Success and failure of controlling the real-time functional magnetic resonance imaging neurofeedback signal are reflected in the striatum

Research output: Contribution to journalArticleAcademicpeer-review

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.

Original languageEnglish
Article numbere01240
Number of pages15
JournalBrain and Behavior
Volume9
Issue number3
Early online date20 Feb 2019
DOIs
Publication statusPublished - Mar 2019

Keywords

  • neurofeedback
  • real-time functional magnetic resonance imaging
  • self-regulation
  • striatum
  • ANTERIOR CINGULATE CORTEX
  • DORSAL STRIATUM
  • FMRI NEUROFEEDBACK
  • VENTRAL STRIATUM
  • REWARD
  • METAANALYSIS
  • PREDICTION
  • SYSTEMS
  • REPRESENTATION
  • INTEGRATION

Cite this

@article{3e4533cb5c874d2e87dcb4b3a5ab11a7,
title = "Success and failure of controlling the real-time functional magnetic resonance imaging neurofeedback signal are reflected in the striatum",
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, ANTERIOR CINGULATE CORTEX, DORSAL STRIATUM, FMRI NEUROFEEDBACK, VENTRAL STRIATUM, REWARD, METAANALYSIS, PREDICTION, SYSTEMS, REPRESENTATION, INTEGRATION",
author = "Leon Skottnik and Bettina Sorger and Tabea Kamp and David Linden and Rainer Goebel",
note = "{\circledC} 2019 The Authors. Brain and Behavior published by Wiley Periodicals, Inc.",
year = "2019",
month = "3",
doi = "10.1002/brb3.1240",
language = "English",
volume = "9",
journal = "Brain and Behavior",
issn = "2162-3279",
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TY - JOUR

T1 - Success and failure of controlling the real-time functional magnetic resonance imaging neurofeedback signal are reflected in the striatum

AU - Skottnik, Leon

AU - Sorger, Bettina

AU - Kamp, Tabea

AU - Linden, David

AU - Goebel, Rainer

N1 - © 2019 The Authors. Brain and Behavior published by Wiley Periodicals, Inc.

PY - 2019/3

Y1 - 2019/3

N2 - 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.

AB - 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.

KW - neurofeedback

KW - real-time functional magnetic resonance imaging

KW - self-regulation

KW - striatum

KW - ANTERIOR CINGULATE CORTEX

KW - DORSAL STRIATUM

KW - FMRI NEUROFEEDBACK

KW - VENTRAL STRIATUM

KW - REWARD

KW - METAANALYSIS

KW - PREDICTION

KW - SYSTEMS

KW - REPRESENTATION

KW - INTEGRATION

U2 - 10.1002/brb3.1240

DO - 10.1002/brb3.1240

M3 - Article

C2 - 30790474

VL - 9

JO - Brain and Behavior

JF - Brain and Behavior

SN - 2162-3279

IS - 3

M1 - e01240

ER -