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, mainly as a result of advances in the characterization of dynamical systems from the signals they produce, and the introduction of concepts such as Generalized (GS) and Phase synchronization (PS) and information theory as applied to time series analysis. In neurophysiology, different analytical tools stemming from these concepts have added to the “traditional” set of linear methods, which include the cross-correlation function (in the time domain), the coherence function (in the frequency domain) or more elaborated tools such as Granger Causality. The LNCyC developed HERMES, a toolbox for the Matlab® environment designed to study functional and effective brain connectivity from neurophysiological data such as multivariate EEG and/or MEG records. HERMES also provides visualization tools and statistical methods to address the problem of multiple comparisons