Using Real-Time fMRI to Control a Dynamical System by Brain Activity Classification

Authors:
Anders Eklund;Henrik Ohlsson;Mats Andersson;Joakim Rydell;Anders Ynnerman;Hans Knutsson
Affiliations:
Div. of Medical Informatics, Linköping University, Sweden and Center for Medical Image Science and Visualization (CMIV),;Div. of Automatic Control, Linköping University, Sweden;Div. of Medical Informatics, Linköping University, Sweden and Center for Medical Image Science and Visualization (CMIV),;Div. of Medical Informatics, Linköping University, Sweden and Center for Medical Image Science and Visualization (CMIV),;Div. for Visual Information Technology and Applications, Linköping University, Sweden and Center for Medical Image Science and Visualization (CMIV),;Div. of Medical Informatics, Linköping University, Sweden and Center for Medical Image Science and Visualization (CMIV),
Venue:
MICCAI '09 Proceedings of the 12th International Conference on Medical Image Computing and Computer-Assisted Intervention: Part I
Year:
2009

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Abstract

We present a method for controlling a dynamical system using real-time fMRI. The objective for the subject in the MR scanner is to balance an inverted pendulum by activating the left or right hand or resting. The brain activity is classified each second by a neural network and the classification is sent to a pendulum simulator to change the force applied to the pendulum. The state of the inverted pendulum is shown to the subject in a pair of VR goggles. The subject was able to balance the inverted pendulum during several minutes, both with real activity and imagined activity. In each classification 9000 brain voxels were used and the response time for the system to detect a change of activity was on average 2-4 seconds. The developments here have a potential to aid people with communication disabilities, such as locked in people. Another future potential application can be to serve as a tool for stroke and Parkinson patients to be able to train the damaged brain area and get real-time feedback for more efficient training.