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    Scientific reports. 2021 Dec 3. doi: 10.1038/s41598-021-02079-4. pii: 10.1038/s41598-021-02079-4
    Progressive modulation of resting-state brain activity during neurofeedback of positive-social emotion regulation networks.
    Krylova M1,  Skouras S2,  Razi A3,  Nicholson AA4,  Karner A5,  Steyrl D6,  Boukrina O7,  Rees G8,  Scharnowski F9,  Koush Y10
    Author information
    1Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany.
    2Department of Biological and Medical Psychology, University of Bergen, Bergen, Norway.
    3Turner Institute for Brain and Mental Health, Monash University, Clayton, Australia.
    4Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, Canada.
    5Department of Cognition, Emotion, and Methods in Psychology, University of Vienna, Vienna, Austria.
    6Department of Cognition, Emotion, and Methods in Psychology, University of Vienna, Vienna, Austria.
    7Center for Stroke Rehabilitation Research, Kessler Foundation, West Orange, NJ, USA.
    8Wellcome Centre for Human Neuroimaging, University College London, London, UK.
    9Department of Cognition, Emotion, and Methods in Psychology, University of Vienna, Vienna, Austria.
    10Department of Radiology and Biomedical Imaging, Magnetic Resonance Research Center, Yale University, 300 Cedar Street, New Haven, CT, 06519, USA. yury.koush@yale.edu.
    Abstract

    Neurofeedback allows for the self-regulation of brain circuits implicated in specific maladaptive behaviors, leading to persistent changes in brain activity and connectivity. Positive-social emotion regulation neurofeedback enhances emotion regulation capabilities, which is critical for reducing the severity of various psychiatric disorders. Training dorsomedial prefrontal cortex (dmPFC) to exert a top-down influence on bilateral amygdala during positive-social emotion regulation progressively (linearly) modulates connectivity within the trained network and induces positive mood. However, the processes during rest that interleave the neurofeedback training remain poorly understood. We hypothesized that short resting periods at the end of training sessions of positive-social emotion regulation neurofeedback would show alterations within emotion regulation and neurofeedback learning networks. We used complementary model-based and data-driven approaches to assess how resting-state connectivity relates to neurofeedback changes at the end of training sessions. In the experimental group, we found lower progressive dmPFC self-inhibition and an increase of connectivity in networks engaged in emotion regulation, neurofeedback learning, visuospatial processing, and memory. Our findings highlight a large-scale synergy between neurofeedback and resting-state brain activity and connectivity changes within the target network and beyond. This work contributes to our understanding of concomitant learning mechanisms post training and facilitates development of efficient neurofeedback training.


    © 2021. The Author(s).

    Publikations ID: 34862407
    Quelle: öffnen
     
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