Success and failure of controlling the real-time functional magnetic resonance imaging neurofeedback signal are reflected in the striatum
Leon Skottnik, Bettina Sorger, Tabea Kamp, David Linden, Rainer Goebel, Leon Skottnik, Bettina Sorger, Tabea Kamp, David Linden, Rainer Goebel
Abstract
Introduction: Over the last decades, neurofeedback has been applied in variety of research contexts and therapeutic interventions. Despite this extensive use, its neural mechanisms are still under debate. Several scientific advances have suggested that different networks become jointly active during neurofeedback, including regions generally involved in self-regulation, regions related to the specific mental task driving the neurofeedback and regions generally involved in feedback learning (Sitaram et al., 2017, Nature Reviews Neuroscience, 18, 86).
Methods: To investigate the neural mechanisms specific to neurofeedback but independent from general effects of self-regulation, we compared brain activation as measured with functional magnetic resonance imaging (fMRI) across different mental tasks involving gradual self-regulation with and without providing neurofeedback. Ten participants freely chose one self-regulation task and underwent two training sessions during fMRI scanning, one with and one without receiving neurofeedback. During neurofeedback sessions, feedback signals were provided in real-time based on activity in task-related, individually defined target regions. In both sessions, participants aimed at reaching and holding low, medium, or high brain-activation levels in the target region.
Results: During gradual self-regulation with neurofeedback, a network of cortical control regions as well as regions implicated in reward and feedback processing were activated. Self-regulation with feedback was accompanied by stronger activation within the striatum across different mental tasks. Additional time-resolved single-trial analysis revealed that neurofeedback performance was positively correlated with a delayed brain response in the striatum that reflected the accuracy of self-regulation.
Conclusion: Overall, these findings support that neurofeedback contributes to self-regulation through task-general regions involved in feedback and reward processing.
Keywords: neurofeedback; real-time functional magnetic resonance imaging; self-regulation; striatum.
Conflict of interest statement
None declared.
© 2019 The Authors. Brain and Behavior published by Wiley Periodicals, Inc.
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References
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