BESA Connectivity 2.0

BESA Connectivity is a dedicated software solution for conducting time-frequency and connectivity analysis of EEG and MEG data. It provides a streamlined, workflow-based interface that guides the user through every step of the analysis process, from data loading and preprocessing to visualization and export. The software integrates a range of well-established methods and is optimized for multi-subject, multi-condition processing.

The connectivity module of BESA Connectivity 2.0 supports comprehensive analysis of functional and effective brain connectivity using both phase-based and causality-based methods. All connectivity measures can be computed on time-frequency decomposed data across multiple conditions and subjects within a single project environment.

Visualization modes are optimized for intuitive interpretation of brain network activity. The TFC grid view allows a full matrix representation of connectivity strengths across frequency and time. A 3D view enables mapping of connections either at the scalp level or within the brain, depending on the data. The circular graph view arranges all sources or sensors along a circle and displays connections for a selected frequency and time range. Channels are grouped into quadrants (left/right, anterior/posterior) to facilitate interpretation. A combined averaging mode across both time and frequency can be used to generate a single connectivity matrix representing the entire selected analysis window, ideal for connectome-style visualizations.

Additional usability features such as Freeze-Pane in the matrix view improve the user experience during exploration of large data sets. Color and size settings of sources, as defined in the BESA Solution File Format (*.bsa), are applied in the 3D renderings.

Connectivity results from all selected methods can be exported in ASCII format or as a full project export compatible with BESA Statistics, enabling seamless transition to statistical evaluation workflows.

BESA Connectivity is available as part of the BESA Research Complete package or can be licensed as a standalone module.

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Key Features

• Workflow-based analysis environment with user guidance throughout all processing steps
• Support for four time-frequency decomposition methods, including Complex Demodulation, Wavelet Transform (Morlet and Mexican Hat), and a Multitaper method using Slepian sequences
• Implementation of nine established connectivity measures, including Coherence, Imaginary Part of Coherency, Phase Locking Value, Phase Lag Index (PLI), Weighted and Directed PLI, Granger Causality, Partial Directed Coherence (PDC), and Directed Transfer Function (DTF)
• Batch processing functionality for multi-subject and multi-condition projects, supporting up to ten experimental conditions per analysis
• Grand Average calculation and visualization tools for time-frequency and connectivity results
• Direct comparison of conditions, subjects, time-frequency methods, and connectivity metrics with minimal user interaction
• Compatibility with sensor-level data (EEG/MEG and polygraphic channels) and source-space data (virtual channels from source montages)
• High-resolution result visualizations in both 2D and 3D, including matrix views, connectome-style representations, circular graph views, and 3D brain surface mappings
• Export options for image and video formats, ASCII data tables, and project structures compatible with BESA Statistics and MATLAB

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Time-Frequency Analysis

BESA Connectivity supports a range of methods for computing time-frequency representations of EEG and MEG signals. These methods include:

• Complex Demodulation, which provides a constant time-frequency resolution by convolving the signal with a series of sine and cosine waves.
• Wavelet Transform, using Morlet or Mexican Hat wavelets to extract magnitude and phase information with optimized time-frequency resolution.
• Multitaper analysis, which employs multiple orthogonal tapers based on Slepian sequences. This method provides smoothed and stable spectral estimates, especially beneficial at higher frequencies. The analysis uses a sliding time window with adaptive length depending on frequency.

The time-frequency analysis workflow includes a batch mode that allows data from multiple subjects to be loaded and processed simultaneously within a single project. Up to ten different experimental conditions can be defined. Time-frequency decompositions can be averaged across subjects and conditions, and displayed as Temporal-Spectral Evolution (TSE) or absolute amplitude/power representations. Exported results retain the selected display settings and are ready for use in subsequent statistical analyses, including integration with BESA Statistics.

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Data Integration and Export

BESA Connectivity is tightly integrated with BESA Research, ensuring compatibility with source and sensor data processed using BESA's pipeline. However, it can also process data from other software platforms, provided the input conforms to the required BESA Connectivity format.

Users can export all results, including averaged time-frequency and connectivity data, for each subject and condition. Exports are available in open file formats including ASCII and MATLAB. The software also supports image and video export of all result visualizations, making it easy to include high-quality figures in publications or presentations.