- About this Journal ·
- Abstracting and Indexing ·
- Aims and Scope ·
- Article Processing Charges ·
- Articles in Press ·
- Author Guidelines ·
- Bibliographic Information ·
- Citations to this Journal ·
- Contact Information ·
- Editorial Board ·
- Editorial Workflow ·
- Free eTOC Alerts ·
- Publication Ethics ·
- Reviewers Acknowledgment ·
- Submit a Manuscript ·
- Subscription Information ·
- Table of Contents
Computational Intelligence and Neuroscience
Volume 2007 (2007), Article ID 25487, 10 pages
fMRI Brain-Computer Interface: A Tool for Neuroscientific Research and Treatment
1Institute of Medical Psychology and Behavioral Neurobiology, Eberhard-Karls-University of Tübingen, Tübingen, 72074, Germany
2Max Planck Institute for Biological Cybernetics, P.O. Box 21 69, Tübingen 72076, Germany
3Institute for Natural Language Processing, University of Stuttgart, Stuttgart 70174, Germany
4National Institute of Health (NIH), NINDS, Human Cortical Physiology, Bethesda, MD 20892-1428, USA
Received 28 February 2007; Revised 2 August 2007; Accepted 18 September 2007
Academic Editor: Shangkai Gao
Copyright © 2007 Ranganatha Sitaram et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
- N. Birbaumer, N. Ghanayim, T. Hinterberger, et al., “A spelling device for the paralysed,” Nature, vol. 398, no. 6725, pp. 297–298, 1999.
- J. P. Donoghue, “Connecting cortex to machines: recent advances in brain interfaces,” Nature Neuroscience, vol. 5, pp. 1085–1088, 2002.
- J. R. Wolpaw, N. Birbaumer, D. J. McFarland, G. Pfurtscheller, and T. M. Vaughan, “Brain-computer interfaces for communication and control,” Clinical Neurophysiology, vol. 113, no. 6, pp. 767–791, 2002.
- M. A. L. Nicolelis, “Brain-machine interfaces to restore motor function and probe neural circuits,” Nature Reviews Neuroscience, vol. 4, no. 5, pp. 417–422, 2003.
- J. R. Wolpaw and D. J. McFarland, “Control of a two-dimensional movement signal by a noninvasive brain-computer interface in humans,” Proceedings of the National Academy of Sciences of the United States of America, vol. 101, no. 51, pp. 17849–17854, 2004.
- L. R. Hochberg and J. P. Donoghue, “Sensors for brain-computer interfaces: options for turning thought into action,” IEEE Engineering in Medicine and Biology Magazine, vol. 25, no. 5, pp. 32–38, 2006.
- N. Weiskopf, R. Sitaram, O. Josephs, et al., “Real-time functional magnetic resonance imaging: methods and applications,” Magnetic Resonance Imaging, vol. 25, no. 6, pp. 989–1003, 2007.
- A. Caria, R. Veit, R. Sitaram, et al., “Regulation of anterior insular cortex activity using real-time fMRI,” NeuroImage, vol. 35, no. 3, pp. 1238–1246, 2007.
- N. K. Logothetis, J. Pauls, M. Augath, T. Trinath, and A. Oeltermann, “Neurophysiological investigation of the basis of the fMRI signal,” Nature, vol. 412, no. 6843, pp. 150–157, 2001.
- A. Shmuel, M. Augath, A. Oeltermann, and N. K. Logothetis, “Negative functional MRI response correlates with decreases in neuronal activity in monkey visual area V1,” Nature Neuroscience, vol. 9, no. 4, pp. 569–577, 2006.
- S.-S. Yoo and F. A. Jolesz, “Functional MRI for neurofeedback: feasibility study on a hand motor task,” NeuroReport, vol. 13, no. 11, pp. 1377–1381, 2002.
- S. Posse, D. Fitzgerald, K. Gao, et al., “Real-time fMRI of temporolimbic regions detects amygdala activation during single-trial self-induced sadness,” NeuroImage, vol. 18, no. 3, pp. 760–768, 2003.
- N. Weiskopf, R. Veit, M. Erb, et al., “Physiological self-regulation of regional brain activity using real-time functional magnetic resonance imaging (fMRI): methodology and exemplary data,” NeuroImage, vol. 19, no. 3, pp. 577–586, 2003.
- R. C. DeCharms, K. Christoff, G. H. Glover, J. M. Pauly, S. Whitfield, and J. D. E. Gabrieli, “Learned regulation of spatially localized brain activation using real-time fMRI,” NeuroImage, vol. 21, no. 1, pp. 436–443, 2004.
- N. Weiskopf, F. Scharnowski, R. Veit, R. Goebel, N. Birbaumer, and K. Mathiak, “Self-regulation of local brain activity using real-time functional magnetic resonance imaging (fMRI),” Journal of Physiology, vol. 98, no. 4–6, pp. 357–373, 2004.
- S.-S. Yoo, T. Fairneny, N.-K. Chen, et al., “Brain-computer interface using fMRI: spatial navigation by thoughts,” NeuroReport, vol. 15, no. 10, pp. 1591–1595, 2004.
- R. C. DeCharms, F. Maeda, G. H. Glover, et al., “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, vol. 102, no. 51, pp. 18626–18631, 2005.
- R. Sitaram, A. Caria, R. Veit, T. Gaber, A. Kuebler, and N. Birbaumer, “Real-time fMRI based brain-computer interface enhanced by interactive virtual worlds,” in Proceedings of the 45th Annual Meeting Society for Psychophysiological Research, Lisbon, Portugal, 2005.
- A. Caria, R. Veit, T. Gaber, R. Sitaram, A. Kuebler, and N. Birbaumer, “Can we learn to increase our emotional involvement? real-time fMRI of anterior cingulate cortex during emotional processing,” in Human Brain Mapping, Florence, Italy, June 2006.
- G. Rota, R. Sitaram, R. Veit, N. Weiskopf, N. Birbaumer, and G. Dogil, “ fMRI-neurofeedback for operant conditioning and neural plasticity investigation: a study on the physiological self-induced regulation of the BA 45,” in Proceedings of the Cognitive Neuroscience Conference, San Francisco, Calif, USA, 2006.
- R. Veit, H. Flor, M. Erb, et al., “Brain circuits involved in emotional learning in antisocial behavior and social phobia in humans,” Neuroscience Letters, vol. 328, no. 3, pp. 233–236, 2002.
- C. H. Wagner and M. L. Barrett, 2004, Published online by PsycExtra.
- J.-D. Haynes and G. Rees, “Decoding mental states from brain activity in humans,” Nature Reviews Neuroscience, vol. 7, no. 7, pp. 523–534, 2006.
- S. M. Laconte, S. J. Peltier, and X. P. Hu, “Real-time fMRI using brain-state classification,” in Human Brain Mapping, 2006.
- R. Goebel, “Cortex-based real-time fMRI,” NeuroImage, vol. 13, no. 6, p. 129, 2001.
- C. T. W. Moonen and P. A. Bandettini, Eds., Functional MRI, Springer, Berlin, Germany, 2000.
- T. E. Feinberg and M. J. Farah, Eds., Behavioral Neurology and Neuropsychology, McGraw-Hill, New York, NY, USA, 2nd edition, 2003.
- B. Rockstroh, T. Elbert, N. Birbaumer, and W. Lutzenberger, “Biofeedback-produced hemispheric asymmetry of slow cortical potentials and its behavioural effects,” International Journal of Psychophysiology, vol. 9, no. 2, pp. 151–165, 1990.
- F. Pulvermüller, B. Mohr, H. Schleichert, and R. Veit, “Operant conditioning of left-hemispheric slow cortical potentials and its effect on word processing,” Biological Psychology, vol. 53, no. 2-3, pp. 177–215, 2000.
- T. Egner and J. H. Gruzelier, “Ecological validity of neurofeedback: modulation of slow wave EEG enhances musical performance,” NeuroReport, vol. 14, no. 9, pp. 1221–1224, 2003.
- M. M. Bradley and P. J. Lang, “Measuring emotion: the self-assessment manikin and the semantic differential,” Journal of Behavior Therapy and Experimental Psychiatry, vol. 25, no. 1, pp. 49–59, 1994.
- A. Caria, R. Veit, R. Sitaram et al., “Regulation of anterior insular cortex activity using real-time fMRI,” Neuroimage, vol. 35, no. 3, pp. 1238–1246, 2007.
- G. Dogil, I. Frese, H. Haider, D. RÖhm, and W. Wokurek, “Where and how does grammatically geared processing take place-and why is broca’s area often involved. A coordinated fMRI/ERBP study of language processing,” Brain and Language, vol. 89, no. 2, pp. 337–345, 2004.
- F. Tong, K. Nakayama, J. T. Vaughan, and N. Kanwisher, “Binocular rivalry and visual awareness in human extrastriate cortex,” Neuron, vol. 21, no. 4, pp. 753–759, 1998.
- T. Fuchs, N. Birbaumer, W. Lutzenberger, J. H. Gruzelier, and J. Kaiser, “Neurofeedback treatment for attention-deficit/hyperactivity disorder in children: a comparison with methylphenidate,” Applied Psychophysiology Biofeedback, vol. 28, no. 1, pp. 1–12, 2003.
- B. Kotchoubey, U. Strehl, C. Uhlmann, et al., “Modification of slow cortical potentials in patients with refractory epilepsy: a controlled outcome study,” Epilepsia, vol. 42, no. 3, pp. 406–416, 2001.
- H. Kato, M. Izumiyama, H. Koizumi, A. Takahashi, and Y. Itoyama, “Near-infrared spectroscopic topography as a tool to monitor motor reorganization after hemiparetic stroke: a comparison with functional MRI,” Stroke, vol. 33, no. 8, pp. 2032–2036, 2002.
- B. H. Dobkin, “Functional MRI: a potential physiologic indicator for stroke rehabilitation interventions,” Stroke, vol. 34, no. 5, pp. e23–e28, 2003.
- F. Scharnowski, N. Weiskopf, K. Mathiak, et al., “Self-regulation of the BOLD signal of supplementary motor area (SMA) and parahippocampal place area (PPA): fMRI-neurofeedbackand its behavioural consequences,” in Proceedings of 10th International Conference on Functional Mapping of the Human Brain, Budapest, Hungary, 2004.
- S. de Vries and T. Mulder, “Motor imagery and stroke rehabilitation: a critical discussion,” Journal of Rehabilitation Medicine, vol. 39, no. 1, pp. 5–13, 2007.
- F. Maeda, “Learning to explicitly control activation in a localized brain region through real-time fMRI feedback based training, with result impact on pain perception,” in Proceedings of the Society for Neuroscience, pp. 601–604, Washington, DC, USA, 2004.
- K. L. Phan, D. A. Fitzgerald, K. Gao, G. J. Moore, M. E. Tancer, and S. Posse, “Real-time fMRI of cortico-limbic brain activity during emotional processing,” NeuroReport, vol. 15, no. 3, pp. 527–532, 2004.
- S. Anders, M. Lotze, M. Erb, W. Grodd, and N. Birbaumer, “Brain activity underlying emotional valence and arousal: a response-related fMRI study,” Human Brain Mapping, vol. 23, no. 4, pp. 200–209, 2004.
- E. Viding, “On the nature and nurture of antisocial behavior and violence,” Annals of the New York Academy of Sciences, vol. 1036, pp. 267–277, 2004.
- E. Viding, “Annotation: understanding the development of psychopathy,” Journal of Child Psychology and Psychiatry and Allied Disciplines, vol. 45, no. 8, pp. 1329–1337, 2004.
- P. A. Brennan and A. Raine, “Biosocial bases of antisocial behavior: psychophysiological, neurological, and cognitive factors,” Clinical Psychology Review, vol. 17, no. 6, pp. 589–604, 1997.
- R. J. R. Blair, “Neurobiological basis of psychopathy,” British Journal of Psychiatry, vol. 182, pp. 5–7, 2003.
- J. LeDoux, “The emotional brain, fear, and the amygdala,” Cellular and Molecular Neurobiology, vol. 23, no. 4-5, pp. 727–738, 2003.
- N. Birbaumer, R. Veit, M. Lotze, et al., “Deficient fear conditioning in psychopathy: a functional magnetic resonance imaging study,” Archives of General Psychiatry, vol. 62, no. 7, pp. 799–805, 2005.
- K. J. Friston, L. Harrison, and W. Penny, “Dynamic causal modelling,” NeuroImage, vol. 19, no. 4, pp. 1273–1302, 2003.
- S. LaConte, S. Strother, V. Cherkassky, J. Anderson, and X. Hu, “Support vector machines for temporal classification of block design fMRI data,” NeuroImage, vol. 26, no. 2, pp. 317–329, 2005.
- J. Mouräo-Miranda, A. L. W. Bokde, C. Born, H. Hampel, and M. Stetter, “Classifying brain states and determining the discriminating activation patterns: support vector machine on functional MRI data,” NeuroImage, vol. 28, no. 4, pp. 980–995, 2005.
- F. Esposito, E. Seifritz, E. Formisano, et al., “Real-time independent component analysis of fMRI time-series,” NeuroImage, vol. 20, no. 4, pp. 2209–2224, 2003.
- S. Thesen, O. Heid, E. Mueller, and L. R. Schad, “Prospective acquisition correction for head motion with image-based tracking for real-time fMRI,” Magnetic Resonance in Medicine, vol. 44, no. 3, pp. 457–465, 2000.