Turbo-BrainVoyager (TBV) is a highly optimized, easy to use software package for the real-time analysis and dynamic visualization of functional magnetic resonance imaging data sets. Turbo-BrainVoyager allows to observe the working brain "online" by incrementally computing statistical maps as contrasts of a General Linear Model (GLM). The program also performs real-time pre-processing, including 3D motion correction, spatial Gaussian smoothing and temporal filtering (drift removal). TBV visualizes the data in various formats including a multi-slice (matrix) view, a single (zoomed) slice view and a anatomical volume view. With the help of BrainVoyager QX, the data can also be visualized on 3D data sets in AC-PC and Talairach space as well as on rendered meshes of the cortical sheet. Statistical results as shown as real-time activation movies on the rotatable and zoomable 3D brain models. Regions-Of-Interest (ROIs) can be easily defined using any of the provided visualizations. The raw time courses as well as event-related averaging plots are shown immediately for any of the defined ROIs and are updated as new data becomes available. Besides standard real-time tasks, such as quality assurance, the powerful computational and visualization capabilities of the proram allow advanced applications, such as neurofeedback and neurosurgical monitoring.
In quality assurance applications, head motion correction and the inspection of statistical maps and time courses help to decide whether an ongoing fMRI measurement works as expected. If problems are detected, the scan can be repeated immediately while the subject or patient is still in the scanner. Besides analyzing single functional runs, the program also allows multi-run analysis across all functional scans recorded within a session if all runs use the same slice positioning parameters. Previously recorded runs can also be reloaded and inspected at any time. Turbo-BrainVoyager can be used as a stand-alone software. It can also be used as part of the Eloquence and IFIS systems.
Because of its speed, the program can read, analyze and visualize incoming data immediately when it becomes available: All computations necessary for processing a functional volume (3D image created from all slices arriving within one TR) are completed in less than a second on standard computer hardware allowing true real-time analysis. Turbo-BrainVoyager is based on the BrainVoyager QX software package with many new or modified features including:
Turbo-BrainVoyager is not a replacement for BrainVoyager QX since it does not contain its full functionality. There are, for example, no routines for head and cortex segmentation, Talairach transformation and between-subject statistical data analysis. Turbo-BrainVoyager runs on Microsoft Windows 98/NT/2000/XP, Linux, and Mac OS X. If you are interested in the program, send an email to "support_at_BrainVoyager_dot_com".
More details about Turbo-BrainVoyager con be found in the online Turbo-BrainVoyager User's Guide and in a movie of the analysis of a faces/houses (FFA/PPA localizer) experiment. The movie shows how the user selects various regions of interest in the vidual cortex and how different display modes (multi-slice, single slice, 3D anatomical, cortex models) can be selected. The movie also shows how an event-related averaging plot is constantly updated during real-time analysis. The two upper time course panels on the right side show the time series of selected ROIs while the third lower panel shows the result of 3D motion detection (6 curves for rigid-body translation and rotation).
Turbo-BrainVoyager has been used for advanced real-time applications, especially neurofeedback studies, with the aim to learn how the human brain is able to change its own activity state at will. The first results of this work is described in the following paper:
Weiskopf, N., Veit, R., Erb, M., Mathiak, K., Grodd, W., Goebel, R. & Birbaumer, N. (2003). Physiological self-regulation of regional brain activity using real-time functional magnetic resonance imaging (fMRI): methodology and exemplary data. NeuroImage, 19, 577-586.