Abstract
Brain-computer interfaces based on functional magnetic resonance imaging (fMRI-BCI) allow volitional control of anatomically specific regions of the brain. Technological advancement in higher field MRI scanners, fast data acquisition sequences, preprocessing algorithms, and robust statistical analysis are anticipated to make fMRI-BCI more widely available and applicable. This noninvasive technique could potentially complement the traditional neuroscientific experimental methods by varying the activity of the neural substrates of a region of interest as an independent variable to study its effects on behavior. If the neurobiological basis of a disorder (e.g., chronic pain, motor diseases, psychopathy, social phobia, depression) is known in terms of abnormal activity in certain regions of the brain, fMRI-BCI can be targeted to modify activity in those regions with high specificity for treatment. In this paper, we review recent results of the application of fMRI-BCI to neuroscientific research and psychophysiological treatment.
| Original language | English |
|---|---|
| Article number | 25487 |
| Journal | Computational Intelligence and Neuroscience |
| Volume | 2007 |
| DOIs | |
| Publication status | Published - 2007 |
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ASJC Scopus subject areas
- Computer Science(all)
- Mathematics(all)
- Neuroscience(all)
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FMRI brain-computer interface : A tool for neuroscientific research and treatment. / Sitaram, Ranganatha; Caria, Andrea; Veit, Ralf; Gaber, Tilman; Rota, Giuseppina; Kuebler, Andrea; Birbaumer, Niels.
In: Computational Intelligence and Neuroscience, Vol. 2007, 25487, 2007.Research output: Contribution to journal › Article
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TY - JOUR
T1 - FMRI brain-computer interface
T2 - A tool for neuroscientific research and treatment
AU - Sitaram, Ranganatha
AU - Caria, Andrea
AU - Veit, Ralf
AU - Gaber, Tilman
AU - Rota, Giuseppina
AU - Kuebler, Andrea
AU - Birbaumer, Niels
PY - 2007
Y1 - 2007
N2 - Brain-computer interfaces based on functional magnetic resonance imaging (fMRI-BCI) allow volitional control of anatomically specific regions of the brain. Technological advancement in higher field MRI scanners, fast data acquisition sequences, preprocessing algorithms, and robust statistical analysis are anticipated to make fMRI-BCI more widely available and applicable. This noninvasive technique could potentially complement the traditional neuroscientific experimental methods by varying the activity of the neural substrates of a region of interest as an independent variable to study its effects on behavior. If the neurobiological basis of a disorder (e.g., chronic pain, motor diseases, psychopathy, social phobia, depression) is known in terms of abnormal activity in certain regions of the brain, fMRI-BCI can be targeted to modify activity in those regions with high specificity for treatment. In this paper, we review recent results of the application of fMRI-BCI to neuroscientific research and psychophysiological treatment.
AB - Brain-computer interfaces based on functional magnetic resonance imaging (fMRI-BCI) allow volitional control of anatomically specific regions of the brain. Technological advancement in higher field MRI scanners, fast data acquisition sequences, preprocessing algorithms, and robust statistical analysis are anticipated to make fMRI-BCI more widely available and applicable. This noninvasive technique could potentially complement the traditional neuroscientific experimental methods by varying the activity of the neural substrates of a region of interest as an independent variable to study its effects on behavior. If the neurobiological basis of a disorder (e.g., chronic pain, motor diseases, psychopathy, social phobia, depression) is known in terms of abnormal activity in certain regions of the brain, fMRI-BCI can be targeted to modify activity in those regions with high specificity for treatment. In this paper, we review recent results of the application of fMRI-BCI to neuroscientific research and psychophysiological treatment.
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UR - http://www.scopus.com/inward/citedby.url?scp=38749151303&partnerID=8YFLogxK
U2 - 10.1155/2007/25487
DO - 10.1155/2007/25487
M3 - Article
C2 - 18274615
AN - SCOPUS:38749151303
VL - 2007
JO - Computational Intelligence and Neuroscience
JF - Computational Intelligence and Neuroscience
SN - 1687-5265
M1 - 25487
ER -