BESA Connectivity

Besa Connectivity 1.0

BESA Connectivity 1.0 is a software developed for neuroscience professionals, whose objective is the analysis of the cerebral connectivity from data of Electroencephalography (EEG) and Magnetoelectroencephalography (MEG). Automatically, when importing data, the BESA Connectivity 1.0 identifies connectivity patterns between electrodes, signal source regions, and dipoles. It is possible to view 2D or 3D display arrays.

There are two main types of analysis possible in BESA Connectivity 1.0: Time-frequency Analysis and Connectivity Analysis.

Time-frequency analysis: analysis based on the decomposition of EEG / MEG signals in magnitude and phase for each frequency (Delta, Theta, Alpha, Beta and Gamma). Two methodologies are available for unit visualization on individual electrodes: Complex Demodulation (based on the coevolution of the EEG / MEG signal with series of data transformations in sines and cosines) and Wavelet Analysis (like Complex Demodulation with additional output function in the domain of time).

Connectivity analysis: offers six different types of analysis of cerebral connectivity between areas, electrodes or signal source regions. Three of these analyzes are based on the phase value: coherence, imaginary coherence, and phase-locking value; while the others are based on the frequency domain: Granger causality, Direct Partial Coherence, and Directed Transfer Function.