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Psychology Software Tools

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BrainVoyager

A Highly-Optimized and User-Friendly Software Package for the Analysis and Visualization of Multi-Modal Brain Imaging Data

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BrainVoyager is a highly optimized and user-friendly software package for the analysis and visualization of multi-modal brain imaging data, not only for structural and functional magnetic resonance imaging data sets but, since BV version 2.0, also for EEG and MEG data sets in combination with MR measurements. The program runs on all major computer platforms including Windows (XP, Vista), Linux (i.e., RedHat, SUSE) and Mac OS X (10.4+). In order to obtain maximum speed on each platform, BrainVoyager has been completely programmed in C++ with optimized and highly efficient statistical, numerical, and image processing routines.

The 3D graphics environment (“surface module”) has been implemented using OpenGL. The interactive graphical user interface was built using the award-winning cross-platform QT library. In combining the best cross-platform technology, BrainVoyager provides a native and responsive user interface on all supported platforms. For further details about the development of BrainVoyager, read the “Cerebral Success” press release.

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 – Windows, for example – can be moved to another platform – such as Mac OS X on PowerPC – and further processed without problem.

Note, that BrainVoyager requires a HASP cross-platform dongle for a single computer. The HASP license system allows you to use the program on Windows, Linux, and Mac OS X. With your purchase of BrainVoyager, you will receive executables for all these platforms.

The comprehensive and powerful neuroimaging tool comes with many exciting features, such as:

• Extremely fast and highly optimized 2D and 3D analysis and visualization routines
• Volume and cortex-based hypothesis-driven statistical data analysis (i.e. GLM) including conjunction and random effects analysis
• Random effects ANCOVA analysis for advanced multi-factorial designs and correlation with external (i.e. behavioral)  variables
• Dynamic statistical thresholding using the False Discovery Rate (FDR) approach for correction of multiple comparisons
• Cluster-size thresholding for correction of multiple comparisons (plugin)
• 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)
• Multi-voxel pattern analysis
• Advanced methods for automatic brain segmentation, surface reconstruction, cortex inflation, and flattening
• Cortex-based inter-subject alignment based on gyral /sulcal pattern of individual brains going beyond Talairach space
• EEG-MEG Module allows distributed analysis of EEG and data on surface reconstructions of the subject’s cortex as well as the analysis and visualization of source activities starting from channel data sets and ending up with surface mesh time-course plots
• Integration of volume and surface rendering with powerful tools for the creation of high-quality figures and movies
• A neuronavigation module as part of the TMS Neuronavigator system
• Multi-processor support and an open architecture with documented file formats
• Cross-platform scripting support allows analysis of the data from many subjects in batch mode
• Cross-platform C++ plugin support which makes it possible to extend the functionality of BrainVoyager
• Windows version (v2.x) will support COM-based interfaces, which can be accessed with all major computer languages (i.e. C/C++, VB, Java) as well as from MATLAB
• The only complete solution running natively on all major computer platforms including Windows XP/Vista, several Linux versions and Mac OS X 10.4+; on 32 bit and 64 bit computer systems

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Turbo-BrainVoyager v4.4

• Turbo-BrainVoyager User's Guide

Turbo-BrainVoyager (TBV) is a highly optimized software package for real-time analysis and advanced visualization of functional and structural magnetic resonance imaging data sets enabling neurofeedback and other brain-computer interface (BCI) applications. Turbo-BrainVoyager allows quality assurance of ongoing fMRI measurements by assessing head motion and time course drifts, and by incrementally computing statistical maps as contrasts of a General Linear Model (GLM). Incrementally calculated (statistical) maps are visualized on original slices (multi-slice view) as well as in orthographic 3D mode using original slices as well as coregistered anatomical scans of the subject. Anatomical data sets of the subject can be prepared in TBV prior to the real-time functional measurement to enable visualization of maps and regions-of-interest (ROIs) in MNI space. With the help of BrainVoyager, maps and ROIs can also be visualized on cortex (mesh) representations. TBV allows to create ROIs on any brain view and plots time courses, estimated beta values and event-related averages dynamically. TBV also allows to use machine learning tools to classify and predict distributed patterns of activity ("brain reading"). Due to its powerful computational and visualization capabilities, TBV enables advanced real-time applications such as fMRI neurofeedback, brain computer interfaces (BCIs) and activation-driven adaptive experimental designs.

TBV and the new TBV EDU version provide a sophisticated data simulation and experiment preparation mode that can be used to prepare and test protocols, and to assess expected localizer and neurofeedback results before moving to the scanner room.

Turbo-BrainVoyager is based on the BrainVoyager software package with the following unique or adjusted features:

• Easy to use graphical user interface (GUI) with essential elements to control online and offline analysis.
• Incremental processing routines written in optimized C++ code or GPU shaders, including CPU and  GPU-based 3D motion correction , and 3D spatial smoothing.
• Selection of ROIs using mouse selection or via prepared Volumes-Of-Interest (VOIs)  in normalized ( MNI or Talairach) space.
• Inspection of ROI data in  time course plots , event-related averaging plots and dynamically estimated beta values at any time during as well as after fMRI scanning.
• Detrending of displayed time courses using incrementally added confounds to GLM design matrices, such as linear and non-linear drift predictors as well as 6 predictors filled with motion parameters as they are calculated online during incremental rigid-body motion correction.
• Percent-signal change transformation of multiple detrended ROI time courses that can be directly used as cleaned input for fMRI neurofeedback or other BCI applications.
• Design matrices, contrasts and other relevant statistical data are created automatically from a defined protocol.
• Robust  incremental  GLM statistical data analysis of block- and event-related designs with multiple conditions.
• Optimized routines for multi-voxel pattern classification (MVPC) using support vector machines (SVMs).
• Instead of using a pre-dermined sequence of condition events, real-time protocols make it possible to build up the main predictors of the design matrix on the fly during scanning supporting flexible designs that depend on behavioral responses or brain activation data of participants. 
• Interactive GUI that allows to explore incoming data while running the actual measurement, including selection of multiple contrasts as well as selection of conjunction of contrasts.
• Advanced volume and surface visualizations with fast statistical updates ("movie") by using transformation matrices to project calculated statistical data from/to original image space.
• Incorporation of Volumes-Of-Interests (VOIs) in MNI (or Talairach) space to (re-)load ROIs across sessions.
• Integrated neurofeedback module to display selected and processed brain activation data to subjects as time courses or thermometer-like displays, and to save ROI data incrementally for use with custom software providing feedback.
• Integrated letter spelling BCI tool (BOLD Decoder).
• Storage of fMRI raw data on local hard drive in BrainVoyager format after functional run has been completed allowing an easy transition for in-depth offline data analysis with BrainVoyager or other fMRI software packages.
• A powerful  plugin interface  that supports integration of custom computations during real-time processing; the plugin interface has access to raw and processed (e.g. motion-corrected) data, to ROIs and statistical maps that can be processed or exported incrementally to disk. 
• Support for real-time ICA analysis implemented as a plugin using the plugin map visualization functions .

Previously recorded runs can also be reloaded and inspected at any time. Turbo-BrainVoyager is optimized for real-time analysis and is not a replacement for BrainVoyager or other offline software. There are, for example, no routines for statistical group analyses. While anatomical document creation from DICOM files, anatomical preprocessing and MNI normalization is available since TBV 4.0, some of the advanced visualization features require processing (e.g. Talairach transformation, surface mesh creation) in BrainVoyager prior to real-time analysis in TBV. Turbo-BrainVoyager 4.4 runs on Microsoft Windows 10/11, Linux (2.6+ kernel), and macOS 10.15+.

The next section provides information how to setup TBV in a scanner network environment and how to prepare neurofeedback experiments . This is followed by an overview of how to use TBV. An in-depth description of its major features is then provided in subsequent topics. If you are new to Turbo-BrainVoyager, you may also want to run the provided sample data sets  to make yourself familar with the software. It is also recommended to have a look at the release notes  describing features added in this and previous versions.

Major analysis steps implemented in Turbo-BrainVoyager are described in the publication:

Goebel, R. (2021). Analysis methods for real-time fMRI neurofeedback. In: M. Hampson (Ed.). fMRI Neurofeedback , pp. 23-55. Academic Press.

Copyright © 2002 - 2024 Rainer Goebel. All rights reserved.

• What's New - Release Notes
• General Setup
• Setup for Neurofeedback
• Running Example Data Sets
• The Graphical User Interface
• The Main Control Buttons
• Menu Functions
• Keyboard and Mouse Functions
• Brain Views
• Multi-Slice View
• Single-Slice View
• Volume View
• Anatomical Volume View
• Surface View
• Time Course Windows
• The Motion Correction Window
• The Contrasts Window
• The Information Window
• The Behavioral Data Window
• Time Courses Container
• The Protocol Dialog
• The Rename DICOM Files Dialog
• Detrending Predictors Timing
• Specification of Control Parameters
• The MasterTBV File Dialog
• The TBV Settings Dialog
• Basic Directories
• Settings for Siemens Multi-Frame Data
• Settings for Siemens MOSAIC Data
• Settings for Philips NIfTI Data
• Settings for Philips Analyze Data
• Settings for GE Signa HDxt Data
• Preprocessing and Statistics
• Multiple Runs within a Session
• GLM Confound Settings
• Enabling GPU Sinc Interpolation
• Using Anatomical Spaces
• The Neurofeedback Dialog
• ROI Activation Feedback Calculation
• Classifier Output Feedback
• Dynamic ROIs
• Semantic Neurofeedback
• Introduction
• SVM Training
• Real-Time SVM Classification
• Creating VMR Files
• Brain Extraction and IIHC
• MNI Normalization
• Coordinates and VOIs
• Creating Spherical VOIs
• Converting VOIs to ROIs
• Functional Masking
• MasterTBV Files
• TBVJ Settings File
• TBV Settings File (Deprecated)
• Contrast Definition Files
• Real-Time Protocols
• The Data Simulator
• Conditions and Regions
• Adding Confounds
• Adding Noise
• Adding Motion
• Scan Parameters
• Output Generation
• Using Plugins
• TBV - Plugin Interactions
• Writing Plugins
• General Access Functions
• GUI Functions
• Basic Project Functions
• Protocol, DM and GLM Functions
• ROI Functions
• Volume Data Access Functions
• Map Visualization Functions
• SVM Access Functions
• Running the Real-Time ICA Plugin

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• Accessibility

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Rainer Goebel

BrainVoyager Brain Tutor

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Specifications, associations, recent activity - news.

Tool & Resource news

Brain Tutor HD on iPad - It's a Kind of Magic  posted by  Rainer Goebel  on Nov 10, 2010

Brain Tutor on iPhone  posted by  Rainer Goebel  on Jan 15, 2009

Recent Activity - Files

bvbraintutor: BrainTutor HD 2.2 release

BrainTutor HD 2.2 for iPad and iPhone in iTunes store  posted by  Rainer Goebel  on Jan 22, 2013

bvbraintutor: BrainVoyager Brain Tutor HD for iPad release

BrainVoyager Brain Tutor HD on iPad in App Store  posted by  Rainer Goebel  on Nov 10, 2010

bvbraintutor: BrainVoyager Brain Tutor 2.5 release

BrainVoyager Brain Tutor 2.5 for Mac OS X  posted by  Rainer Goebel  on Nov 10, 2010

BrainVoyager Brain Tutor 2.5 for Windows  posted by  Rainer Goebel  on Nov 10, 2010

bvbraintutor: Brain Tutor 3D (for iPhone) release

Link to AppStore  posted by  Rainer Goebel  on Jan 14, 2009

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RRID : SCR_006737

PubMed Mentions : 2

News Items : 2

Total Downloads: 7652

Registered:  Oct 28, 2008

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BrainVoyager 21.2 Release Notes

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• Installation & Introduction
• Functional Analysis: Preparation
• Volume Space
• Functional Analysis: Statistics
• Surface Space
• Diffusion Weighted Imaging
• Automation & Development
• Available Tools
• Publishing Results
• Learning Material
• Turbo-BrainVoyager
• TMS Neuronavigator
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Region-Of-Interest Analysis Tool

An important way to analyze fMRI experiments is the investigation of time courses from brain areas, which were "mapped" in preceding experiments (e.g., O'Craven & Kanwisher, 2000, J Cogn Neurosci , 12 , 1013-1023): For each subject, several brain areas (i.e. V5, FFA) are determined once with a simple, standardized stimulation protocol. In subsequent main experiments, the time courses of the premapped ROIs (ROI = r egion- o f- i nterest) are statistically analyzed. This approach provides two main advantages over a normal whole-volume mapping approach, increased statistical power and spatial correspondency across subjects. The ROI-based analysis approach is statistically powerful because only a small number of a priori specified ROIs/voxels are analyzed. In addition, this approach provides homologue functional areas across subjects, which allows a statistical analysis across subjects without spatial uncertainties. A disadvantage of this approach is that the determination of homologue functional areas is somewhat subjective and might work only for a limited number of brain regions. Another disadvantage is that this approach downplays the role of other coactivated areas by narrowly focusing on the preselected ones.

BrainVoyager allows to determine ROIs based on functional analysis (VMPs) as well as through direct anatomical specification (VMRs). The ROIs are saved as a set of voxels and are also called "VOIs" (VOI = v olume- o f- i nterest). One or more defined VOIs are saved in a .VOI file. BrainVoyager's ROI Analysis Tool uses these .VOI files to access and visualize the VOIs and allows to retrieve the associated VOI time course from any functional experiment (VTC files). Depending on taste, you may want to store in one VOI file only the determined brain areas for one subject ("single-subject VOI") or for all subjects ("multi-subject VOI"). In the following, it is first described how VOIs are defined based on a statistical map and how VOIs can be applied using the Regions-Of-Interest Analysis dialog. It is then described how a VOI can be defined based on anatomical specification.

Determination of VOIs from functional clusters. To specify a VOI based on a 3D functional analysis, run any statistical test (i.e. linear correlation, GLM), which will result in a VMP (volume map) data structure. You may also load a VMP file directly or you may load a GLM file and specify a contrast. Any procedure which leads to a VMP data structure can be used for defining VOIs. In the example used here, the GLM file "ClockTaskTwoSubjects.glm" has been loaded from the "ClockTask" sample folder after invoking the Overlay Contrasts and Contribution Maps dialog. From the six listed predictors, only the first one, "Subject BS: Auditory stimulation", has been selected. The default threshold (F = 16) has been changed to F = 30 resulting in the VMP shown in the snapshot below.

The snapshot shows the right half of the VMR window (TRA and COR views, left part), the 3D Volume Tools dialg (right, upper part) and a ROI Signal Time Course window with the time course of a selected region-of-interest (right, lower part). The time course has been obtained by right-clicking in the "active" region in the Heschl gyrus of the left hemisphere. This is the standard way to select functional clusters (activated regions). The right-mouse click launches a region-growing process, which "spreads" from the selected voxel to suprathreshold neighboring voxels and stops at the boundaries of the functional cluster. This process, thus, finds all connected "significant" voxels. The region-growing process is, however, not only stopped at the borders of a functional cluster but is also limited by a specified spatial extent around the selected voxel. This range can be specified separately for the three dimensions in the Max cluster range field in the Talairach tab of the 3D Volume Tools dialog (see red rectangle in snapshot). The default range value is "10", which allows to "sample" subclusters within larger clusters. Since we wish here to select a "complete" functional cluster, the three range values have been changed to "100" voxels prior to clicking in the target region. In the next step, we now define the selected functional cluster as a volume-of-interest (VOI). The respective button to do this is located in the Options dialog of the ROI Signal Time Course window. To get there, we must first "expand" the time course window by clicking its >> button in the right lower corner. In the expanded lower section of the window, click the Options... button, which will invoke the Options dialog.

The ROI Time Course Options dialog shows in the VOI infos field information about the selected functional cluster (see upper red rectangle in dialog snapshot above). The NrOfVoxels: value reflects the size of the VOI, which normally corresponds also to the volume in cubic (Talairach) millimeter. The X: , Y: and Z: values show the center of gravity of the functional cluster in Talairach coordinates. The button to define the VOI is located within the Region-of-interest field (highlighted with the lower red rectangle). Click the Define ROI... button, which invokes the Define VOI dialog.

This dialog has two main text entry fields, the Name for VOI: and Add to file: text boxes. Enter a value for the selected functional cluster in the Name for VOI: text field. For our example, the name "Subject BS - Auditory cortex, LH" has been entered. The Add to file: text box is normally filled with the name of the last used VOI file. The specified region-of-interest (the VOI name and the coordinates of the voxels defining it) will be added to the file entered in the Add to file: field. If you have several VOI files, you can also select a particular one directly or more conveniently browse to one after clicking the Select VOI file... button. In our example we enter the file name "ClockTask.voi" (full name: C:\Program Files\BrainVoyager\Samples\ClockTask\ClockTask.voi"). If you enter just the file name without the path, the current directory will be used to define the full file name. Click the OK button to add the VOI to the specified file.

Using VOIs. The defined VOIs are accessed using the Region-Of-Interest Analysis dialog. To be able to invoke this dialog, a VMR data set has to be loaded. If you have several projects loaded in the workspace, click the title bar of the VMR data set you want to work with. For our example, we close and reload the same VMR data set. Invoke the Region-Of-Interest Analysis dialog by clicking the Region-Of-Interest analysis.. item in the Analysis menu. A fast alternative to get the dialog is to press the "R" key.

The dialog shows in the Regions-Of-Interest definition file text box the name "..\ClockTask.voi", which is the VOI file name entered in the previous section. The dialog shows always the most recently used VOI file name. If you want to switch to another VOI file, you can select it using the Browse... button next to the text box. The Regions-Of-Interest (VOIs = 3D ROIs): list box shows the name of the VOI we have defined in the previous step, "Subject BS - Auditory cortex, LH". Select the VOI with a left mouse button click. The Time course (VTC) files: list box has one entry, namely the VTC file "BS_run1_r1_pp.vtc", which was linked to the VMR when the VOI was defined. You can add other VTC files by using the Add... button (see below). You can also delete VTC files from that list by selecting a file name and then click the Delete button. Select the listed VTC file with a left mouse button click. To visualize the VOI and to show the associated time course from the selected VTC file, click the Show time course button.

The snapshot above shows the selected VOI in the 3D VMR View window. The white lines show the outline (border) of the cluster. The associated time course for that VOI for the selected VTC fiel is shown in the right lower part and matches the time course we have seen when the VOI was defined.

NOTE:  The Region-Of-Interest Analysis dialog is a "modal" dialog that means that the graphical user interface is blocked until you leave the dialog by clicking the Quit button. If you want, for example, to navigate in the VMR window, you must first quit the dialog. You can quickly reenter the dialog by pressing the "R" button. (BrainVoyager QX uses a "modeless" dialog which does not block the graphical user interface).

Besides in outline mode, a VOI can also be shown "filled", i.e. all voxels belonging to a cluster are then set to a certain color value. To change display settings, click the Options... button in the Region-Of-Interest Analysis dialog, which will invoke the ROI Analysis Options dialog as shown next.

The dialog shows the default settings. Deselect the Show Outline of ROIs option and check the Enable ROI colors option. Click the OK button. Click the Show time course button in the Region-Of-Interest Analysis dialog. You will now see the selected VOI in filled color mode. The main goal of the VOIs is to look at associated time courses from other VTC files. As an example, we will now add a VTC file from another subject who has participated in the same experiment and inspect the time course within the VOI which we have defined for subject "BS". Click the Add... button and select the file "ML_run1_r1_pp.vtc" located in the "ClockTask" sample folder. The file is added to the Time course (VTC) files: list box and automatically selected as the current one. After clicking the Show time course button, you will see a display similar to the snapshot shown below.

As depicted in the title bar of the ROI Signal Time Course window, the time course shown is now from the selected VTC file "ML_run1_r1_pp.vtc". In the outlined manner, you can use any VOI to select the time course at that region from any VTC file. As an interesting additional option, you can run a ROI GLM analysis to obtain detailed statistical information for the selected VOI.  

Additional options. You may change the name of a VOI by clicking the Rename button. You may delete a VOI from the list box by selecting it and then clicking the Delete button. If you display sequentially several time courses, you can chose whether you show each new time course in the same window or each in a new window. As default, one window appears and its content is replaced when showing the next VOI time course. If you check the In new window option, each new time course will be shown in a separate window. It is also possible to select multiple VOIs for display. Hold down the CTRL key and click on all VOIs you want to display. If you want to select a contiguous range of VOIs, select the first one, hold down the SHIFT key and then click the last one in the range. Note that in case you have selected multiple VOIs, each ones associated time course is shown in a separate window after clicking the Show time course button, irrespective of the state of the In new window option. An interesting feature can be enabled by checking the Significant voxels option. This option allows to show the time course for those voxels of a VOI only, which are above the current threshold of an overlayed statistical map (VMP). Note that this option has only an effect if a VMP is loaded. This possibility is, for example, relevant in the context of retinotopic mapping experiments. Here you might have mapped areas V1, V2, V3 etc. and then present a certain stimulus in a subsequent experiment activating a subpart of V1 and the other mapped areas. If you now select the V1 VOI, the time course averaged over the whole area would be shown in default mode. If you, however, check the Significant voxels option, only the time course of the activated subpart of V1 will be shown. An example of this feature is presented at the end of the chapter "Talairach brain atlas" .

VOI intersections and unions. Another interesting possibility is to define new VOIs based on the intersection or union of a selected set of  "source" VOIs. Simply select a set of source VOIs in the list box by holding down the CTRL key, then click the a AND b or a OR b button. Although these two buttons refer only to two VOIs (a, b), they operate also for 3 and more selected VOIs. The union operation ( a OR b button) computes a new VOI containing simply all voxels of all selected VOIs. If the selected VOIs overlap, the respective voxels are included only once in the final VOI. The intersection operation ( a AND b button) detects the set of voxels contained in all selected VOIs. These voxels then define the new VOI. Note that if the intersection set is empty, the program informs you about this situation and does not add a new VOI. After a successful execution of a union or intersection operation, the program asks you for the name of the newly defined VOI. The following example describes how the left and right auditory cortex has been combined into a new VOI by using the union operation. First the active region in the auditory cortex of the right hemisphere has been selected as described above and then added to the same VOI file ("ClockTask.voi"). The Region-Of-Interest Analysis tool now shows two VOIs:

Both VOIs have been selected by CTRL-clicking them. To create the new VOI as the union of the two source VOIs, click the a OR b button (see red rectangle above). The program presents a New VOI Name dialog asking for the name of the union VOI. Enter, for example, "Subject BS - Auditory cortex, bilateral" and click the OK button.

The new VOI finally appears in the Regions-Of-Interest list box (see snaphsot below) and can be selected and used as usual.

VOI segmentation and surface reconstruction options. VOIs are normally shown overlayed on a VMR data set. For certain applications it is desirable to have a standard VMR representation of VOIs. One such application is the surface reconstruction of functional clusters. The Region-Of-Interest Analysis dialog provides two buttons, Segment and Glass brain , to provide this functionality. The features described here are also used as part of the glass brain display option . To use the "segmentation" or "glass brain" feature, you must first select one or more VOIs in the Regions-Of-Interest list box. In our example, select the VOI "Subject BS - Auditory cortex, LH" and then press the Segment button.

The "Segment" feature creates a new VMR data set with the name "VOI_Segments.vmr" containing the selected VOI(s) as color-coded voxels. The created data set is available in the VMR viewing window as a secondary data set. The title bar now shows the primary data set ("BS_TAL.vmr") and the secondary data set ("VOI_Segments.vmr") together with an arrow indicating which data set is currently shown in the SAG, COR and TRA views. You can toggle between the two data sets using the "F8" key (for details, see section "Two VMR data sets" in chapter "Keyboard and Mouse Functions"). You can also save the secondary VMR by using the File -> Save secondary VMR... menu. With this VMR file, it is now possible to perform any standard operation. One interesting operation is surface reconstruction. If you click the Clear for rec. button in the Segmentation tab of the 3D Volume Tools dialog, the VOI gets prepared for a boundary reconstruction process. If you then switch to the surface module and click the Reconstruct button in the Create Mesh dialog, a polygon mesh representation of the VOI is created and displayed in the surface module window. The snapshot below shows the segmented VOI after the "clear for reconstruction" process on the left side and the surface representation after the "boundary reconstruction" process on the right side.

The outlined steps are performed automatically when using the "glass brain" option. Select the two VOIs "Subject BS - Auditory cortex, LH" and "Subject BS - Auditory cortex, RH" and then click the Glass brain button as indicated in the snapshot below.

The "glass brain" tool first works like the "segmentation" tool creating a VMR with the selected VOIs. It then switches to the surface module, reconstruct the boundaries of the VOIs and smoothes the resulting polygon mesh representations slightly. Note that these steps are performed for each VOI successively which allows to assign a different color to them. The program finally enables a surface representation of the (reduced) Talairach grid. This grid can be turned on or off within the 3D Axes Options dialog, which you can invoke using the Meshes -> Rendering options -> Axes and Tal grid... menu. You can also easily change the colors of each VOI by using the "surface flood fill" option. This feature is activated by clicking the Fill mode icon (see red rectangle in the snapshot below). After turning this feature on, click with the left mouse on one of the VOI clusters.

The cluster will change its color to the one currently selected in the Region Deletion and Coloring dialog. You can invoke this dialog using the Meshes -> Floodfill options... menu. Change the current color using the Fill color index: spin box (see red rectangle below). The RGB values of the selected color can be changed in the three text boxes R , G and B of the Fill color basic/convex: field. Click the OK button to close the dialog. Now the selected color is used when using the surface flood fill tool.

NOTE:  Do not forget to turn the surface flood fill tool off by clicking the Fill mode icon again after completion of coloring the VOIs.

NOTE:  The set of reconstructed VOIs is saved as one surface in the file "Clusters.srf" within the current directory allowing you to use this file in the future. To prevent overriding the file with new "surface VOIs", you might want to rename the file within Explorer or simply save it under a different name in BrainVoyager.

Reconstructed VOIs ("surface VOIs") can be visualized in combination with other surfaces. One example is the glass brain view showing reconstructed VOIs simultaneously with a surface representing the contours of the Talairach brain. Another important application is the combined visualization of cortical surfaces of an individual brain together with surface VOIs from statistical results of the same subject. This is an alternative to the standard "surface painting" visualization used with surface maps. This kind of combined visualization provides a useful additional visualization with the advantage that it does not suffer from functional sampling problems which might happen with surface maps in case that the cortex is not reconstructed correctly in some brain regions. The two snapshots below show such a combined visualization. The data used is from the "Objects" example. The first snapshot (lateral view) shows that the red functional cluster (hMT+/LO) fits nicely to the "grooves" in the cortex.

The second snapshot also shows that the functional clusters fit perfectly well into the sulci of the ventral visual cortex. This kind of visualization is, thus, also an important diagnostic tool for evaluating the quality of the functional-anatomical coregistration.

Visualization of VOIs on surfaces. VOIs are visualized as default in VMR data sets. In the previous section it was explained how VOIs can be also represented and visualized as polygon meshes in the surface module. Another possibility is to visualize VOIs on a surface. The latter approach is similar to the standard use of surface maps visualizing statistically significant regions with a separate color range on the surface. It is possible to color VOIs on the surface with the ROI Analysis tool. There is no extra button to activate this feature, it simply works automatically as soon as a surface mesh is available in the surface module. The surface has to be, of course, "touch" the voxels in the corresponding VMR data set, otherwise the VOI will not be visible. In the following example, the "Brodman area 41" VOI has ben selected (see Talairach brain atlas ) and visualized using the Show time course button. Besides a VMR data set ("CG2_TAL.vmr"), a reconstructed cortical surface ("CG2_TAL_LH_WM.vmr")  has been loaded before visualizing the VOI. As you can see in the snapshot below, the Brodmann 41 VOI is now shown both within the VMR data set as well as on the cortical surface mesh. The VOI on the surface is colored with surface fill color 1, which has been changed to a green shade (R =0, G = 255, B = 75) in the Region Deletion and Coloring Options dialog (see explanations in the previous section to change "surface fill colors").

Determination of VOIs based on anatomical specification. At the beginning of this chapter, it was explained how a VOI can be specified from functionally defined (statistical) clusters. The ROI analysis tool also allows to create VOIs based on anatomical specification: Any marked set of voxels in a VMR data set can be transformed to a VOI data structure. One way to mark voxels in a VMR data set is to use the "mouse drawing tool", which is available in the Segmentation tab of the 3D Volume Tools dialog (see red rectangle below). To activate mouse drawing, check the Enable option in the Draw with mouse field.

NOTE:  Although the drawing tool is used in this section, any method producing a set of voxels with the same color (i.e. region growing, projections from a surface) can be used to define a VOI.

After activating the "mouse drawing tool", any click in the associated VMR data set now sets the color of the selected voxel to the color value specified in the New val: text box of the Inclusion range field. The value in the New val: text box should normally be in the range of 226 - 245. The colors of these indices correspond to the 20 colors shown in the Overlay Look-Up-Table dialog ( Options -> Change overlay LUT... menu). The color indices shown in this dialog in the Color column correspond to the New val: value after subtracting "225". The default color index "240" corresponds, for example, to the color 240 - 225 = 15, which is a blue-green color shade in the default look-up-table. Since mouse clicking (including moving the mouse while holding down the left mouse button) is now used for "drawing", it can no longer be used for navigating in the VMR data set. To navigate with the mouse, you must turn off the drawing tool by unchecking the Enable button in the Draw with mouse field. Alternatively, you can use the cursor key buttons to navigate in the VMR and use the mouse for drawing. The extent of the drawing tool can be specified in the Size: text box in the Draw with mouse field. This value determines the size of the border of a square, i.e. a value of "3" would color a 3 x 3 patch. The specified size of the drawing tool is used only within the slice plane clicked. If, for example, a click is performed in the COR view, the specified size (i.e. 2 x 2) is applied within that plane but is restricted to a depth of one voxel. You can change this behavior in the Segmentation Options dialog by unchecking the In-plane option in the Mouse drawing field. If you draw primarily in one plane, you might want to enlarge the respective view by using the CTRL-T button combination. In the following example, the left hand motor cortex is marked approximately in a VMR data set ("BS_TAL.vmr") and then defined as a VOI. On the snapshot below, you see the beginning of the drawing in the "hand knob" region, which is a landmark of the cortical motor representation of the hand.

The next snapshot shows a COR view at the end of drawing (left side). The next step is to create a VOI for the marked region. Click the Options button in the Segmentation tab of the 3D Volume Tools dialog to invoke the Segmentation Options dialog.

To define the VOI, click the Def VOI button (see red rectangle). This will invoke the Define VOI dialog. From this step on, the procedure is the same as that described in the "Determination of VOIs from functional clusters" section above. Enter a name for the new VOI (for example "Subject BS - hand knob, LH") and select a .VOI file ("ClockTask.voi") to which the defined VOI should be added. Now click the OK button.

The VOI is now defined and added to the specified .VOI file. You may now turn off mouse drawing. You may also want to use the Reload all button in the Segmentation tab to "undo" the mouse drawing or simply close and reload the VMR file. To use the new VOI, invoke the Region-Of-Interest Analysis dialog. You will now see the VOI "Subject BS - hand knob, LH" in the Regions-Of-Interest list box. Select the VOI as well as a VTC file. The VTC file used in our example ("BS_run1_r1_pp.vtc") involves button presses with the right hand. Click the Show time course button. You see now the VOI in the VMR data set as well as the associated time course which shows indeed event-related motor activity.

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