Person: Panetsos Petrova, Fivos
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First Name
Fivos
Last Name
Panetsos Petrova
Affiliation
Universidad Complutense de Madrid
Faculty / Institute
Óptica y Optometría
Department
Biodiversidad, Ecología y Evolución
Area
Matemática Aplicada
Identifiers
8 results
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Item Determinación del patrón de conectividad cerebral a partir de EEG en presencia de artefactos(Mapfre Medicina, 2007) Castellanos, Nazareth P.; Makarov Slizneva, Valeriy; Sánchez Ramos, Celia; Panetsos Petrova, FivosLos diferentes estados del cerebro provocan la formación temporal de circuitos corticales cuya discriminación experimental abre el camino al estudio y caracterización de respuestas de comportamiento. En este trabajo recogemos e ilustramos en ejemplos los pasos necesarios para la determinación de patrones de conectividad funcional entre zonas corticales a partir de los registros EEG. El primer paso, la supresión de artefactos de diferentes tipos, se realiza mediante el análisis de componentes independientes que permite reconstruir la actividad neuroal subyacente al artefacto e indica en qué grado está presente el artefacto sobre cada electrodo. En el segundo paso determinamos la conectividad funcional a partir de registros preprocesados. Empleamos métodos estadísticos: la Coherencia Espectral Parcial y dDTF (direct Directed Transfer Function) que proporcionan un patrón de conectividad teniendo en cuenta el nivel de sincronización entre seáles de los electrodos.Item Neural activity in the lower pathway of the somatosensory system in the presence of silicon interfaces(First International IEEE EMBS Conference on Neural Engineering, 2003., 2003) Makarov Slizneva, Valeriy; Panetsos Petrova, Fivos; Bonacasa, V.; Wolf, LJ; Strock, JLIn this communication, we present results of experimental work carried out in the frame of the ROSANA project aiming at the investigation of the interactions between sensory inputs and the activity of Central Nervous System (CNS) neurons in the creation of the internal representations of real-world stimuli. We implanted sieve microelectrodes in the peripheral nerve of rats and we obtained functional regeneration of the sensory nerves. We recorded the electrical activity of the regenerated nerve fibers and also of the relay neurons of the first station of the somatosensory pathway. Finally we developed mathematical models of the oscillatory neurons involved in the information processing that fit well with our experimental data.Item Artificial stimulation of the peripheral nerves to generate natural-like activity in the central nervous system(Engineering in Medicine and Biology Society, 2004) Bonacasa, V.; Cepeda, I. R.; Makarov Slizneva, Valeriy; Panetsos Petrova, FivosIn the present work we study how sensory inputs conveyed by nerve fibers in the form of spatiotemporal patterns generate different responses in the central nervous system (CNS) depending on the physical characteristics of the stimulus applied and then we reproduce similar responses by means of electrical stimulation of the nervous fibersItem A method for determining neural connectivity and inferring the underlying network dynamics using extracellular spike recordings(Journal of Neuroscience Methods, 2005) Makarov Slizneva, Valeriy; Panetsos Petrova, Fivos; De Feo, ÓscarIn the present paper we propose a novel method for the identification and modeling of neural networks using extracellular spike recordings. We create a deterministic model of the effective network, whose dynamic behavior fits experimental data. The network obtained by our method includes explicit mathematical models of each of the spiking neurons and a description of the effective connectivity between them. Such a model allows us to study the properties of the neuron ensemble independently from the original data. It also permits to infer properties of the ensemble that cannot be directly obtained from the observed spike trains. The performance of the method is tested with spike trains artificially generated by a number of different neural networks. (c) 2004 Elsevier B.V. All rights reserved.Item Separation of extracellular spikes: When wavelet based methods outperform the principle component analysis(Mechanisms, Symbols, and Models Underlying Cognition, 2005) Makarov Slizneva, Valeriy; Pavlov, Alexey N.; Makarova, J.; Panetsos Petrova, Fivos; Mira, J; Álvarez, JRSpike separation is a basic prerequisite for analyzing of the cooperative neural behavior and neural code when registering extracellularly. Final performance of any spike sorting method is basically defined by the quality of the discriminative features extracted from the spike waveforms. Here we discuss two features extraction approaches: the Principal Component Analysis (PCA), and methods based on the Wavelet Transform (WT). We show that the WT based methods outperform the PCA only when properly tuned to the data, otherwise their results may be comparable or even worse. Then we present a novel method of spike features extraction based on a combination of the PCA and continuous WT. Our approach allows automatic tuning of the wavelet part of the method by the use of knowledge obtained from the PCA. To illustrate the methods strength and weakness we provide comparative examples of their performances using simulated and experimental data.Item Wavelet-analysis in application to studying spike separation and information encoding in neuron dynamics(Complex Dynamics and Fluctuations in Biomedical Photonics III, 2006) Makarov Slizneva, Valeriy; Pavlov, Alexey N.; Dumsky, Dmitry V.; Tupitsyn, Anatoly N.; Pavlova, Olga N.; Panetsos Petrova, Fivos; Tuchin, W.We study how the noise statistics influences the performance of separation of extracellularly recorded spikes by principal component analysis and wavelet-based technique. We show that the two approaches have different robustness against the frequency band of the experimental noise and an appropriate filtering of the spike waveforms can significantly improve the results of separation. For the wavelet technique we suggest filter parameters optimizing spike separation. Finally we discuss a hypothesis that information encoding in neural dynamics may sometimes be considered in terms of frequency modulation.Item Tactile information processing in the trigeminal complex of the rat(Complex Dynamics and Fluctuations in Biomedical Photonics IV, 2007) Makarov Slizneva, Valeriy; Pavlov, Alexey N.; Tupitsyn, Anatoly N.; Panetsos Petrova, Fivos; Moreno, Ángel; García-González,, Víctor; Sánchez Jiménez, Abel; Tuchin, VVWe study mechanisms of information processing in the principalis (Pr5), oralis (Sp5o) and interpolaris (Sp5i) nuclei of the trigeminal sensory complex of the rat under whisker stimulation by short air puffs. After the standard electrophysiological description of the neural spiking activity we apply a novel wavelet based method quantifying the structural stability of Bring patterns evoked by a periodic whisker stimulation. We show that the response stability depends on the puff duration delivered to the vibrissae and differs among the analyzed nuclei. Pr5 and Sp5i exhibit the maximal stability to an intermediate stimulus duration, whereas Sp5o shows "preference" for short stimuli.Item Eliminación de artefactos en el EEG basada en el análisis de componentes independientes y transformada Wavelet.(Mapfre Medicina, 2007) Castellanos, Nazareth P.; Makarov Slizneva, Valeriy; Sánchez Ramos, Celia; Panetsos Petrova, FivosLas señales electroencefalográficas (EEG) registradas en diferentes posiciones del cuero cabelludo permiten estudiar la integración de la información moto-sensorial a larga escala. Sin embargo, los artefactos del movimiento de ojos, los parpadeos, el pulso cardiaco, y de la actividad muscular suponen una gran limitación en la aplicación clínica e investigación de los EEGs. Actualmente son muy suados los métodos que conllevan la eliminación semi-automática de sementos contaminados por los artefactos aunque suponen una considerable pérdida de datos. Su aplicación se dificulta en paciente que sufren ciertos daños cerebrales con la consecuente presencia masiva de artefactos en el EEGs. El reciente el métodos de supresión de artefactos basado en el Análisis de Componentes independientes (Independent Components Análisis, ICA) ha acaparado mucha atención entre la comunidad científica. En este trabajo demostramos que la aplicación de este método permite suprimir los artefactos más comunes, pero como efecto colateral supone una pérdida de actividad cerebral que altera las propiedades espectrales de la señal neuronal sobre todo en bandas beta y gamma. Demostramos que este efecto se acentúa con el aumento de la longitud de segmentos de EEG utilizados en el análisis. Para solventar el problema proponemos una extensión del ICA basada en la transofrmada Wavelet. Utilizando registro realies y semi-simulados demostrmaos que el nuevo método, llemado wIAC, nos permite recuperar la actividad neuronal y conservar las propiedades espectrales en todas bandas de frecuencias.