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Abstract #2246

Connectivity-Based Neurofeedback: Dynamic Causal Modeling for Real-Time FMRI.

Yury Koush1, 2, Maria Joao Rosa3, Fabien Robineau4, 5, Klaartje Heinen6, Nikolaus Weiskopf7, Patrik Vuilleumier4, 5, Dimitri Van de Ville, 28, Frank Scharnowski1, 2

1Department of Radiology and Medical Informatics, CIBM, University of Geneva , Geneva, Switzerland; 2Institute of Bioengineering, cole Polytechnique Fdrale de Lausanne, Lausanne, Switzerland; 3Computer Science Department, University College London, London, United Kingdom; 4Department of Neuroscience, CMU, University of Geneva, Geneva, Switzerland; 5Geneva Neuroscience Center, Geneva, Switzerland; 6Institute of Cognitive Neuroscience, University College London, London, United Kingdom; 7Wellcome Trust Centre for Neuroimaging, Institute of Neurology,, University College London, London, United Kingdom; 8Department of Radiology and Medical Informatics, CIBM, University of Geneva, Geneva, Switzerland

Neurofeedback based on real-time fMRI is a novel technique that allows to train voluntary control over brain activity. So far, this technique was limited to training localized brain activity within a region of interest. Here, we overcome this limitation by presenting real-time dynamic causal modelling in order to provide neurofeedback information based on connectivity between brain areas rather than activity within a brain area. Being able to train network activity is an important extension of the neurofeedback approach that will contribute to its development as a promising research tool, and will open up a whole new range of medical applications.

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Keywords

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