The comprehensive and powerful neuroimaging tool comes with many exciting features, such as:
A modern graphical user interface.
New data management capabilities providing a hierarchical view on your data.
New workflow tools allowing to specify, execute and document complete analyses across all subjects of an experiment.
Very fast and highly optimized 2D and 3D analysis and visualization routines.
A comprehensive set of efficient pre-processing tools, including motion correction, high-pass filtering and slice scan time correction.
Fast and precise coregistration of functional and anatomical data sets including boundary-based registration.
Automatic MNI and Talairach brain normalization tools.
Volume and cortex-based hypothesis-driven statistical data analysis using the General Linear Model (GLM).
Random-effects ANCOVA analysis for advanced multi-factorial designs and correlation with external (e.g. behavioral) variables.
Nonparametric Permutation Inference for Multi-Subject Designs including threshold-free cluster enhancement.
Cluster-size thresholding for correction of multiple comparisons for volume and surface maps.
Multi-voxel pattern analysis (MVPA) tools, including support vector machines (SVMs) and recursive feature elimination (RFE).
Distributed source EEG and MEG cortical imaging and analysis of EEG-fMRI coupling for simultaneous measurements with artifact correction.
Analysis of Diffusion-Weighted Imaging (DWI) including combined visualization of tracked fiber bundles with structural and functional MRI.
Dynamic statistical thresholding using the False Discovery Rate (FDR) approach for correction of multiple comparisons.
Retinotopic mapping analysis using population receptive field (pRF) estimation as well as classical phase-encoded analysis.
Multi-subject Volume-of-Interest (VOI) and surface Patch-of-Interest (POI) analysis.
Volume and cortex-based data-driven analysis using Independent Component Analysis (ICA) performing single run as well as group analyses.
Cortical thickness analysis for advanced morphometry.
Automatic coregistration of functional and diffusion-weighted data with high-resolution 3D anatomical data sets
Advanced methods for automatic brain segmentation, surface reconstruction, cortex inflation and flattening.
Powerful manual segmentation tools.
Cortex-based inter-subject alignment based on gyral / sulcal pattern of individual brains going beyond standard volumetric normalization approaches such as Talairach transformation.
Creation ("seeding") and visualization of EEG / MEG multiple dipole models in combination with the powerful BESA program.
Integration of volume and surface rendering with powerful tools for the creation of high-quality figures and movies.
Advanced visualizations of anatomical and functional data sets with real-time GPU-based volume rendering.
A real-time neuronavigation module as part of the TMS Neuronavigator system.
Multi-core and multi-processor support and an open architecture with documented file formats.
Cross-platform scripting support allowing to analyze the data from many subjects in batch mode.
Cross-platform C++ plugin support which makes it possible to extent the functionality of BrainVoyager.
The Windows version supports COM-based interfaces, which can be accessed with all major computer languages (e.g. C/C++, VB, Java) as well as from MATLAB.
The macOS version supports AppleScript scripting allowing to automate BrainVoyager from outside the program and to integrate it in scripted workflows with other programs.
Since BrainVoyager 20, it is possible to develop scripts and plugins using the Python language.
Optimized native executables for all major computer platforms including Windows, Linux and macOS.
BrainVoyager provides a comprehensive cross-platform solution embodied in a single product. The software allows easy exchange of data between platforms handling transparently potential byte order differences ("big endian" vs "little endian"). Data analyzed on one platform - for example Windows - can be moved to another platform - for example macOS - and processed further without any problem.
Note that with BrainVoyager 20.0, the name and version numbering of BrainVoyager has been changed. The "QX" part from previous version names has been dropped since it is no longer necessary to stress the cross-platform nature of BrainVoyager. Furthermore, version numbers now follow a yearly release cycle starting with BrainVoyager 1.0 (Windows version) released in June 1996. In order to be compatible with previous naming and licensing terms, BrainVoyager 20.X is internally also coded as BrainVoyager QX 3.X.
BrainVoyager 22.0 Now Available With Major New FeaturesWe are happy to announce the availability of BrainVoyager 22.0, which is a major release introducing important new features. The two most outstanding new features are BV Notebooks for reproducible data analysis and an advanced cortex segmentation tool that is based on a deep neural network (DNN) with an advanced "Tiramisu" architecture. These as well as other new features, enhancements and bug fixes are described in the release notes and the updated 22.0 User's Guide.
The DNN segmentation tool has been developed for high-resolution sub-millimeter data to segment grey matter with very high accuracy both along the inner (white-grey) and outer (pial) boundary. The high-quality segmentations are especially suited for cortical thickness measurements and mesoscopic (laminar and columnar) fMRI analyses.
The introduced BV Notebooks offer (script) programmers a means to write Python code to document performed analysis steps. BV Notebooks are inspired by Jupyter notebooks but they offer many BrainVoyager-specific features. Probably the most unique feature is that they support reproducible analyses also for users that do not (want to) program by converting essential GUI actions into corresponding code. Both manual as well as auto-generated code can be easily enriched with images, animations, rendered Markdown text as well as embedded BrainVoyager viewers enabling any BrainVoyager user to create rich documents.