Browsing by Autor "Mario Valderrama"

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Altered Oscillatory Dynamics of CA1 Parvalbumin Basket Cells during Theta–Gamma Rhythmopathies of Temporal Lobe Epilepsy
(Society for Neuroscience, 2016) Diego Lopez‐Pigozzi; François Laurent; Jorge R. Brotons‐Mas; Mario Valderrama; Manuel Valero; Iván Fernández‐Lamo; Elena Cid; Daniel Gómez-Domínguez; Beatriz Gal; Liset Menéndez de la Prida
Recent reports in human demonstrate a role of theta-gamma coupling in memory for spatial episodes and a lack of coupling in people experiencing temporal lobe epilepsy, but the mechanisms are unknown. Using multisite silicon probe recordings of epileptic rats engaged in episodic-like object recognition tasks, we sought to evaluate the role of theta-gamma coupling in the absence of epileptiform activities. Our data reveal a specific association between theta-gamma (30-60 Hz) coupling at the proximal stratum radiatum of CA1 and spatial memory deficits. We targeted the microcircuit mechanisms with a novel approach to identify putative interneuronal types in tetrode recordings (parvalbumin basket cells in particular) and validated classification criteria in the epileptic context with neurochemical identification of intracellularly recorded cells. In epileptic rats, putative parvalbumin basket cells fired poorly modulated at the falling theta phase, consistent with weaker inputs from Schaffer collaterals and attenuated gamma oscillations, as evaluated by theta-phase decomposition of current-source density signals. We propose that theta-gamma interneuronal rhythmopathies of the temporal lobe are intimately related to episodic memory dysfunction in this condition.
Efectos de la estimulación eléctrica habenular en la modulación de respuestas emocionales en ratas Wistar
(Catholic University of Colombia, 2018) María Herrera; Natalia Guisselle Rubio; Juan Pablo Quintanilla; Víctor Manuel Huerta; Alejandro Osorio-Forero; Melissa Andrea Cárdenas Molano; Mario Valderrama; Fernando P. Cárdenas
A pesar del amplio uso de la estimulación cerebral profunda para controlar patologías neurológicas y neuropsiquiátricas, su mecanismo de acción aún no es claramente conocido, y existen pocos estudios sistemáticos que relacionen la variación de parámetros de estimulación eléctrica (frecuencia, intensidad, duración del pulso) y la ejecución comportamental. La habénula es una estructura reguladora de respuestas emocionales diana en tratamientos para dolor crónico y depresión, pero la relación entre su estimulación crónica y el desempeño animal en pruebas conductuales no se ha establecido con claridad. Con el objetivo de evaluar el efecto emocional de la estimulación habenular crónica, en este estudio se utilizaron ratas Wistar que recibieron estimulación habenular a intensidad baja (10-80 µA) o alta (120-260 µA) y frecuencia baja (80-150 Hz) o alta (240- 380 Hz): BIBF-AIBF-BIAF-AIAF, durante 15 minutos a lo largo de tres días consecutivos. Al cuarto día, se hizo la evaluación en un laberinto elevado en cruz y en campo abierto. Los resultados indican un efecto de tipo ansiolítico en el tratamiento BIAF, en comparación con BIBF y AIBF (aumento del número de entradas, porcentaje de tiempo en brazos abiertos y de la distancia recorrida en ellos), efecto que no se explica por cambios en la locomotricidad (distancia recorrida en los brazos cerrados y la exploración en el campo abierto). Se concluye que el parámetro frecuencia posee mayor impacto sobre el efecto comportamental que la intensidad
Efectos de la estimulación eléctrica habenular en la modulación de respuestas emocionales en ratas Wistar
(Catholic University of Colombia, 2018) María Herrera; Natalia Guisselle Rubio; Juan Pablo Quintanilla; Víctor Manuel Huerta; Alejandro Osorio-Forero; Melissa Andre Cárdenas Molano; Karen Corredor Páez; Mario Valderrama; Fernando P. Cárdenas
A pesar del amplio uso de la estimulación cerebral profunda para controlar patologías neurológicas y neuropsiquiátricas, su mecanismo de acción aún no es claramente conocido, y existen pocos estudios sistemáticos que relacionen la variación de parámetros de estimulación eléctrica (frecuencia, intensidad, duración del pulso) y la ejecución comportamental. La habénula es una estructura reguladora de respuestas emocionales diana en tratamientos para dolor crónico y depresión, pero la relación entre su estimulación crónica y el desempeño animal en pruebas conductuales no se ha establecido con claridad. Con el objetivo de evaluar el efecto emocional de la estimulación habenular crónica, en este estudio se utilizaron ratas Wistar que recibieron estimulación habenular a intensidad baja (10-80 µA) o alta (120-260 µA) y frecuencia baja (80-150 Hz) o alta (240- 380 Hz): BIBF-AIBF-BIAF-AIAF, durante 15 minutos a lo largo de tres días consecutivos. Al cuarto día, se hizo la evaluación en un laberinto elevado en cruz y en campo abierto. Los resultados indican un efecto de tipo ansiolítico en el tratamiento BIAF, en comparación con BIBF y AIBF (aumento del número de entradas, porcentaje de tiempo en brazos abiertos y de la distancia recorrida en ellos), efecto que no se explica por cambios en la locomotricidad (distancia recorrida en los brazos cerrados y la exploración en el campo abierto). Se concluye que el parámetro frecuencia posee mayor impacto sobre el efecto comportamental que la intensidad ?lo que puede explicar algunos hallazgos paradójicos previos?, que los parámetros utilizados no poseen efecto ansiogénico, y que los efectos potencialmente ansiogénicos de la estimulación a baja frecuencia y el papel de los sistemas dopaminérgicos y serotoninérgicos encontrados deben ser estudiados en futuras investigaciones.
Open Source EEG Platform with Reconfigurable Features for Multiple-Scenarios
(Institute of Advanced Engineering and Science (IAES), 2018) Juan Manuel López; Fabián Andrés González; Juan Carlos Bohórquez; Jorge Bohórquez; Mario Valderrama; Fredy Segura-Quijano
Electroencephalogram (EEG) acquisition systems are widely used as diagnostic and research tools. This document shows the implementation of a reconfigurable family of three affordable 8-channels, 24 bits of resolution, EEG acquisition systems intended for a wide variety of research purposes. The three devices offer a modular design and upgradability, permitting changes in the firmware and software. Due to the nature of the Analog Front-End (AFE) used, no high-pass analog filters were implemented, allowing the capture of very low frequency components. Two systems of the family, called “RF-Brain” and “Bluetooth-Brain”, were designed to be light and wireless, planned for experimentation where movement of the subject cannot be restricted. The sample rate in these systems can be configured up to 2000 samples per second (SPS) for the RF-Brain and 250 SPS for the Bluetooth-Brain when the 8 channels are used. If fewer channels are required, the sampling frequency can be higher (up to 4 kSPS or 2 kSPS for 1 channel for RF-Brain and Bluetooth-Brain respectively). The third system, named “USB-Brain”, is a wired device designed for purposes requiring high sampling frequency acquisition and general purpose ports, with sampling rates up to 4 kSPS.
Open Source EEG Platform with Reconfigurable Features for Multiple-Scenarios
(Institute of Advanced Engineering and Science (IAES), 2018) Juan Manuel López; Fabián Andrés González; Juan Carlos Bohórquez; Jorge Bohórquez; Mario Valderrama; Fredy Segura-Quijano
Electroencephalogram (EEG) acquisition systems are widely used as diagnostic and research tools. This document shows the implementation of a reconfigurable family of three affordable 8-channels, 24 bits of resolution, EEG acquisition systems intended for a wide variety of research purposes. The three devices offer a modular design and upgradability, permitting changes in the firmware and software. Due to the nature of the Analog Front-End (AFE) used, no high-pass analog filters were implemented, allowing the capture of very low frequency components. Two systems of the family, called “RF-Brain” and “Bluetooth-Brain”, were designed to be light and wireless, planned for experimentation where movement of the subject cannot be restricted. The sample rate in these systems can be configured up to 2000 samples per second (SPS) for the RF-Brain and 250 SPS for the Bluetooth-Brain when the 8 channels are used. If fewer channels are required, the sampling frequency can be higher (up to 4 kSPS or 2 kSPS for 1 channel for RF-Brain and Bluetooth-Brain respectively). The third system, named “USB-Brain”, is a wired device designed for purposes requiring high sampling frequency acquisition and general purpose ports, with sampling rates up to 4 kSPS.
Seizure Prediction: A Visual Approach
(2018) Raúl Reina Molina; Andrés Hernández; Mario Valderrama
Activity preceding the onset of epileptic seizures has been an elusive subject for neuroscience research, without a clear grasp of what patterns might be responsible. In this work, we present an out of the box approach to this problem, trying to mimic the visual inspection process that a trained physician might do to locate the beginning of a pre-ictal state in an EEG plot. We explore different data labeling methods for the posterior training of a Convolutional Neural Network, taking into account only visual characteristics for classification. Ten second images (300x400 px) were synthesized from scalp EEG recordings belonging to 10 epileptic patients from the public Physionet CHB-MIT database. A tortuosity measure was taken for each one-second window, for each channel (23 channels in 10-20 bipolar configuration). Unsupervised clustering methods in conjunction with the mean and the standard deviation of the tortuosity sets were used to identify pre-ictal states; interictal states were selected according to the same proximity criteria used for the Kaggles Melbourne University AES/MathWorks/NIH Seizure Prediction Challenge. The proposed labelling method indentified 28 posible pre-ictal states across 10 patients. Data from pre-ictal states and interictal states was used to train, and test, a Convolutional Neural Network classifier for each of the 8 patients selected. A classification accuracy of 99.29% was achieved for the best patient; however, an accuracy of 46.93% was also obtained for the worst patient. Mean performance across patients was 76.03%, a 52.07% improvement over chance.