Real-time fMRI and its application to neurofeedback

Real-time fMRI (rtfMRI) allows immediate access to experimental results by analyzing data as fast as they are acquired. It was devised soon after the inception of fMRI and has undergone a rapid development since then. The availability of results during the ongoing experiment facilitates a variety of applications such as quality assurance or fast functional localization. RtfMRI can also be used as a brain-computer interface (BCI) with high spatial resolution and whole-brain coverage, overcoming limitations of EEG based BCIs. This review will focus on the application of rtfMRI BCIs to neurofeedback, i.e., the online feedback of the blood oxygen level dependent (BOLD) response. I will motivate its development and place its beginnings into the contemporary scientific context by providing an account of our early work at the University of Tübingen, followed by a review of the accomplishments and the current state of rtfMRI neurofeedback. RtfMRI neurofeedback has been used to train self-regulation of the local BOLD response in various different brain areas and to study consequential behavioral effects. Behavioral effects such as modulation of pain, reaction time, linguistic or emotional processing have been shown in healthy and/or patient populations. RtfMRI neurofeedback presents a new paradigm for studying the relation between brain behavior and physiology, because the latter can be regarded as the independent variable (unlike in conventional neuroimaging studies where behavior is the independent variable). The initial results in patient populations improving pain, tinnitus, depression or modulating perception in schizophrenia are encouraging and merit further controlled clinical studies.

[1]  Rainer Goebel,et al.  Real-time independent component analysis of fMRI time-series , 2003, NeuroImage.

[2]  R. DeCharms,et al.  Reading and controlling human brain activation using real-time functional magnetic resonance imaging , 2007, Trends in Cognitive Sciences.

[3]  J. Rieger,et al.  Predicting Decisions in Human Social Interactions Using Real-Time fMRI and Pattern Classification , 2011, PloS one.

[4]  N Birbaumer,et al.  Stability of cortical self‐regulation in epilepsy patients , 1997, Neuroreport.

[5]  Thomas Eickermann,et al.  A new approach to measure single‐event related brain activity using real‐time fMRI: Feasibility of sensory, motor, and higher cognitive tasks , 2001, Human brain mapping.

[6]  Rainer Goebel,et al.  Cortex-based real-time fMRI , 2001, NeuroImage.

[7]  N. Logothetis,et al.  Neurophysiological investigation of the basis of the fMRI signal , 2001, Nature.

[8]  Oliver Speck,et al.  The impact of physiological noise correction on fMRI at 7 T , 2011, NeuroImage.

[9]  J. Bernarding,et al.  A new concept of a unified parameter management, experiment control, and data analysis in fMRI: Application to real-time fMRI at 3T and 7T , 2008, Journal of Neuroscience Methods.

[10]  M. Boly,et al.  Willful modulation of brain activity in disorders of consciousness. , 2010, The New England journal of medicine.

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

[12]  Wolfgang Linden,et al.  The Efficacy of Behavioral Treatments for Hypertension , 2006, Applied psychophysiology and biofeedback.

[13]  Klaus Mathiak,et al.  Social reinforcement can regulate localized brain activity , 2010, European Archives of Psychiatry and Clinical Neuroscience.

[14]  S Thesen,et al.  Prospective acquisition correction for head motion with image‐based tracking for real‐time fMRI , 2000, Magnetic resonance in medicine.

[15]  S. S. Steiner,et al.  Biofeedback efficacy studies , 1981, Biofeedback and self-regulation.

[16]  Cuntai Guan,et al.  Temporal classification of multichannel near-infrared spectroscopy signals of motor imagery for developing a brain–computer interface , 2007, NeuroImage.

[17]  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.

[18]  G. Rees,et al.  Neuroimaging: Decoding mental states from brain activity in humans , 2006, Nature Reviews Neuroscience.

[19]  T. Egner,et al.  Ecological validity of neurofeedback: modulation of slow wave EEG enhances musical performance , 2003, Neuroreport.

[20]  R W Cox,et al.  Real‐time 3D image registration for functional MRI , 1999, Magnetic resonance in medicine.

[21]  T J Grabowski,et al.  Real‐time multiple linear regression for fMRI supported by time‐aware acquisition and processing , 2001, Magnetic resonance in medicine.

[22]  Michael Erb,et al.  Brain areas activated in fMRI during self-regulation of slow cortical potentials (SCPs) , 2003, Experimental Brain Research.

[23]  M S Cohen,et al.  Real-time functional magnetic resonance imaging. , 2001, Methods.

[24]  Ravi S. Menon,et al.  Dissociating pain from its anticipation in the human brain. , 1999, Science.

[25]  Niels Birbaumer,et al.  Real-time support vector classification and feedback of multiple emotional brain states , 2011, NeuroImage.

[26]  G.E. Moore,et al.  Cramming More Components Onto Integrated Circuits , 1998, Proceedings of the IEEE.

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

[28]  Byoung-Kyong Min,et al.  Neuroimaging-based approaches in the brain-computer interface. , 2010, Trends in biotechnology.

[29]  E. Fetz Operant Conditioning of Cortical Unit Activity , 1969, Science.

[30]  H. Flor,et al.  A spelling device for the paralysed , 1999, Nature.

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

[32]  S. Posse,et al.  Enhancement of BOLD‐contrast sensitivity by single‐shot multi‐echo functional MR imaging , 1999, Magnetic resonance in medicine.

[33]  Daniel Gembris,et al.  Functional Magnetic Resonance Imaging in Real-Time (FIRE) , 2000 .

[34]  Tirin Moore,et al.  Selective Attention from Voluntary Control of Neurons in Prefrontal Cortex , 2011, Science.

[35]  Hesamoddin Jahanian,et al.  Real‐time functional MRI using pseudo‐continuous arterial spin labeling , 2011, Magnetic resonance in medicine.

[36]  R. Christopher,et al.  Applications of real-time fMRI , 2008 .

[37]  Michael Erb,et al.  Deactivation of Brain Areas During Self-Regulation of Slow Cortical Potentials in Seizure Patients , 2006, Applied psychophysiology and biofeedback.

[38]  R. DeCharms,et al.  Quantification of Adverse Events Associated with Functional MRI Scanning and with Real-Time fMRI-Based Training , 2012, International Journal of Behavioral Medicine.

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

[40]  Bettina Sorger,et al.  Another kind of 'BOLD Response': answering multiple-choice questions via online decoded single-trial brain signals. , 2009, Progress in brain research.

[41]  Mukesh Dhamala,et al.  Hyperscanning : Simultaneous fMRI during Linked Social Interactions , 2001 .

[42]  Matthew H. Davis,et al.  Detecting awareness in the vegetative state. , 2006, Science.

[43]  Geraint Rees,et al.  Manipulating visual perception with real-time fMRI-based neurofeedback training , 2010 .

[44]  T. Mulholland,et al.  Feedback delay and amplitude threshold and control of the occipital EEG , 1979, Biofeedback and self-regulation.

[45]  Bettina Sorger,et al.  Real-time fMRI-based brain-computer interfacing for neurofeedback therapy and compensation of lost motor functions , 2010 .

[46]  Charles R. G. Guttmann,et al.  Multiresolution Data Acquisition and Detection in Functional MRI , 2001, NeuroImage.

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

[48]  Stephen LaConte,et al.  Decoding fMRI brain states in real-time , 2011, NeuroImage.

[49]  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.

[50]  R. Veit,et al.  Self-regulation of local brain activity using real-time functional magnetic resonance imaging (fMRI) , 2004, Journal of Physiology-Paris.

[51]  Rainer Goebel,et al.  Neurofeedback: A promising tool for the self-regulation of emotion networks , 2010, NeuroImage.

[52]  J Hennig,et al.  Functional Imaging by I0‐ and T2* ‐parameter mapping using multi‐image EPI , 1998, Magnetic resonance in medicine.

[53]  Wolfgang Grodd,et al.  Principles of a brain-computer interface (BCI) based on real-time functional magnetic resonance imaging (fMRI) , 2004, IEEE Transactions on Biomedical Engineering.

[54]  J. O'Doherty,et al.  Direct Instrumental Conditioning of Neural Activity Using Functional Magnetic Resonance Imaging-Derived Reward Feedback , 2007, The Journal of Neuroscience.

[55]  R. Deichmann,et al.  Real-time functional magnetic resonance imaging: methods and applications. , 2007, Magnetic resonance imaging.

[56]  Clement Hamani,et al.  Clinical StudyDeep Brain Stimulation for Treatment-Resistant Depression , 2005 .

[57]  F. Jolesz,et al.  Brain–machine interface via real-time fMRI: Preliminary study on thought-controlled robotic arm , 2009, Neuroscience Letters.

[58]  van Pim Dijk,et al.  Neural activity underlying tinnitus generation: Results from PET and fMRI , 2009, Hearing Research.

[59]  Gary H. Glover,et al.  Learned regulation of spatially localized brain activation using real-time fMRI , 2004, NeuroImage.

[60]  K Mathiak,et al.  Evaluation of motion and realignment for functional magnetic resonance imaging in real time , 2001, Magnetic resonance in medicine.

[61]  A. Lozano,et al.  Deep Brain Stimulation for Treatment-Resistant Depression , 2005, Neuron.

[62]  S S Fox,et al.  Operant Controlled Neural Event: Formal and Systematic Approach to Electrical Coding of Behavior in Brain , 1968, Science.

[63]  S Posse,et al.  Functional magnetic resonance imaging in real time (FIRE): Sliding‐window correlation analysis and reference‐vector optimization , 2000, Magnetic resonance in medicine.

[64]  Epifanio Bagarinao,et al.  Estimation of general linear model coefficients for real-time application , 2003, NeuroImage.

[65]  Jakob Heinzle,et al.  Flow of affective information between communicating brains , 2011, NeuroImage.

[66]  Xiaoping P. Hu,et al.  Real‐time fMRI using brain‐state classification , 2007, Human brain mapping.

[67]  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.

[68]  Nikolaus Weiskopf,et al.  Neuronal mechanisms underlying control of a brain–computer interface , 2005, The European journal of neuroscience.

[69]  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.

[70]  D. H. Mellor,et al.  Real time , 1981 .

[71]  M. Raichle,et al.  Subgenual prefrontal cortex abnormalities in mood disorders , 1997, Nature.

[72]  N Birbaumer,et al.  Biofeedback-produced hemispheric asymmetry of slow cortical potentials and its behavioural effects. , 1990, International journal of psychophysiology : official journal of the International Organization of Psychophysiology.

[73]  Richard M. Leahy,et al.  Electromagnetic brain mapping , 2001, IEEE Signal Process. Mag..

[74]  Jong-Hwan Lee,et al.  Functional magnetic resonance imaging-mediated learning of increased activity in auditory areas , 2007, Neuroreport.

[75]  Nikolaus Weiskopf,et al.  An EEG-driven brain-computer interface combined with functional magnetic resonance imaging (fMRI) , 2004, IEEE Transactions on Biomedical Engineering.

[76]  Satrajit S. Ghosh,et al.  Computing moment-to-moment BOLD activation for real-time neurofeedback , 2010, NeuroImage.

[77]  Xiaochu Zhang,et al.  Single subject task‐related BOLD signal artifact in a real‐time fMRI feedback paradigm , 2011, Human brain mapping.

[78]  Niels Birbaumer,et al.  Detection of Cerebral Reorganization Induced by Real-Time fMRI Feedback Training of Insula Activation , 2011, Neurorehabilitation and neural repair.

[79]  E. Fetz Volitional control of neural activity: implications for brain–computer interfaces , 2007, The Journal of physiology.

[80]  Niels Birbaumer,et al.  Reorganization of functional and effective connectivity during real-time fMRI-BCI modulation of prosody processing , 2011, Brain and Language.

[81]  Rainer Goebel,et al.  Information-based functional brain mapping. , 2006, Proceedings of the National Academy of Sciences of the United States of America.

[82]  Irene Liu,et al.  Improved modulation of rostrolateral prefrontal cortex using real-time fMRI training and meta-cognitive awareness , 2011, NeuroImage.

[83]  Thilo Hinterberger,et al.  [Neurofeedback for children with ADHD: a comparison of SCP- and theta/beta-protocols]. , 2006, Praxis der Kinderpsychologie und Kinderpsychiatrie.

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

[85]  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.

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

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

[88]  Nikolaus Weiskopf,et al.  Single-shot compensation of image distortions and BOLD contrast optimization using multi-echo EPI for real-time fMRI , 2005, NeuroImage.

[89]  Niels Birbaumer,et al.  Acquired Control of Ventral Premotor Cortex Activity by Feedback Training , 2012, Neurorehabilitation and neural repair.

[90]  H. Flor,et al.  A multimodal brain-based feedback and communication system , 2004, Experimental Brain Research.

[91]  Douglas C. Noll,et al.  Online Analysis of Functional MRI Datasets on Parallel Platforms , 1997, The Journal of Supercomputing.

[92]  Todd W. Thompson,et al.  When the brain is prepared to learn: Enhancing human learning using real-time fMRI , 2011, NeuroImage.

[93]  James T. Voyvodic,et al.  Real-Time fMRI Paradigm Control, Physiology, and Behavior Combined with Near Real-Time Statistical Analysis , 1999, NeuroImage.

[94]  J P Hatch,et al.  Controlled group designs in biofeedback research: Ask, “what does the control group control for?” , 1982, Biofeedback and self-regulation.

[95]  Soo-Young Lee,et al.  Brain–computer interface using fMRI: spatial navigation by thoughts , 2004, Neuroreport.

[96]  Oliver Speck,et al.  Magnetic resonance imaging of freely moving objects: prospective real-time motion correction using an external optical motion tracking system , 2006, NeuroImage.

[97]  Klaus Mathiak,et al.  Signal quality and Bayesian signal processing in neurofeedback based on real-time fMRI , 2012, NeuroImage.

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

[99]  U. Strehl,et al.  Modification of Slow Cortical Potentials in Patients with Refractory Epilepsy: A Controlled Outcome Study , 2001, Epilepsia.

[100]  Karl J. Friston,et al.  Human Brain Function , 1997 .