Sensorimotor functional connectivity: A neurophysiological factor related to BCI performance

Brain-Computer Interfaces (BCIs) are systems that allow users to control devices using brain activity alone. However, the ability of participants to command BCIs varies from subject to subject. About 20% of potential users of sensorimotor BCIs do not gain reliable control of the system. The inefficiency to decode user's intentions requires the identification of neurophysiological factors determining “good” and “poor” BCI performers. One of the important neurophysiological aspects in BCI research is that the neuronal oscillations, used to control these systems, show a rich repertoire of spatial sensorimotor interactions. Considering this, we hypothesized that neuronal connectivity in sensorimotor areas would define BCI performance. Analyses for this study were performed on a large dataset of 80 inexperienced participants. They took part in a calibration and an online feedback session recorded on the same day. Undirected functional connectivity was computed over sensorimotor areas by means of the imaginary part of coherency. The results show that post- as well as pre-stimulus connectivity in the calibration recording is significantly correlated to online feedback performance in μ and feedback frequency bands. Importantly, the significance of the correlation between connectivity and BCI feedback accuracy was not due to the signal-to-noise ratio of the oscillations in the corresponding post and pre-stimulus intervals. Thus, this study demonstrates that BCI performance is not only dependent on the amplitude of sensorimotor oscillations as shown previously, but that it also relates to sensorimotor connectivity measured during the preceding training session. The presence of such connectivity between motor and somatosensory systems is likely to facilitate motor imagery, which in turn is associated with the generation of a more pronounced modulation of sensorimotor oscillations (manifested in ERD/ERS) required for the adequate BCI performance. We also discuss strategies for the up-regulation of such connectivity in order to enhance BCI performance

Improving motor imagery classification during induced motor perturbations

Objective.Motor imagery is the mental simulation of movements. It is a common paradigm to design brain-computer interfaces (BCIs) that elicits the modulation of brain oscillatory activity similar to real, passive and induced movements. In this study, we used peripheral stimulation to provoke movements of one limb during the performance of motor imagery tasks. Unlike other works, in which induced movements are used to support the BCI operation, our goal was to test and improve the robustness of motor imagery based BCI systems to perturbations caused by artificially generated movements.Approach.We performed a BCI session with ten participants who carried out motor imagery of three limbs. In some of the trials, one of the arms was moved by neuromuscular stimulation. We analysed 2-class motor imagery classifications with and without movement perturbations. We investigated the performance decrease produced by these disturbances and designed different computational strategies to attenuate the observed classification accuracy drop.Main results.When the movement was induced in a limb not coincident with the motor imagery classes, extracting oscillatory sources of the movement imagination tasks resulted in BCI performance being similar to the control (undisturbed) condition; when the movement was induced in a limb also involved in the motor imagery tasks, the performance drop was significantly alleviated by spatially filtering out the neural noise caused by the stimulation. We also show that the loss of BCI accuracy was accompanied by weaker power of the sensorimotor rhythm. Importantly, this residual power could be used to predict whether a BCI user will perform with sufficient accuracy under the movement disturbances.Significance.We provide methods to ameliorate and even eliminate motor related afferent disturbances during the performance of motor imagery tasks. This can help improving the reliability of current motor imagery based BCI systems

Oscillatory Source Tensor Discriminant Analysis (OSTDA): A regularized tensor pipeline for SSVEP-based BCI systems

Periodic signals called Steady-State Visual Evoked Potentials (SSVEP) are elicited in the brain by flickering stimuli. They are usually detected by means of regression techniques that need relatively long trial lengths to provide feedback and/or sufficient number of calibration trials to be reliably estimated in the context of brain-computer interface (BCI). Thus, for BCI systems designed to operate with SSVEP signals, reliability is achieved at the expense of speed or extra recording time. Furthermore, regardless of the trial length, calibration free regression-based methods have been shown to suffer from significant performance drops when cognitive perturbations are present affecting the attention to the flickering stimuli. In this study we present a novel technique called Oscillatory Source Tensor Discriminant Analysis (OSTDA) that extracts oscillatory sources and classifies them using the newly developed tensor-based discriminant analysis with shrinkage. The proposed approach is robust for small sample size settings where only a few calibration trials are available. Besides, it works well with both low- and high-number-of-channel settings, using trials as short as one second. OSTDA performs similarly or significantly better than other three benchmarked state-of-the-art techniques under different experimental settings, including those with cognitive disturbances (i.e. four datasets with control, listening, speaking and thinking conditions). Overall, in this paper we show that OSTDA is the only pipeline among all the studied ones that can achieve optimal results in all analyzed conditions

Sobrecompactación del suelo agricola parte I: influencia diferencial del peso y del número de pasadas Overcompaction of agricultural soil part I: differential influence of axle load and number of passes

Han sido objetivos principales de este trabajo, tanto el discriminar la responsabilidad de las variables independientes, peso y número de pasadas, en la distribución vertical de la compactación inducida, como obtener evidencia que permita decidir la conveniencia entre conjuntos ligeros que rueden muchas veces sobre la superficie trabajada, o conjuntos más grandes y pesados que resuelvan la tarea con menos pasajes. Se trabajó sobre un suelo de textura fina, con alta humedad presente. Las variables experimentales independientes configuraron dos tratamientos, tractor pesado y ligero, y tres diferentes número de pasadas, 1, 5 y 10, resultaron en seis subtratamientos de diferente intensidad de tráfico, más una parcela testigo sin tráfico. Los resultados no mostraron diferencias entre los tratamientos pesado y ligero, en el rango más superficial evaluado, sin embargo siempre fueron muy significativas las diferencias si se considera el rango de mayor profundidad. Disminuciones del rendimiento del pastizal del orden de 7 a 25% fueron medidas en las zonas adyacentes a las huellas, mientras que esas pérdidas ascendieron al rango de 52 a 76% dentro de la impronta dejada por las huellas del tráfico. Se pudo concluir que, el número de pasadas reiteradas sobre la misma senda, puede emular, e incluso reemplazar, al factor peso sobre el eje, en la responsabilidad principal de inducir compactaciones en el subsuelo. Diez pasadas, es el número crítico de rodadas, a partir del cual se pierden las ventajas de traficar con un tractor ligero, como alternativa a uno pesado con menos pasadas.<br>The main objectives of this research were: to determine the responsability of weight, number of passes and independent variables, on the vertical distribution of subsoil compaction and to obtain evidence to decide upon the convenience of matching equipments with light or heavy tractors, according to their differences in passes on the field. Field tests were carried out on grassland, on a typic Argiudol with a soil moisture below, but near to field capacity. The dependent experimental variable was the induced soil compaction and was related to bulk density (assessed with gamma probe), penetration resistance (measured with an electronic cone penetrometer), and remaining grassland yield, six and eight months after traffic treatments were applied. Data from two tests, with two phases of data logging were analysed, totalizing a three year period of assessment pursuit. Results did not show differences between heavy and light treatments in the shallower depth range. Nevertheless, highly significant differences were shown if the deepest range is considered. Decrease in grassland yields ranging from 7 to 25% were measured in out-of-track areas, and 52 to 76% in intrack areas. It was concluded that the number of repeated passes on the same tramlines of a light tractor, can do as much or even greater damage than the heavier tractor with fewer passes. Ten is the critical number of passes, beyond it, advantages taken from the use of a light tractor are lost