Meta-analysis of real-time fMRI neurofeedback studies using individual participant data: How is brain regulation mediated?

An increasing number of studies using real-time fMRI neurofeedback have demonstrated that successful regulation of neural activity is possible in various brain regions. Since these studies focused on the regulated region(s), little is known about the target-independent mechanisms associated with neurofeedback-guided control of brain activation, i.e. the regulating network. While the specificity of the activation during self-regulation is an important factor, no study has effectively determined the network involved in self-regulation in general. In an effort to detect regions that are responsible for the act of brain regulation, we performed a post-hoc analysis of data involving different target regions based on studies from different research groups. We included twelve suitable studies that examined nine different target regions amounting to a total of 175 subjects and 899 neurofeedback runs. Data analysis included a standard first- (single subject, extracting main paradigm) and second-level (single subject, all runs) general linear model (GLM) analysis of all participants taking into account the individual timing. Subsequently, at the third level, a random effects model GLM included all subjects of all studies, resulting in an overall mixed effects model. Since four of the twelve studies had a reduced field of view (FoV), we repeated the same analysis in a subsample of eight studies that had a well-overlapping FoV to obtain a more global picture of self-regulation. The GLM analysis revealed that the anterior insula as well as the basal ganglia, notably the striatum, were consistently active during the regulation of brain activation across the studies. The anterior insula has been implicated in interoceptive awareness of the body and cognitive control. Basal ganglia are involved in procedural learning, visuomotor integration and other higher cognitive processes including motivation. The larger FoV analysis yielded additional activations in the anterior cingulate cortex, the dorsolateral and ventrolateral prefrontal cortex, the temporo-parietal area and the visual association areas including the temporo-occipital junction. In conclusion, we demonstrate that several key regions, such as the anterior insula and the basal ganglia, are consistently activated during self-regulation in real-time fMRI neurofeedback independent of the targeted region-of-interest. Our results imply that if the real-time fMRI neurofeedback studies target regions of this regulation network, such as the anterior insula, care should be given whether activation changes are related to successful regulation, or related to the regulation process per se. Furthermore, future research is needed to determine how activation within this regulation network is related to neurofeedback success.

[1]  Sven Haller,et al.  Real-time fMRI feedback training may improve chronic tinnitus , 2010, European Radiology.

[2]  H. Critchley,et al.  Neural systems supporting interoceptive awareness , 2004, Nature Neuroscience.

[3]  James J Prisciandaro,et al.  Real-time fMRI in the treatment of nicotine dependence: a conceptual review and pilot studies. , 2013, Psychology of addictive behaviors : journal of the Society of Psychologists in Addictive Behaviors.

[4]  Christian Paret,et al.  Down-regulation of amygdala activation with real-time fMRI neurofeedback in a healthy female sample , 2014, Front. Behav. Neurosci..

[5]  M. Farah,et al.  A functional MRI study of mental image generation , 1997, Neuropsychologia.

[6]  Niels Birbaumer,et al.  Volitional Control of Anterior Insula Activity Modulates the Response to Aversive Stimuli. A Real-Time Functional Magnetic Resonance Imaging Study , 2010, Biological Psychiatry.

[7]  Hubert Preissl,et al.  The Obese Brain Athlete: Self-Regulation of the Anterior Insula in Adiposity , 2012, PloS one.

[8]  Niels Birbaumer,et al.  Real-time fMRI brain computer interfaces: Self-regulation of single brain regions to networks , 2014, Biological Psychology.

[9]  Kevin A. Johnson,et al.  Intermittent “Real‐time” fMRI Feedback Is Superior to Continuous Presentation for a Motor Imagery Task: A Pilot Study , 2012, Journal of neuroimaging : official journal of the American Society of Neuroimaging.

[10]  J. Pillai Functional Connectivity. , 2017, Neuroimaging clinics of North America.

[11]  E. Procyk,et al.  Anterior cingulate error‐related activity is modulated by predicted reward , 2005, The European journal of neuroscience.

[12]  Gary H. Glover,et al.  Control of nucleus accumbens activity with neurofeedback , 2014, NeuroImage.

[13]  Jerzy Bodurka,et al.  Prefrontal Control of the Amygdala during Real-Time fMRI Neurofeedback Training of Emotion Regulation , 2013, PloS one.

[14]  R. Goebel,et al.  Real-Time Functional Magnetic Resonance Imaging Neurofeedback for Treatment of Parkinson's Disease , 2011, The Journal of Neuroscience.

[15]  W. K. Simmons,et al.  Self-Regulation of Amygdala Activation Using Real-Time fMRI Neurofeedback , 2011, PloS one.

[16]  Klaas E. Stephan,et al.  Neurofeedback-mediated self-regulation of the dopaminergic midbrain , 2013, NeuroImage.

[17]  Karl J. Friston,et al.  Temporal Difference Models and Reward-Related Learning in the Human Brain , 2003, Neuron.

[18]  K. Doya,et al.  Representation of Action-Specific Reward Values in the Striatum , 2005, Science.

[19]  Lawrence P. Panych,et al.  Increasing cortical activity in auditory areas through neurofeedback functional magnetic resonance imaging , 2006, Neuroreport.

[20]  Niels Birbaumer,et al.  Using real-time fMRI to learn voluntary regulation of the anterior insula in the presence of threat-related stimuli. , 2012, Social cognitive and affective neuroscience.

[21]  Dimitri Van De Ville,et al.  Self-regulation of inter-hemispheric visual cortex balance through real-time fMRI neurofeedback training , 2014, NeuroImage.

[22]  Jong-Hwan Lee,et al.  Real-time fMRI-based neurofeedback reinforces causality of attention networks , 2012, Neuroscience Research.

[23]  Stefan Pollmann,et al.  A universal role of the ventral striatum in reward-based learning: Evidence from human studies , 2014, Neurobiology of Learning and Memory.

[24]  Wolfgang Grodd,et al.  Regulation of anterior insular cortex activity using real-time fMRI , 2007, NeuroImage.

[25]  O. Blanke,et al.  Neural Basis of Embodiment: Distinct Contributions of Temporoparietal Junction and Extrastriate Body Area , 2006, The Journal of Neuroscience.

[26]  Stephan G. Boehm,et al.  Upregulation of emotion areas through neurofeedback with a focus on positive mood , 2011, Cognitive, affective & behavioral neuroscience.

[27]  M. Lotze,et al.  Motor imagery , 2006, Journal of Physiology-Paris.

[28]  Vinod Menon,et al.  Functional connectivity in the resting brain: A network analysis of the default mode hypothesis , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[29]  Li Yao,et al.  Modulation of functional network with real-time fMRI feedback training of right premotor cortex activity , 2014, Neuropsychologia.

[30]  V. Menon,et al.  A critical role for the right fronto-insular cortex in switching between central-executive and default-mode networks , 2008, Proceedings of the National Academy of Sciences.

[31]  John D E Gabrieli,et al.  Control over brain activation and pain learned by using real-time functional MRI. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[32]  Gary H Glover,et al.  Modulation of subgenual anterior cingulate cortex activity with real‐time neurofeedback , 2011, Human brain mapping.

[33]  Masataka Watanabe Reward expectancy in primate prefrental neurons , 1996, Nature.

[34]  K. Brady,et al.  Sustained reduction of nicotine craving with real-time neurofeedback: exploring the role of severity of dependence. , 2013, Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco.

[35]  Abraham Z. Snyder,et al.  A default mode of brain function: A brief history of an evolving idea , 2007, NeuroImage.

[36]  R W Cox,et al.  Real‐Time Functional Magnetic Resonance Imaging , 1995, Magnetic resonance in medicine.

[37]  Perruchoud Loïse,et al.  Anterior Cingulate Cortex , 2020, Definitions.

[38]  G L Shulman,et al.  INAUGURAL ARTICLE by a Recently Elected Academy Member:A default mode of brain function , 2001 .

[39]  Bettina Sorger,et al.  Real-Time Self-Regulation of Emotion Networks in Patients with Depression , 2012, PloS one.

[40]  Niels Birbaumer,et al.  Real-Time fMRI , 2012, The Neuroscientist : a review journal bringing neurobiology, neurology and psychiatry.

[41]  Mariela Rance,et al.  Real time fMRI feedback of the anterior cingulate and posterior insular cortex in the processing of pain , 2014, Human brain mapping.

[42]  Mark W. Woolrich,et al.  Advances in functional and structural MR image analysis and implementation as FSL , 2004, NeuroImage.

[43]  J. Hollerman,et al.  Influence of reward expectation on behavior-related neuronal activity in primate striatum. , 1998, Journal of neurophysiology.

[44]  Mark Hallett,et al.  Self-modulation of primary motor cortex activity with motor and motor imagery tasks using real-time fMRI-based neurofeedback , 2012, NeuroImage.

[45]  Kevin A. Johnson,et al.  Volitional reduction of anterior cingulate cortex activity produces decreased cue craving in smoking cessation: a preliminary real‐time fMRI study , 2013, Addiction biology.

[46]  H. Heinze,et al.  The resting brain and our self: Self-relatedness modulates resting state neural activity in cortical midline structures , 2008, Neuroscience.

[47]  C. Summerfield,et al.  An information theoretical approach to prefrontal executive function , 2007, Trends in Cognitive Sciences.

[48]  Kymberly D. Young,et al.  Real-Time fMRI Neurofeedback Training of Amygdala Activity in Patients with Major Depressive Disorder , 2014, PloS one.

[49]  John J. Foxe,et al.  The Anterior Cingulate and Error Avoidance , 2006, The Journal of Neuroscience.

[50]  H. Yin,et al.  The role of the basal ganglia in habit formation , 2006, Nature Reviews Neuroscience.

[51]  A. Craig How do you feel? Interoception: the sense of the physiological condition of the body , 2002, Nature Reviews Neuroscience.

[52]  C. Neuper,et al.  Neural substrates of cognitive control under the belief of getting neurofeedback training , 2013, Front. Hum. Neurosci..

[53]  R. Veit,et al.  Self‐regulation of regional cortical activity using real‐time fMRI: The right inferior frontal gyrus and linguistic processing , 2009, Human brain mapping.

[54]  V. Menon,et al.  Saliency, switching, attention and control: a network model of insula function , 2010, Brain Structure and Function.

[55]  Dimitri Van De Ville,et al.  Dynamic reconfiguration of human brain functional networks through neurofeedback , 2013, NeuroImage.

[56]  Mark Hallett,et al.  Modulation of functionally localized right insular cortex activity using real-time fMRI-based neurofeedback , 2013, Front. Hum. Neurosci..

[57]  Chris McNorgan,et al.  A meta-analytic review of multisensory imagery identifies the neural correlates of modality-specific and modality-general imagery , 2012, Front. Hum. Neurosci..

[58]  Margot J. Taylor,et al.  The centre of the brain: Topographical model of motor, cognitive, affective, and somatosensory functions of the basal ganglia , 2013, Human brain mapping.

[59]  Takeo Watanabe,et al.  Perceptual learning incepted by decoded fMRI neurofeedback without stimulus presentation , 2012 .

[60]  Seung-Schik Yoo,et al.  Functional MRI for neurofeedback: feasibility studyon a hand motor task , 2002, Neuroreport.

[61]  Takashi Hanakawa,et al.  Involvement of insula and cingulate cortices in control and suppression of natural urges. , 2009, Cerebral cortex.

[62]  T. Robbins,et al.  Inhibition and the right inferior frontal cortex: one decade on , 2014, Trends in Cognitive Sciences.

[63]  Rafael Malach,et al.  Differential Magnetic Resonance Neurofeedback Modulations across Extrinsic (Visual) and Intrinsic (Default-Mode) Nodes of the Human Cortex , 2015, The Journal of Neuroscience.

[64]  Nick Medford,et al.  Self-regulation of the anterior insula: Reinforcement learning using real-time fMRI neurofeedback , 2014, NeuroImage.

[65]  Michael Erb,et al.  Physiological self-regulation of regional brain activity using real-time functional magnetic resonance imaging (fMRI): methodology and exemplary data , 2003, NeuroImage.

[66]  E. Miller,et al.  An integrative theory of prefrontal cortex function. , 2001, Annual review of neuroscience.

[67]  Y. Yen,et al.  Deactivation of Sensory-Specific Cortex by Cross-Modal Stimuli , 2002, Journal of Cognitive Neuroscience.

[68]  Erich Seifritz,et al.  Real-time Neurofeedback Using Functional MRI Could Improve Down-Regulation of Amygdala Activity During Emotional Stimulation: A Proof-of-Concept Study , 2013, Brain Topography.

[69]  J. Brewer,et al.  Annals of the New York Academy of Sciences the Posterior Cingulate Cortex as a Plausible Mechanistic Target of Meditation: Findings from Neuroimaging , 2022 .

[70]  Roger Gassert,et al.  Improvement in precision grip force control with self-modulation of primary motor cortex during motor imagery , 2015, Front. Behav. Neurosci..

[71]  M. Hallett,et al.  Functional properties of brain areas associated with motor execution and imagery. , 2003, Journal of neurophysiology.

[72]  Stéphane Lehéricy,et al.  Normal functional imaging of the basal ganglia. , 2002, Epileptic disorders : international epilepsy journal with videotape.

[73]  Mark W. Woolrich,et al.  Multilevel linear modelling for FMRI group analysis using Bayesian inference , 2004, NeuroImage.

[74]  Frank Schneider,et al.  Real-time fMRI of temporolimbic regions detects amygdala activation during single-trial self-induced sadness , 2003, NeuroImage.

[75]  Hubert D. Zimmer,et al.  Visual and spatial working memory: From boxes to networks , 2008, Neuroscience & Biobehavioral Reviews.

[76]  N. Farb,et al.  Attending to the present: mindfulness meditation reveals distinct neural modes of self-reference. , 2007, Social cognitive and affective neuroscience.

[77]  Tilo Kircher,et al.  Acquired self‐control of insula cortex modulates emotion recognition and brain network connectivity in schizophrenia , 2013, Human brain mapping.

[78]  B. Balleine,et al.  Human and Rodent Homologies in Action Control: Corticostriatal Determinants of Goal-Directed and Habitual Action , 2010, Neuropsychopharmacology.

[79]  Sven Haller,et al.  Comparison of anterior cingulate vs. insular cortex as targets for real-time fMRI regulation during pain stimulation , 2014, Front. Behav. Neurosci..

[80]  A. Wagner,et al.  Annals of the New York Academy of Sciences Cognitive Control and Right Ventrolateral Prefrontal Cortex: Reflexive Reorienting, Motor Inhibition, and Action Updating , 2022 .

[81]  Yiyuan Tang,et al.  The anterior cingulate gyrus and the mechanism of self-regulation , 2007, Cognitive, affective & behavioral neuroscience.