New ICT Literacies and Holistic Approaches for the Effective Learning of Languages in Tertiary Education

Abstract: This paper summarizes the evolution of different subjects of English for Specific Purposes and English for Academic and Professional Purposes. The aim here is to show a continuum of changes that have not started and nished in one subject alone but affect the whole curriculum. After the discussion section where advantages and drawbacks of the changes introduced are analyzed, we arrive at some conclusions regarding this ve year period of development in the approach to the teaching and learning of the specific or academic English language in the Escuela Universitaria de Ingeniería Técnica de Telecomunicación, Universidad Politécnica de Madrid. Resumen: Este trabajo resume la evolución que han experimentado distintas asignaturas de Inglés para Fines Especí cos e Inglés para Fines Académicos y Profesionales. El objetivo principal es mostrar cómo el esfuerzo por mejorar las asignaturas afecta al currículo como un todo y no sólo a cada una de las asignaturas. Tras el análisis de algunas de las ventajas e inconvenientes de los cambios introducidos, se alcanzan algunas conclusiones sobre la evolución que han sufrido este tipo de asignaturas durante los últimos cinco años en la Escuela Universitaria de Ingeniería Técnica de Telecomunicación, Universidad Politécnica de Madrid.

HERMES: Towards an Integrated Toolbox to Characterize Functional and Effective Brain Connectivity

The analysis of the interdependence between time series has become an important field of research in the last years, mainly as a result of advances in the characterization of dynamical systems from the signals they produce, the introduction of concepts such as generalized and phase synchronization and the application of information theory to time series analysis. In neurophysiology, different analytical tools stemming from these concepts have added to the ‘traditional’ set of linear methods, which includes the cross-correlation and the coherency function in the time and frequency domain, respectively, or more elaborated tools such as Granger Causality. This increase in the number of approaches to tackle the existence of functional (FC) or effective connectivity (EC) between two (or among many) neural networks, along with the mathematical complexity of the corresponding time series analysis tools, makes it desirable to arrange them into a unified-easy-to-use software package. The goal is to allow neuroscientists, neurophysiologists and researchers from related fields to easily access and make use of these analysis methods from a single integrated toolbox. Here we present HERMES (http://hermes.ctb.upm.es), a toolbox for the Matlab® environment (The Mathworks, Inc), which is designed to study functional and effective brain connectivity from neurophysiological data such as multivariate EEG and/or MEG records. It includes also visualization tools and statistical methods to address the problem of multiple comparisons. We believe that this toolbox will be very helpful to all the researchers working in the emerging field of brain connectivity analysis.

HERMES: towards an integrated toolbox to characterize functional and effective brain connectivity

The analysis of the interdependence between time series has become an important field of research in the last years, mainly as a result of advances in the characterization of dynamical systems from the signals they produce, the introduction of concepts such as generalized and phase synchronization and the application of information theory to time series analysis. In neurophysiology, different analytical tools stemming from these concepts have added to the ?traditional? set of linear methods, which includes the cross-correlation and the coherency function in the time and frequency domain, respectively, or more elaborated tools such as Granger Causality. This increase in the number of approaches to tackle the existence of functional (FC) or effective connectivity (EC) between two (or among many) neural networks, along with the mathematical complexity of the corresponding time series analysis tools, makes it desirable to arrange them into a unified, easy-to-use software package. The goal is to allow neuroscientists, neurophysiologists and researchers from related fields to easily access and make use of these analysis methods from a single integrated toolbox. Here we present HERMES (http://hermes.ctb.upm.es), a toolbox for the Matlab® environment (The Mathworks, Inc), which is designed to study functional and effective brain connectivity from neurophysiological data such as multivariate EEG and/or MEG records. It includes also visualization tools and statistical methods to address the problem of multiple comparisons. We believe that this toolbox will be very helpful to all the researchers working in the emerging field of brain connectivity analysis.