Principles of a brain-computer interface (BCI) based on real-time functional magnetic resonance imaging (fMRI)

Principles of a brain-computer interface (BCI) based on real-time functional magnetic resonance imaging (fMRI)

A brain-computer interface (BCI) based on functional magnetic resonance imaging (fMRI) records noninvasively activity of the entire brain with a high spatial resolution. We present a fMRI-based BCI which performs data processing and feedback of the hemodynamic brain activity within 1.3 s. Using this...

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Bibliographic Details
Published in:IEEE transactions on biomedical engineering Vol. 51; no. 6; pp. 966 - 970
Main Authors: Weiskopf, N., Mathiak, K., Bock, S.W., Scharnowski, F., Veit, R., Grodd, W., Goebel, R., Birbaumer, N.
Format: Journal Article
Language:English
Published: United States IEEE 01-06-2004
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Adult
Biofeedback, Psychology - methods
Biofeedback, Psychology - physiology
Biomedical imaging
Blood
Brain - physiology
Brain computer interfaces
Brain Mapping - methods
Delay
Electroencephalography
Feasibility Studies
Feedback - physiology
Female
Hemodynamics
Hippocampus - physiology
Humans
Image Interpretation, Computer-Assisted - methods
Magnetic resonance imaging
Magnetic Resonance Imaging - methods
Male
Motor Cortex - physiology
Neurofeedback
Online Systems
Psychology
Reproducibility of Results
Sensitivity and Specificity
Spatial resolution
User-Computer Interface
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Description
Summary:A brain-computer interface (BCI) based on functional magnetic resonance imaging (fMRI) records noninvasively activity of the entire brain with a high spatial resolution. We present a fMRI-based BCI which performs data processing and feedback of the hemodynamic brain activity within 1.3 s. Using this technique, differential feedback and self-regulation is feasible as exemplified by the supplementary motor area (SMA) and parahippocampal place area (PPA). Technical and experimental aspects are discussed with respect to neurofeedback. The methodology now allows for studying behavioral effects and strategies of local self-regulation in healthy and diseased subjects.
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ISSN:0018-9294
1558-2531
DOI:10.1109/TBME.2004.827063