BrainVoyager v23.0

Group Analysis of FA Maps

In order to perform a voxel-level group comparisons of FA maps, the maps must be transformed in normalized space. Due to the complexities of direction data, it is not recommended to tranform the diffusion weighted data into Talairach space but to transform FA maps calculated in original slice space or in linearly transformed 3D space. The FA maps from individual brains must be loaded in a common VMP file and the names of the subject must follow standard naming rules so that the VMP file is accepted for a one between-factor (one-way) ANOVA design. For further details, see the documentation of the single factor ANCOVA model.

BrainVoyager User's Guide
What's New
General Information
- Overview
- Main Features
- Installation
- Installing and Enabling Python
- Platform-Specific Tips
- What's New - Archive
- Credits
Getting Started
- Launching BrainVoyager
- The Graphical User Interface
- Opening and Saving Documents
- Scene Files
- DICOM to Documents
- Creating Functional Documents
- Creating Anatomical Documents
- Creating Diffusion-Weighted Documents
- DICOM to NIfTI and BIDS
- NIfTI Sidecar Files - JSON and TSV
- Anonymization and Defacing
- The 3D Viewer
Coordinates and Transformations
- Spatial Transformation Matrices
- Coordinate Systems
- NIfTI Files
- 4D NIfTI Time Course Files
- NIfTI Volume Map Files
Scripts and Plugins
- Overview
- Scripting and Automation
- The Script Development Window
- Developing User Interfaces
- Python Scripting and Development
- Plugins
- Plugin Development
BV Notebooks
- Introduction
- User Interface
- Python Code Cells
- Markdown Cellls
- Image Cells
- Image Annotator
- Animation Cells
- Embedded Viewers
- From GUI to Code
Data Analysis Manager
- Reproducible Analysis Pipelines
- BIDS Compatibility
- Create New Project
- Add Subject to Project
- Adding NIfTI and DICOM Datasets
- Workflows
- Inspecting Workflow Reports
- Data Flow Visualization
- Preprocessing Pipelines
- Group-GLM Statistics Workflow
Data Preprocessing
- Functional and Anatomical Preprocessing
- Preprocessing of Functional Data
Coregistration
- Coregistration of Functional and Anatomical Data Sets
- Initial Alignment (IA) Step
- IA Using Header-Based Coregistration
- IIHC of Functional Volume
- Fine-Tuning Alignment (FA) Step
- FA Using Gradient-Driven Affine Transformations
- Boundary-Based Registration (BBR)
- FA Using Boundary-Based Registration
- Manual IA Using Corresponding Points
- FA Using Intensity-Driven Rigid Transformations
Transformation to Normalized Space
- Overview of Brain Normalization
- MNI Normalization
- Automatic ACPC and Talairach Transformation
- Manual ACPC and Talairach Transformation
- Creation of Volume Time Course Data
- Creation of Mesh Time Course Data
  - From Volume to Mesh Time Courses
Statistical Data Analysis
- Overview of Statistical Data Analysis
- Basic Statistical Principles
- The General Linear Model (GLM)
- Time Course Normalization
- From Single Voxels to Statistical Maps
- The Multiple Comparisons Problem
- Single-Subject Analysis
- Fixed Effects, Random Effects, Mixed Effects
- Fixed Effects Group Analysis
  - Fixed Effects (FFX) Group Analysis
- Random Effects Group Analysis
Brain and Cortex Segmentation
- Overview
- Head Skin Segmentation and Reconstruction
- Removing MP2Rage Background Noise
- PD-Based Intensity Inhomogeneity Correction
- Intensity Inhomogeneity Correction
- Cortex Segmentation and Reconstruction
- Advanced Segmentation Tools
- Automatic Cortex Segmentation for BBR
- Manual Segmentation Tools
- Reconstructing Edited Brain Volumes
- Deep Neural Network Segmentation
Regions-Of-Interest
- Introduction
- Volumes-Of-Interest (VOIs)
- VOIs from Numerical Region Labels
- Patches-Of-Interest (POIs)
Cortex-Based Alignment
- Overview
- Preparing a Mesh for CBA
- Morphing Cortex to a Sphere
- Mapping Standard Sphere to Morphed Sphere
- Creating Curvature Maps for Alignment
- Pairwise Source to Target Alignment
- Group Alignment
- Visualizing Group Results
- CBA Transformation of POIs
- CBA Transformation of SMPs
- Functionally Informed CBA
Probabilistic Maps and Atlas Creation
- Introduction
- Probabilistic Maps from Volume Maps
- Probabilistic Maps from Surface Maps
- Probabilistic Maps and MPMs from VOIs
- Probabilistic Maps and MPMs from POIs
Multi-Voxel Pattern Analysis (MVPA)
- Overview
- Basic Concepts
- Trial Estimation
- Support Vector Machines (SVMs)
- Applying SVMs to ROIs
- Assessing the Significance of SVMs
- ROI-SVM Batch Processing
- Recursive Feature Elimination (RFE)
- Multivariate Searchlight Mapping
Representational Similarity Analysis
- Overview
- First-Level RSA
- Second-Level RSA
Population Receptive Field Analysis
- Introduction to pRF Analysis
- Generating Binary Stimulus Frames
- Creating pRF Model Time Courses
- pRF Estimation in Volume Space
- pRF Estimation in Cortical Surface Space
- Decoding pRF Models
Functional Connectivity Analysis
- Independent Component Analysis (ICA)
- Inter-Subject Correlation (ISC) Analysis
Cortical Thickness Analysis
- Overview
- Measuring Cortical Thickness in Volume Space
- Measuring Cortical Thickness in Cortex Space
- Group Analysis of Cortical Thickness Maps
- ROI Analysis of Cortical Thickness Maps
Laminar and Columnar Analysis
- Overview
- Using PD Scans for Inhomogeneity Correction
- Creation of High-Resolution VTCs
- VTC-VTC Alignment of Multiple Runs
- Spatial Transformation of VTC Data
- Whole-Mesh Cortical Depth Sampling
- Issues with the Whole-Mesh Sampling Approach
- Regular 2D Grids At Different Cortical Depth Levels
- Visualization of Depth Grids and Sampled Data
- Equi-Volume Depth Modelling
- Depth Grids as Flattened Volumes
Diffusion-Weighted Imaging Analysis
- Overview
- DMR Project Creation
- Diffusion Tensor Estimation
- ADC and FA Maps on Measured Slices
- From Measured Slices to 3D Space
- Diffusion Tensor Estimation in 3D Space
- ADC, FA and Color Direction Maps
- Diffusion Tensor Visualization
- Interactive Fiber Tracking
- VOI-Based Fiber Tracking
- Editing Properties of Fiber Bundles
- Group Analysis of FA Maps
EEG/MEG Analysis: The EMEG Suite
- Overview of EEG/MEG Distributed Source Analysis
- EEG/MEG Forward Models
- EEG/MEG Channel Data Preparation and Preprocessing
- EEG/MEG Channel Data Covariance Calculation
- EEG/MEG Inverse Models
- EEG/MEG Source Time Course Reconstruction
- EEG/MEG Continous Wavelet Filtering
- EEG/MEG Source Imaging and Analysis
- EEG Source Analysis with EEG-fMRI Coupling
- EEG/MEG File Formats
- EEG and MEG Channel Configurations
- EEG and MEG Raw Data Import
- EEG/MEG Channel Data Filtering
- EEG/MEG Temporal Independent Component Analysis
- Simultaneous EEG-fMRI: FMRI Artifact Detection and Removal
Useful Tools
- Overview
- Multi-Subject Contrast Maps from GLMs
- Creating VTC Masks from Statistical Maps
- Cross-VTC Intersubject Correlation
- Projecting a Mesh in a VMR
- Projecting a Mesh as Filled Volume
- Drawing POIs
- POI Path Tools
- Shortest Path Creation
- Creating Sulcal Depth Maps
Quality Assurance Tools
- Overview of Tools
- Verification of Functional Brain Coverage
Volume Rendering
- Introduction
- Anatomical Data
- Slice Cuts
- Lighting
- Volume Maps
- Volumes-Of-Interest
- Settings and Options
- High-Resolution Grid Data
Movie Studio
- Introduction
- From States to Movies
- Editing Movies
- Mesh Morphing Movies
- Surface Maps for Activation Movies
- Adding Images
- Exporting Movies
Additional Documentation
- Additional Documentation
- Exploiting the Power of GP-GPUs
- Analysis of Retinotopic Mapping Experiments
- TMS Neuronavigation