BESA Statistics

$3,551.20
SKU
NS-7388

BESA is the most versatile and comprehensive EEG/MEG reader available on the market.

BESA STATS includes: Easy intuitive user interface, preliminary statistics, cross subject statistics based on permutation tests, visualization of significant data clusters and many more. BESA STATS is a standalone software package and does not require any other BESA packages.

For further configurations, multiple licenses or standalone licenses please contact us!

BESA is the most widely used software for source analysis and dipole localization in EEG and MEG research. BESA Research has been developed on the basis of 30 years experience in human brain research by Michael Scherg, University of Heidelberg, and Patrick Berg, University of Konstanz. BESA Research is a highly versatile and user-friendly Windows® program with optimized tools and scripts to preprocess raw or averaged data for source analysis. All important aspects of source analysis are displayed in one window for immediate selection of a wide range of tools. BESA Research provides fast and easy hypothesis testing, a variety of source analysis algorithms, integration with MRI and fMRI, standardized realistic head models (FEM) as well as the possibility to import individual head models (FEM) generated by BESA MRI 2.0. Source coherence, a unique feature for viewing brain activity BESA Research transforms surface signals into brain activity using source montages derived from multiple source models. This allows displaying ongoing EEG/MEG, single epochs, and averages with much higher spatial resolution. The Source Coherence Module provides an extremely fast and user-friendly implementation of time-frequency analysis based on complex demodulation. Users can create event-related time-frequency displays of power, amplitude, or event-related (de)synchronization and coherence for the current montage using brain sources or surface channels. Induced and evoked activities can be separated. Source coherence analysis reveals the functional connectivity between brain regions by reducing the volume conduction effects seen in surface coherence.

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