What Can the Brain Teach Us about Winemaking? An fMRI Study of Alcohol Level Preferences

Over the last few decades, wine makers have been producing wines with a higher alcohol content, assuming that they are more appreciated by consumers. To test this hypothesis, we used functional magnetic imaging to compare reactions of human subjects to different types of wine, focusing on brain regions critical for flavor processing and food reward. Participants were presented with carefully matched pairs of high- and low- alcohol content red wines, without informing them of any of the wine attributes. Contrary to expectation, significantly greater activation was found for low- alcohol than for high- alcohol content wines in brain regions that are sensitive to taste intensity, including the insula as well as the cerebellum. Wines were closely matched for all physical attributes except for alcohol content, thus we interpret the preferential response to the low- alcohol content wines as arising from top-down modulation due to the low alcohol content wines inducing greater attentional exploration of aromas and flavours. The findings raise intriguing possibilities for objectively testing hypotheses regarding methods of producing a highly complex product such as wine.

A detailed investigation of classification methods for vowel speech imagery recognition

Accurate and fast decoding of speech imagery from electroencephalographic (EEG) data could serve as a basis for a new generation of brain computer interfaces (BCIs), more portable and easier to use. However, decoding of speech imagery from EEG is a hard problem due to many factors. In this paper we focus on the analysis of the classification step of speech imagery decoding for a three-class vowel speech imagery recognition problem. We empirically show that different classification subtasks may require different classifiers for accurately decoding and obtain a classification accuracy that improves the best results previously published. We further investigate the relationship between the classifiers and different sets of features selected by the common spatial patterns method. Our results indicate that further improvement on BCIs based on speech imagery could be achieved by carefully selecting an appropriate combination of classifiers for the subtasks involved.

Estudio de señales cerebrales y aplicación a cojín elevador para discapacitados.

[ES]Estudio de obtención de señales cerebrales, creación de sensores de electroencefalograma y circuito que procesa frecuencias cerebrales para control de un prototipo de cojín elevador que ayude a personas discapacitadas a levantarse de un asiento con el fin de dar los primeros pasos en la creación de un exoesqueleto controlado cerebralmente.

Desarrollo de un prototipo de exoesqueleto básico activado con una señal cerebral.

[ES]En este documento se estudia el desarrollo de una aplicación electrónica para la ayuda a gente con movilidad reducida a través de unos sensores cerebrales que permitan el análisis de la iniciativa de la persona a realizar acciones que de otra manera no podría realizar. El concepto completo consiste en el diseño del sensor que el paciente se colocaría en la cabeza, el tratamiento de la información extraída y la actuación por medio de una solución mecánica, como un conjunto cilindro-pistón para el futuro desarrollo de un sistema de ayuda a la movilidad.