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

Niso Galán, Julia Guiomar; Bruña Fernandez, Ricardo; Pereda, Ernesto; Gutiérrez Díez, Ricardo; Bajo Breton, Ricardo; Maestú, Fernando y Pozo Guerrero, Francisco del (2013). HERMES: Towards an Integrated Toolbox to Characterize Functional and Effective Brain Connectivity. "Neuroinformatics", v. 11 (n. 4); pp. 405-434. ISSN 1539-2791. https://doi.org/10.1007/s12021-013-9186-1.

Descripción

Título: HERMES: Towards an Integrated Toolbox to Characterize Functional and Effective Brain Connectivity
Autor/es:
  • Niso Galán, Julia Guiomar
  • Bruña Fernandez, Ricardo
  • Pereda, Ernesto
  • Gutiérrez Díez, Ricardo
  • Bajo Breton, Ricardo
  • Maestú, Fernando
  • Pozo Guerrero, Francisco del
Tipo de Documento: Artículo
Título de Revista/Publicación: Neuroinformatics
Fecha: Octubre 2013
Volumen: 11
Materias:
Escuela: Centro de Tecnología Biomédica (CTB) (UPM)
Departamento: Otro
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

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Resumen

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.

Más información

ID de Registro: 21459
Identificador DC: http://oa.upm.es/21459/
Identificador OAI: oai:oa.upm.es:21459
Identificador DOI: 10.1007/s12021-013-9186-1
URL Oficial: http://link.springer.com/article/10.1007%2Fs12021-013-9186-1
Depositado por: Memoria Investigacion
Depositado el: 05 Nov 2013 19:03
Ultima Modificación: 01 Nov 2014 23:56
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