MS) is the application of EEG quantification (QEEG) of brain activity when the subject is stressed by the demands of a cognitive task. In particular, modulations of the spectral content that take place in the EEG of patients with multiple sclerosis remitting-relapsing (RRMS) and benign multiple sclerosis (BMS) during a visuo-spatial task need to be observed.</p> <p>Methods</p> <p>The sample consisted of 19 patients with RRMS, 10 with BMS, and 21 control subjects. All patients were free of medication and had not relapsed within the last month. The power spectral density (PSD) of different EEG bands was calculated by Fast-Fourier-Transformation (FFT), those analysed being delta, theta, alpha, beta and gamma. Z-transformation was performed to observe individual profiles in each experimental group for spectral modulations. Lastly, correlation analyses was performed between QEEG values and other variables from participants in the study (age, EDSS, years of evolution and cognitive performance).</p> <p>Results</p> <p>Nearly half (42%) the RRMS patients showed a statistically significant increase of two or more standard deviations (SD) compared to the control mean value for the beta-2 and gamma bands (F = 2.074, p = 0.004). These alterations were localized to the anterior regions of the right hemisphere, and bilaterally to the posterior areas of the scalp. None of the BMS patients or control subjects had values outside the range of ± 2 SD. There were no significant correlations between these values and the other variables analysed (age, EDSS, years of evolution or behavioural performance).</p> <p>Conclusion</p> <p>During the attentional processing, changes in the high EEG spectrum (beta-2 and gamma) in MS patients exhibit physiological alterations that are not normally detected by spontaneous EEG analysis. The different spectral pattern between pathological and controls groups could represent specific changes for the RRMS patients, indicative of compensatory mechanisms or cortical excitatory states representative of some phases during the RRMS course that are not present in the BMS group.</p

Attentional networks in neurodegenerative diseases: anatomical and functional evidence from the Attention Network Test

Introduction: Understanding alterations to brain anatomy and cognitive function associated with neurodegenerative diseases remains a challenge for neuroscience today. In experimental neuroscience, several computerised tests have been developed to contribute to our understanding of neural networks involved in cognition. The Attention Network Test (ANT) enables us to measure the activity of 3 attentional networks (alertness, orienting, and executive function). Objectives: The main aim of this review is to describe all the anatomical and functional alterations found in diverse neurological diseases using the ANT. Material and methods: We collected studies published since 2010 in the PubMed database that employed the ANT in different neurological diseases. Thirty-two articles were obtained, addressing multiple sclerosis, epilepsy, and Parkinson’s disease, among other disorders. Conclusions: Some of the anatomical structures proposed in the 3 attentional networks model were confirmed. The most relevant structures in the alertness network are the prefrontal cortex, parietal region, thalamus, and cerebellum. The thalamus is also relevant in the orienting network, together with posterior parietal regions. The executive network does not depend exclusively on the prefrontal cortex and anterior cingulate cortex, but also involves such subcortical structures as the basal ganglia and cerebellum and their projections towards the entire cortex. Resumen: Introducción: Comprender las alteraciones en la anatomía y función del cerebro en los procesos cognitivos para las enfermedades neurodegenerativas es aún un desafío para la neurociencia actual. Desde la neurociencia experimental, algunos tests computarizados han sido desarrollados para mejorar nuestro conocimiento de las redes neurales involucradas en la cognición. El Attention Network Test (ANT) permite medir la activad de las tres redes atencionales (alerta, orientación y función ejecutiva). Objetivos: El principal objetivo de esta revisión fue describir todas las alteraciones anatómicas y funcionales encontradas en diversas enfermedades neurológicas usando el ANT. Material y métodos: Un protocolo de revisión fue aplicado seleccionando estudios desde 2010 en la base de datos PubMed que involucraban al Attention Network Test en diferentes enfermedades neurológicas. Se obtuvieron treinta y dos artículos para esclerosis múltiple, epilepsia o Parkinson entre otras patologías. Conclusiones: Se confirman algunas de las estructuras anatómicas propuestas para el modelo de tres grandes redes atencionales. Las estructuras más relevantes para la red de alerta son la corteza prefrontal, regiones parietales, tálamo y el cerebelo. El tálamo es también relevante para la red de orientación, junto a regiones parietales posteriores. Respecto a la red ejecutiva, no depende exclusivamente de la corteza prefrontal y corteza cingulada anterior, sino también de estructuras subcorticales como los ganglios basales y el cerebelo y sus proyecciones hacia toda la corteza

Revisión sistemática de la aplicación de algoritmos de «machine learning» en la esclerosis múltiple

Resumen: Introducción: La aplicación de la inteligencia artificial y en particular de algoritmos de aprendizaje automático o «machine learning» (ML) constituye un desafío y al mismo tiempo una gran oportunidad en diversas disciplinas científicas, técnicas y clínicas. Las aplicaciones específicas en el estudio de la esclerosis múltiple (EM) no han sido una excepción mostrando un creciente interés en los últimos años. Objetivo: Realizar una revisión sistemática de la aplicación de algoritmos de ML en la EM. Material y métodos: Empleando el motor de búsqueda de libre acceso PubMed que accede a la base de datos MEDLINE, se seleccionaron aquellos estudios que incluyeran simultáneamente los dos siguientes conceptos de búsqueda: «machine learning» y «multiple sclerosis». Se rechazaron aquellos estudios que fueran revisiones, estuvieran en otro idioma que no fuera el castellano o el inglés, y aquellos trabajos que tuvieran un carácter técnico y no fueran aplicados para la EM. Se seleccionaron como válidos 76 artículos y fueron rechazados 38. Conclusiones: Tras la revisión de los estudios seleccionados, se pudo observar que la aplicación del ML en la EM se concentró en cuatro categorías: 1) clasificación de subtipos de pacientes dentro de la enfermedad; 2) diagnóstico del paciente frente a controles sanos u otras enfermedades; 3) predicción de la evolución o de la respuesta a intervenciones terapéuticas y por último 4) otros enfoques. Los resultados hallados hasta la fecha muestran que los diferentes algoritmos de ML pueden ser un gran apoyo para el profesional sanitario tanto en la clínica como en la investigación de la EM. Abstract: Introduction: The applications of artificial intelligence, and in particular automatic learning or “machine learning” (ML), constitute both a challenge and a great opportunity in numerous scientific, technical, and clinical disciplines. Specific applications in the study of multiple sclerosis (MS) have been no exception, and constitute an area of increasing interest in recent years. Objective: We present a systematic review of the application of ML algorithms in MS. Materials and methods: We used the PubMed search engine, which allows free access to the MEDLINE medical database, to identify studies including the keywords “machine learning” and “multiple sclerosis.” We excluded review articles, studies written in languages other than English or Spanish, and studies that were mainly technical and did not specifically apply to MS. The final selection included 76 articles, and 38 were rejected. Conclusions: After the review process, we established 4 main applications of ML in MS: 1) classifying MS subtypes; 2) distinguishing patients with MS from healthy controls and individuals with other diseases; 3) predicting progression and response to therapeutic interventions; and 4) other applications. Results found to date have shown that ML algorithms may offer great support for health professionals both in clinical settings and in research into MS

Cambios en las propiedades fisicoquímicas y microbiológicas del suelo generados por la producción de carbón vegetal en el bosque templado de (quercus spp.) en Santa Rosa, Gto. México

The temperate forest of Quercus spp. Santa Rosa is one of the most extensive forests in central Mexico. In this forest, charcoal is produced traditionally by rural communities. This study evaluated the impact of the activity of charcoal production in three sampling sites of the forest, soil from the impact site, land adjacent to the site of charcoal production and control soil without charcoal production activity on physicochemical and microbiological properties. We determined pH, concentration of macro-and micro-elements was performed by calculating microbial colony forming units (CFU) of bacteria, fungi, actinomycetes and promoting growth of plants rhizobacteria (PGPR). Finally, we determined microbial biomass by fumigation-incubation method. On the floor of coal production, an increase in pH, the concentration of cations forming bases (Ca2 + and K+) and a high regard microbial fungi, bacteria and actinomycetes, but the microbial biomass and organic matter content was higher in the control soil, in terms of RPCP only isolated in the soil adjacent to coal production site and the control soil. The physicochemical changes produced by the warming effect of soil significantly affected the microbial community favoring the reduction or elimination of dominant groups sensitive to high temperatures that are actively involved in the dynamics of soil processesEl bosque templado de Quercus spp. en Santa Rosa constituye uno de los bosques más extensos del centro de México. En este bosque, se produce carbón vegetal de manera tradicional, por las comunidades rurales. En este trabajo se evaluó el impacto de la actividad de producción de carbón vegetal en tres sitios de muestreo del bosque, en suelo del sitio de impacto, suelo adyacente al sitio de producción de carbón vegetal y suelo control sin actividad de producción de carbón, sobre las propiedades fisicoquímicas y microbiológicas. Se determinó pH, concentración de macro- y micro- elementos, se realizó cuenta microbiana en placa calculando las unidades formadoras de colonias (UFC) de bacterias, hongos, actinomicetos y rizobacterias promotoras de crecimiento de plantas (RPCP). Por último se determinó la biomasa microbiana por el método de fumigación-incubación. En el suelo de producción de carbón se obtuvo un aumento en el pH, en la concentración de cationes formadores de bases (Ca2+ y K+) y una elevada cuenta microbiana de hongos, bacterias y actinomicetos, pero la biomasa microbiana y el contenido de materia orgánica fue mayor en el suelo no control, en cuanto a las RPCP sólo se aislaron en los suelos adyacentes a sitio de producción de carbón y en el suelo no control. Los cambios fisicoquímicos generados por el efecto del calentamiento del suelo afectaron de manera importante a la comunidad microbiana favoreciendo la reducción o eliminación de grupos dominantes sensibles a altas temperaturas que participan activamente en la dinámica de los procesos del suelo

Potenciales evocados cognitivos en pacientes con esclerosis múltiple remitente-recurrente y benigna

Introducción: Conseguir una evaluación mejor del deterioro cognitivo en la esclerosis múltiple es uno de los grandes retos actuales. Un objetivo esencial es obtener, desde diferentes aproximaciones, la valoración objetiva del déficit, y que permitan su correlación con variables fisiológicas. Objetivos: Analizar las posibles modulaciones en componentes fisiológicos del procesamiento de la información relacionados con un déficit atencional en pacientes con diversos tipos de esclerosis múltiple. Sujetos y métodos: Participaron en el presente estudio 17 pacientes con esclerosis múltiple remitente-recurrente, nueve pacientes con esclerosis múltiple benigna y 19 sujetos sanos. Se registraron sus respuestas conductuales en una tarea visuoespacial y, posteriormente, se realizó una prueba oddball auditiva en la que se registró la señal de electroencefalografía para la obtención de los potenciales evocados cognitivos. Se realizaron, asimismo, análisis de correlación entre las variables fisiológicas con variables clínicas propias del paciente. Resultados: Se encontraron un retraso en los tiempos de reacción durante el desarrollo de la tarea de Posner y un retraso en la latencia del componente P3 durante la realización de la tarea oddball en ambos grupos de pacientes con esclerosis múltiple. Conclusión: Los resultados obtenidos en este experimento confirman la presencia de deterioro atencional en ambos grupos de pacientes. La modulación exclusiva de la latencia del componente P3 sugiere que el deterioro atencional en estos pacientes al comienzo de la enfermedad se localiza en el procesamiento cognitivo central y, en principio, es producto de la desmielinización.48(9):453-8