HERMES
The easy way to estimate connectivity
The analysis of the interdependence between time series has become an important field of research in the last years.
This increase in the number of approaches to tackle the existence of functional (FC) or effective connectivity (EC) between two (or 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.
HERMES, includes several commonly used linear and nonlinear indexes of FC and EC, ranging from the traditional cross-correlation and coherence functions to advanced measures of interdependence based on phase or generalized synchronization, Granger causality and information theory. HERMES has been designed for the analysis of neurophysiological data from multivariate MEG, EEG and fMRI records, and it includes also visualization tools and statistical methods that deal with 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.
Niso G., Bruña R., Pereda E., Gutiérrez R., Bajo R., Maestú F., del-Pozo F. (2013). HERMES: towards an integrated toolbox to characterize functional and effective brain connectivity. NeuroInformatics, 11 (4), 405-434. doi: 10.1007/s12021-013-9186-1. (link)
HERMES is available at: http://hermes.ctb.upm.es
Guiomar Niso 