A graphics processing unit accelerated motion correction algorithm and modular system for real-time fMRI

Neuroinformatics

Volumn 11, Issue 3, 2013, Pages 291-300

  Scheinost, Dustin ^a,c   Hampson, Michelle ^b   Qiu, Maolin ^b   Bhawnani, Jitendra ^b   Constable, R Todd ^a,b,c   Papademetris, Xenophon ^a,b  

^a Yale University   (United States)

^b YALE UNIVERSITY   (United States)

^c YALE UNIVERSITY SCHOOL OF MEDICINE   (United States)

Author keywords

Graphics processing unit; Motion correction; Open source software; Real time fMRI

Indexed keywords

EID: 84881090343     PISSN: 15392791     EISSN: None     Source Type: Journal    
DOI: 10.1007/s12021-013-9176-3     Document Type: Article

References (43)

1. Bagarinao, E.; Matsuo, K.; & Nakai, T. (2003). Real-time functional MRI using a PC cluster. Concepts in Magnetic Resonance Part B: Magnetic Resonance Engineering, 19B, 14-25.
2. Caria, A.; Sitaram, R.; Veit, R.; Begliomini, C.; & Birbaumer, N. (2010). Volitional control of anterior insula activity modulates the response to aversive stimuli. A real-time functional magnetic resonance imaging study. Biological Psychiatry, 68, 425-432.
3. Caria, A.; Sitaram, R.; & Birbaumer, N. (2012). Real-Time fMRI: A tool for local brain regulation. Neuroscientist, 18, 487-501.
4. Christopher deCharms, R. (2008). Applications of real-time fMRI. Nature Reviews Neuroscience, 9, 720-729.
5. Cox, R. W.; & Jesmanowicz, A. (1999). Real-time 3D image registration for functional MRI. Magnetic Resonance in Medicine, 42, 1014-1018.
6. Cox, R. W.; Jesmanowicz, A.; & Hyde, J. S. (1995). Real-time functional magnetic resonance imaging. Magnetic Resonance in Medicine, 33, 230-236.
7. Cusack, R.; Veldsman, M.; Naci, L.; Mitchell, D. J.; & Linke, A. C. (2011). Seeing different objects in different ways: Measuring ventral visual tuning to sensory and semantic features with dynamically adaptive imaging. Human Brain Mapping, 33(2):387-397.
8. deCharms, R. C. (2007). Reading and controlling human brain activation using real-time functional magnetic resonance imaging. Trends in Cognitive Sciences, 11, 473-481.
9. deCharms, R. C.; Christoff, K.; Glover, G. H.; Pauly, J. M.; Whitfield, S.; & Gabrieli, J. D. E. (2004). Learned regulation of spatially localized brain activation using real-time fMRI. NeuroImage, 21, 436-443.
10. deCharms, R. C.; Maeda, F.; Glover, G. H.; Ludlow, D.; Pauly, J. M.; & Soneji, D. (2005). Control over brain activation and pain learned by using real-time functional MRI. Proceedings of the National Academy of Sciences of the United States of America, 102, 18626-18631.
11. Eklund, A.; Ohlsson, H.; Andersson, M.; Rydell, J.; Ynnerman, A.; & Knutsson, H. (2009). Using Real-Time fMRI to Control a Dynamical System by Brain Activity Classification. Medical Image Computing and Computer-Assisted Intervention - MICCAI, 5761, 1000-1008.
12. Esposito, F.; Seifritz, E.; Formisano, E.; Morrone, R.; Scarabino, T.; Tedeschi, G.; et al. (2003). Real-time independent component analysis of fMRI time-series. NeuroImage, 20, 2209-2224.
13. Gembris, D.; Taylor, J. G.; Schor, S.; Frings, W.; Suter, D.; & Posse, S. (2000). Functional magnetic resonance imaging in real time (FIRE): sliding-window correlation analysis and reference-vector optimization. Magnetic Resonance in Medicine, 43, 259-268.
14. Goebel, R.; Zilverstand, A.; & Sorger, B. (2011). Real-time fMRI-based brain computer interfacing for neurofeedback therapy and compensation of lost motor functions. Imaging in Medicine, 2, 407-415.
15. Hamilton, J. P.; Glover, G. H.; Hsu, J.-J.; Johnson, R. F.; & Gotlib, I. H. (2011). Modulation of subgenual anterior cingulate cortex activity with real-time neurofeedback. Human Brain Mapping, 32, 22-31.
16. Hampson, M.; Scheinost, D.; Qiu, M.; Bhawnani, J.; Lacadie, C. M.; Leckman, J. F.; et al. (2011a). Biofeedback of real-time functional magnetic resonance imaging data from the supplementary motor area reduces functional connectivity to subcortical regions. Brain Connectivity, 1, 91-98.
17. Hampson, M.; Stoica, T.; Saksa, J.; Scheinost, D.; Qiu, M.; Bhawnani, J.; Pittenger, C.; Papademetris, X.; Constable T. (2012). Real-time fMRI biofeedback targeting the orbi to frontal cortex for contamination anxiety. Journal of Visual Experiments, (59):e3535.
18. Hinds, O.; Ghosh, S.; Thompson, T. W.; Yoo, J. J.; Whitfield-Gabrieli, S.; Triantafyllou, C.; et al. (2011). Computing moment-to-moment BOLD activation for real-time neurofeedback. NeuroImage, 54, 361-368.
19. Joshi, A.; Scheinost, D.; Okuda, H.; Belhachemi, D.; Murphy, I.; Staib, L.; et al. (2011). Unified framework for development, deployment and robust testing of neuroimaging algorithms. Neuroinformatics, 9, 69-84.
20. LaConte, S. M. (2011). Decoding fMRI brain states in real-time. NeuroImage, 56, 440-454.
21. LaConte, S. M.; Peltier, S. J.; & Hu, X. P. (2007). Real-time fMRI using brain-state classification. Human Brain Mapping, 28, 1033-1044.
22. Lee, S.; Ruiz, S.; Caria, A.; Veit, R.; Birbaumer, N.; & Sitaram, R. (2011). Detection of cerebral reorganization induced by real-time fMRI feedback training of insula activation. Neurorehabilitation and Neural Repair, 25, 259-267.
23. Mathiak, K.; & Posse, S. (2001). Evaluation of motion and realignment for functional magnetic resonance imaging in real time. Magnetic Resonance in Medicine, 45, 167-171.
24. McCaig, R. G.; Dixon, M.; Keramatian, K.; Liu, I.; & Christoff, K. (2011). Improved modulation of rostrolateral prefrontal cortex using real-time fMRI training and meta-cognitive awareness. NeuroImage, 55, 1298-1305.
25. Nakai, T.; Bagarinao, E.; Matsuo, K.; Ohgami, Y.; & Kato, C. (2006). Dynamic monitoring of brain activation under visual stimulation using fMRI-The advantage of real-time fMRI with sliding window GLM analysis. Journal of Neuroscience Methods, 157, 158-167.
26. Papademetris, X.; Vives, K. P.; DiStasio, M.; Staib, L. H.; Neff, M.; Flossman, S. et al. (2006). Development of a research interface for image guided intervention: initial application to epilepsy neurosurgery. Biomedical Imaging: Nano to Macro, 2006. 3rd IEEE International Symposium on, pp. 490-493.
27. Phan, K. L.; Fitzgerald, D. A.; Gao, K.; Moore, G. J.; Tancer, M. E.; & Posse, S. (2004). Real-time fMRI of cortico-limbic brain activity during emotional processing. NeuroReport, 15, 527-532.
28. Posse, S.; Binkofski, F.; Schneider, F.; Gembris, D.; Frings, W.; Habel, U.; et al. (2001). A new approach to measure single-event related brain activity using real-time fMRI: feasibility of sensory, motor, and higher cognitive tasks. Human Brain Mapping, 12, 25-41.
29. Rota, G.; Sitaram, R.; Veit, R.; Erb, M.; Weiskopf, N.; Dogil, G.; et al. (2009). Self-regulation of regional cortical activity using real-time fMRI: the right inferior frontal gyrus and linguistic processing. Human Brain Mapping, 30, 1605-1614.
30. Rota, G.; Handjaras, G.; Sitaram, R.; Birbaumer, N.; & Dogil, G. (2011). Reorganization of functional and effective connectivity during real-time fMRI-BCI modulation of prosody processing. Brain and Language, 117, 123-132.
31. Sander, J.; & Kandrot, E. (2010). CUDA by Example: An Introduction to General-Purpose GPU Programming. Addison-Wesley Professional.
32. Shibata, K.; Watanabe, T.; Sasaki, Y.; & Kawato, M. (2011). Perceptual learning incepted by decoded fMRI neurofeedback without stimulus presentation. Science, 334, 1413-1415.
33. Sitaram, R.; Lee, S.; Ruiz, S.; Rana, M.; Veit, R.; & Birbaumer, N. (2010). Real-time support vector classification and feedback of multiple emotional brain states. NeuroImage, 56, 753-765.
34. Studholme, C.; Hill, D. L.; & Hawkes, D. J. (1996). Automated 3-D registration of MR and CT images of the head. Medical Image Analysis, 1, 163-175.
35. Thesen, S.; Heid, O.; Mueller, E.; & Schad, L. R. (2000). Prospective acquisition correction for head motion with image-based tracking for real-time fMRI. Magnetic Resonance in Medicine, 44, 457-465.
36. Tokuda, J.; Fischer, G. S.; Papademetris, X.; Yaniv, Z.; Ibanez, L.; Cheng, P.; et al. (2009). OpenIGTLink: an open network protocol for image-guided therapy environment. The International Journal of Medical Robotics and Computer Assisted Surgery, 5, 423-434.
37. Voyvodic, J. T. (1999). Real-time fMRI paradigm control, physiology, and behavior combined with near real-time statistical analysis. NeuroImage, 10, 91-106.
38. Weiskopf, N.; Mathiak, K.; Bock, S. W.; Scharnowski, F.; Veit, R.; Grodd, W.; et al. (2004). Principles of a brain-computer interface (BCI) based on real-time functional magnetic resonance imaging (fMRI). Biomedical Engineering, IEEE Transactions on, 51, 966-970.
39. Weiskopf, N.; Sitaram, R.; Josephs, O.; Veit, R.; Scharnowski, F.; Goebel, R.; et al. (2007). Real-time functional magnetic resonance imaging: methods and applications. Magnetic Resonance Imaging, 25, 989-1003.
40. Yoo, S.-S.; & Jolesz, F. A. (2002). Functional MRI for neurofeedback: feasibility studyon a hand motor task. NeuroReport, 13, 1377-1381.
41. Yoo, S.-S.; Fairneny, T.; Chen, N.-K.; Choo, S.-E.; Panych, L. P.; Park, H.; et al. (2004). Brain-computer interface using fMRI: spatial navigation by thoughts. NeuroReport, 15, 1591-1595.
42. Yoo, S.-S.; O'Leary, H. M.; Fairneny, T.; Chen, N.-K.; Panych, L. P.; Park, H.; et al. (2006). Increasing cortical activity in auditory areas through neurofeedback functional magnetic resonance imaging. NeuroReport, 17, 1273-1278.
43. Zotev, V.; Krueger, F.; Phillips, R.; Alvarez, R. P.; Simmons, W. K.; Bellgowan, P.; et al. (2011). Self-regulation of amygdala activation using real-time fMRI neurofeedback. PLoS One, 6, e24522.