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Learning control over emotion networks through connectivity-based neurofeedback

Koush, Yury, Meskaldji, Djalel-E., Pichon, Swann, Rey, Gwladys, Rieger, Sebastian W., Linden, David, Van De Ville, Dimitri, Vuilleumier, Patrik and Scharnowski, Frank 2017. Learning control over emotion networks through connectivity-based neurofeedback. Cerebral Cortex 27 (2) , pp. 1193-1202. 10.1093/cercor/bhv311

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Most mental functions are associated with dynamic interactions within functional brain networks. Thus, training individuals to alter functional brain networks might provide novel and powerful means to improve cognitive performance and emotions. Using a novel connectivity-neurofeedback approach based on functional magnetic resonance imaging (fMRI), we show for the first time that participants can learn to change functional brain networks. Specifically,we taught participants control over a key component of the emotion regulation network, in that they learned to increase top-down connectivity from the dorsomedial prefrontal cortex, which is involved in cognitive control, onto the amygdala, which is involved in emotion processing. After training, participants successfully self-regulated the top-down connectivity between these brain areas even without neurofeedback, and this was associated with concomitant increases in subjective valence ratings of emotional stimuli of the participants. Connectivity-based neurofeedback goes beyond previous neurofeedback approaches, which were limited to training localized activity within a brain region. It allows to noninvasively and nonpharmacologically change interconnected functional brain networks directly, thereby resulting in specific behavioral changes. Our results demonstrate that connectivitybased neurofeedback training of emotion regulation networks enhances emotion regulation capabilities. This approach can potentially lead to powerful therapeutic emotion regulation protocols for neuropsychiatric disorders.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Medicine
Publisher: Oxford University Press
ISSN: 1047-3211
Date of First Compliant Deposit: 12 March 2018
Date of Acceptance: 17 December 2015
Last Modified: 25 Apr 2018 01:26

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