Classification of Imaginary Motor Task from Electroencephalographic Signals: A Comparison of Feature Selection Methods and Classification Algorithms / Clasificación de una Motricidad Imaginaria por medio de Señales Electroencefalográficas: Una Comparación de Métodos de Selección de Características y Algoritmos de Clasificación

Abstract: In this work, a Brain Computer interface able to decode imagery motor task from EEG is presented. The method uses time-frequency representation of the brain signal recorded in different regions of the brain to extract important features. Principal Component Analysis and Sequential Forward Selection methods are compared in their ability to represent the feature set in a compact form, removing at the same time unnecessary information. Finally, two method based on machine learning are implemented for the task of classification. Results show that it is possible to decode the mental activity of the subjects with accuracy above 80%. Furthermore, visualization of the main components extracted from the brain signal allow for physiological insights on the activity that take place in the sensorimotor cortex during execution of imaginary movement of different parts of the body.

Resumen: En este trabajo es presentada una Interfaz Cerebro Computadora que tiene la capacidad de decodificar actividades motrices. El método utiliza representación en el dominio de la frecuencia y el tiempo de las señales del cerebro grabadas en distintas regiones de este mismo, con el fin de extraer características importantes. Los métodos: Análisis de Componentes Principales y Selección Secuencial, son comparados en términos de su capacidad para representar características de la señal de una forma compacta, removiendo de esta forma, información innecesaria. Finalmente, dos métodos basados en aprendizaje de máquinas fueron implementados para la clasificación de actividades motrices utilizando solo las señales cerebrales. Los resultados muestran que es posible decodificar la actividad mental en los sujetos con una precisión superior al 80%. Además, la visualización de las componentes principales extraídas de las señales del cerebro permite un analísis de la actividad que toma lugar en la corteza cerebral sensorimotora durante la ejecución de la imaginación de movimientos de distintas partes del cuerpo.

Pulse-train Stimulation of Primary Somatosensory Cortex Blocks Pain Perception in Tail Clip Test

Human studies of brain stimulation have demonstrated modulatory effects on the perception of pain. However, whether the primary somatosensory cortical activity is associated with antinociceptive responses remains unknown. Therefore, we examined the antinociceptive effects of neuronal activity evoked by optogenetic stimulation of primary somatosensory cortex. Optogenetic transgenic mice were subjected to continuous or pulse-train optogenetic stimulation of the primary somatosensory cortex at frequencies of 15, 30, and 40 Hz, during a tail clip test. Reaction time was measured using a digital high-speed video camera. Pulse-train optogenetic stimulation of primary somatosensory cortex showed a delayed pain response with respect to a tail clip, whereas no significant change in reaction time was observed with continuous stimulation. In response to the pulse-train stimulation, video monitoring and local field potential recording revealed associated paw movement and sensorimotor rhythms, respectively. Our results show that optogenetic stimulation of primary somatosensory cortex at beta and gamma frequencies blocks transmission of pain signals in tail clip test.