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.


Program Features

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:

  • Easy to use graphical user interface (GUI) with the possibility to visualize the data and statistical results (maps) in multi-slice and single slice view, on 3D data sets in AC-PC or Talairach space, and on surface rendered views of the cortical sheet.
  • Interactive GUI during real-time processing allowing to explore the incoming data while running the actual measurement; during real-time processing it is, for example, possible to zoom into single slices, to browse with a 3D cursor in the 3D view, to rotate and zoom 3D models and to select Regions-Of-Interest (ROIs) to display time courses and event-related averaging plots.
  • New routines for incremental statistical data analysis (recursive least-squares GLM) and incremental event-related averaging.
  • Automatic creation of design matrices including confound predictors capturing low frequency drifts.
  • Useful contrasts are automatically generated from provided protocols but contrasts can also be specified by the user.
  • Fast incremental 3D motion correction, spatial Gaussian smoothing and drift removal using the design matrix.
  • Statistical threshold and cluster size for overlaid contrast maps can be changed any time during real-time analysis.
  • Statistical information from multiple overlaid contrast maps can be optionally visualized with separate colors; this "colors code contrasts" mode also highlights voxels with significant conjunctions (intersections) with special colors.
  • Import and export of Volumes-Of-Interest in AC-PC or Talairach space, which is useful for advanced applications, e.g. neurofeedback.
  • Storage of fMRI raw data on local hard drive in BrainVoyager format after functional run has been completed allowing an easy transition to in-depth data analysis with BrainVoyager QX or other fMRI software packages.

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, 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 visual 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 as 6 parameter time course used for rigid-body translation and rotation and optionally as confound predictors during real-time analysis.

Advanced Real-Time Applications: Neurofeedback and BCI Studies

Turbo-BrainVoyager has been used for advanced real-time applications, especially neurofeedback and brain-computer-interface studies. In the video above, Rainer Goebel introduces these advanced real-time fMRI applications. More details can be found in the selected list of publications below.

B Sorger, R Goebel (2020). Real-time fMRI for brain-computer interfacing. In: Ramsey NF, and Millán JDR, (eds). Brain-Computer Interfaces. San Diego: Elsevier BV, 168, 289-302.

Hohenfeld C, Kuhn H, Müller C, Nellessen N, Ketteler S, Heinecke A, Goebel R, Shah NJ, Schulz JB, Reske M, Reetz K. (2020). Changes in brain activation related to visuo-spatial memory after real-time fMRI neurofeedback training in healthy elderly and Alzheimer's disease. Behav Brain Res. 381, 112435

Goebel R (2019). What’s in the thermometer? Towards semantic neurofeedback at 7 Tesla. Talk in chair symposium of Real-Time Functional Imaging and Neurofeedback (rtFIN) Conference, Maastricht, NL, Dec 9.

Kaas A, Goebel R, Valente G, Sorger B.(2019). Topographic Somatosensory Imagery for Real-Time fMRI Brain-Computer Interfacing.Front Hum Neurosci, 13, 427.

Krause F, Benjamins C, Eck J, Lührs M, van Hoof R, Goebel R (2019). Active head motion reduction in magnetic resonance imaging using tactile feedback. Hum Brain Mapp, 40, 4026-4037.

Skottnik L, Sorger B, Kamp T, Linden D, Goebel R (2019). Success and failure of controlling the real-time functional magnetic resonance imaging neurofeedback signal are reflected in the striatum. Brain Behav, 9, e01240.

Lührs M, Riemenschneider B, Eck J, Andonegui AB, Poser BA, Heinecke A, Krause F, Esposito F, Sorger B, Hennig J, Goebel R (2019). The potential of MR-Encephalography for BCI/Neurofeedback applications with high temporal resolution. Neuroimage, 194, 228-243.

Mehler DMA, Sokunbi MO, Habes I, Barawi K, Subramanian L, Range M, Evans J, Hood K, Lührs M, Keedwell P, Goebel R, Linden DEJ (2018). Targeting the affective brain-a randomized controlled trial of real-time fMRI neurofeedback in patients with depression. Neuropsychopharmacology, 43, 2578-2585.

Neyedli HF, Sampaio-Baptista C, Kirkman MA, Havard D, Lührs M, Ramsden K, Flitney DD, Clare S, Goebel R, Johansen-Berg H (2018). Increasing Lateralized Motor Activity in Younger and Older Adults using Real-time fMRI during Executed Movements. Neuroscience, 378, 165-174.

Zilverstand A, Sorger B, Slaats-Willemse D, Kan CC, Goebel R, Buitelaar JK (2017). fMRI Neurofeedback Training for Increasing Anterior Cingulate Cortex Activation in Adult Attention Deficit Hyperactivity Disorder. An Exploratory Randomized, Single-Blinded Study. PLoS One, 12, e0170795.

Lührs M, Sorger B, Goebel R, Esposito F (2017). Automated selection of brain regions for real-time fMRI brain-computer interfaces. J Neural Eng, 14, 016004.

Krause F, Benjamins C, Lührs M, Eck J, Noirhomme Q, Rosenke M, Brunheim S, Sorger B, Goebel R (2017). Real-time fMRI-based self-regulation of brain activation across different visual feedback presentations. Brain-computer interfaces, 4, 87-101.

Zilverstand A, Sorger B, Sarkheil P, Goebel R (2015). fMRI neurofeedback facilitates anxiety regulation in females with spider phobia. Front Behav Neurosci, 9, 148.

Sarkheil P, Zilverstand A, Kilian-Hütten N, Schneider F, Goebel R, Mathiak K (2015). fMRI feedback enhances emotion regulation as evidenced by a reduced amygdala response. Behav Brain Res, 281, 326-332.

Zilverstand A, Sorger B, Zimmermann J, Kaas A, Goebel R. (2014). Windowed Correlation: A Suitable Tool for Providing Dynamic fMRI-Based Functional Connectivity Neurofeedback on Task Difficulty. PLoS One, 9, e85929.

Sorger, B., Reithler, J., Dahmen, B., Goebel, R. (2012). A Real-time fMRI-based Spelling Device Immediately Enabling Robust Motor-independent Communication. Current Biology, 22, 1333-1338.

Linden, D.E.J., Habes, I., Johnston, S.J., Linden, S., Tatineni, R., Subramanian L., Sorger, B., Healy, D., Goebel, R. (2012) Real-time Self-regulation of Emotion Networks in Patients with Depression. PLOS One, 7, e38115.

Subramanian, L. Hindle, J.V., Johnston, S., Roberts, M.V., Husain, M., Goebel, R., Linden, D. (2011). Real-Time Functional Magnetic Resonance Imaging Neurofeedback for Treatment of Parkinson’s Disease. The Journal of Neuroscience, 31, 16309-16317.

Johnston, S., Linden, D.E., Healy, D., Goebel, R., Habes, I., Boehm, S.G. (2011). Upregulation of emotion areas through neurofeedback with a focus on positive mood. Cognitive, Affective and Behavioral Neuroscience, 11, 44-51.

Sorger B, Dahmen B, Reithler J, Gosseries O, Maudoux A, Laureys S, Goebel R (2009). Another kind of 'BOLD Response': answering multiple-choice questions via online decoded single-trial brain signals. Prog Brain Res, 177, 275-292.

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.