BESA Connectivity 2.0 provides optimized, user-guided workflows for time-frequency and connectivity analysis of EEG/MEG data. Multiple well-established methods are provided. They were optimized for stream-lined performance that yields results for multiple combinations of input data types, time-frequency methods, and connectivity measures. 

Particular highlights include: 

• Three time-frequency methods and six connectivity methods supported, including Imaginary Part of Coherency, Granger Causality, PDC, DTF 
• Direct comparison between conditions, time-frequency methods, connectivity methods with one or two mouse clicks 
• Support for source montages as well as sensor-level data and polygraphic channels 
• Superior visualization of results in 2D and 3D 
• Highly versatile image and video export of results 
• ASCII data result export and input support for Matlab 
• Modern 64-bit architecture optimized for multi-core processing 
• Workflow-based user guidance for optimized usability