Review
Clinical efficacy and potential mechanisms of neurofeedback

https://doi.org/10.1016/j.paid.2012.11.037Get rights and content

Abstract

Although many psychological disorders have significant basis in neurobiological dysfunction, most treatment approaches either neglect biological aspects of the problem, or approach dysfunction through pharmacological treatment alone, which may expose individuals to negative side effects. In recent decades, neurofeedback has been promoted as an alternative approach to treating neurobiological dysfunction. Neurofeedback helps individuals gain control over subtle brain activity fluctuations through real-time rewards for pre-established target brainwave frequencies at specific cortical locations. This paper reviews the effectiveness of neurofeedback in a range of conditions, including ADHD, autism spectrum disorders, substance use, PTSD, and learning difficulties. Neurofeedback has emerged as superior or equivalent to either alternative or no treatment in many of the examined studies, suggesting it produces some effects worthy of further examination. In light of its potential to address neurobiological dysfunction directly, future research is suggested in order to refine protocols, as well as to establish effectiveness and efficacy. Potential mechanisms of neurofeedback are discussed, including global connectivity, neuroplasticity, and reinforcement of the default mode network, central executive network, and salience network.

Highlights

Neurofeedback is an alternative treatment to psychotherapy or psychopharmacology. ► This paper reviews rigorously designed RCT studies of different conditions. ► Potential mechanisms are global connectivity, plasticity and core network involvement. ► Future directions to investigate effectiveness, efficacy and mechanism are proposed.

Introduction

Clinicians and researchers have long searched for ways to influence minds toward optimal functioning. However, many methods for influencing brain activity, such as surgery, psychopharmacology or electroconvulsive therapy, are invasive or produce profound side effects. Talk therapy is often effective, but some conditions require an integrated biological and cognitive approach. Neurofeedback is an alternative approach that aims to help individuals alter brain activation without introducing electrical or magnetic activity, or pharmacological compounds into the brain, hence preventing the brain from becoming dependent on outside influences for better functioning. However, while this approach may be conceptually appealing, there have been few rigorous studies to establish its efficacy and effectiveness. This review summarizes different neurofeedback protocols and details efficacy findings in a wide range of conditions. Potential mechanisms of change and directions for future research and clinical practice are also discussed.

Biofeedback allows individuals to gain control over their physiology by providing real-time reflection of biological activity. Biofeedback has been demonstrated as an effective treatment for conditions such as hypertension, incontinence, headaches, and others (see Association for Applied Psychophysiology, 2008 for an extensive review). Neurofeedback involves measures of brain activity, such as Electroencephalography (EEG) or real time functional magnetic resonance imaging (RTfMRI). Less expensive, safer, and simpler to administer, EEG neurofeedback has been studied more extensively than RTfMRI and is the focus of this review.

EEG measures scalp wave frequencies classified as delta (1–4 Hz), theta (4–8 Hz), alpha (8–12 Hz), beta (13–30 Hz), gamma (30–100+ Hz,) and 12–15 Hz representing sensorimotor rhythm (SMR). These protocols utilize the International 10–20 System of placement (Jasper, 1958). Below, different neurofeedback protocols are summarized:

Beta waves represent alertness and active concentration (Haenschel, Baldeweg, Croft, Whittington, & Gruzelier, 2000), while SMR is associated with semantic processing and sustained attention (Egner & Gruzelier, 2001). SMR neurofeedback training appears to strengthen thalamic inhibitory function (Sterman, 1996), and has been applied to learning disabilities or attention deficit and hyperactivity disorder (ADHD), as well as to seizure disorders. Some protocols that aim to increase attention combine upregulation of Beta/SMR with downregulation of theta, which is referred to as theta/beta.

These frequencies are targeted for upregulation in disorders of hyperarousal such as posttraumatic stress disorder (PTSD). Beyond therapeutic benefits, alpha/theta training may enhance creativity. High-level musicians and dancers trained with this protocol performed better under stressful conditions (Egner and Gruzelier, 2003, Raymond et al., 2005).

SCPs are short (hundreds of milliseconds), event-related brain responses. Positive SCPs represent behavioral inhibition for the purpose of attention (Birbaumer, Elbert, Canavan, & Rockstroh, 1990). The contingent negative variation (CNV) represents event anticipation, and is inhibited in some attention disorders (Banaschewski & Brandeis, 2007). Upregulating CNV was found to improve attention (Gevensleben et al., 2009a, Gevensleben et al., 2009b).

Relatively higher right over left prefrontal activity relates to internalizing (depressive, anxious) symptoms (Davidson, 1998). Alpha Asymmetry protocol, or ALAY, aims to reduce left alpha activity (with alpha activity representing neural hypoactivity) and increase right frontal alpha activity, in aim of reducing susceptibility toward negative emotions (Baehr, Rosenfeld, & Baehr, 1997).

Quantitative EEG (qEEG) is a whole-brain mapping approach. Some qEEG approaches attempt to bring individuals closer to a healthy qEEG norm (Thornton, 2000). Other approaches use qEEG to identify hypoactive or hyperactive target regions for training (Logemann, Lansbergen, Van Os, Böcker, & Kenemans, 2010).

A newer approach, infralow frequency neurofeedback targets frequencies as low as 0.01 Hz (Legarda, McMahon, & Othmer, 2011). Few studies have been published using this technique, though some evidence suggests it is a future direction for PTSD or other disorders (Legarda et al., 2011, Othmer et al., 2011).

fMRI measures blood flow through blood-oxygen level dependence signal (Ogawa, Lee, Kay, & Tank, 1990). fMRI shows better spatial resolution than EEG, but transformations required for signal processing mean that feedback is currently provided at a 3–5 s delay (deCharms et al., 2005). This approach is developing and has been applied to conditions such as pain and tinnitus.

Below, findings from a broad range of neurofeedback studies are summarized and future directions for research are discussed. To investigate this literature, a systematic search was undertaken using the PubMed/Medline (http://www.ncbi.nlm.nih.gov/sites/entrez) and PsycInfo (http://www.apa.org/pubs/databases/psycinfo/index.aspx) databases. The following search terms were used: “neurofeedback” or “EEG biofeedback;” “controlled,” “control group,” “RCT” or “randomized.” Articles were restricted to those written in English and using human subjects. References of selected articles were also examined. Articles were discarded for small groups or unclear methods. Publications between 1st of January 1960 and 31st of July 2012 were examined.

Table 1 summarizes RCT study findings, organized by target condition. The table provides effect sizes (ES) when available or calculable. If several measures were reported, ES were averaged. ES reported in the paper or in correspondence with authors are bolded and specified as between or within group. Calculated ES were done so using the program dstat (Johnson, 1989), using within group results from reported χ2 values, within-group pre-post F-test values, or pre-post means and pooled standard deviations. Starred values indicate significant interactions, i.e. findings that neurofeedback produced superior effects to control conditions using analysis of variance. When available, follow-up ES are reported.

Most studies excluded participants who were comorbid for any other condition or who exhibited organic brain disorders. This review focuses on studies that use rigorous methodology, with randomized clinical trials (RCT) design. Table 1 includes sample description, ES and design characteristics for these studies.

Section snippets

ADHD

At least seven RCT studies exist for ADHD neurofeedback, several with follow-up articles. The first found a significant average increase of 9.3 IQ points (Cohen’s d = 0.76) in a theta/beta experimental group, as well as significant reductions in inattentive behavior (d = 0.69; Table 1: Linden, Habib, & Radojevic, 1996). Theta/beta or SMR training was replicated in several additional RCTs (Table 1: Lévesque et al., 2006, Steiner et al., 2012). Like theta/beta, SCP training was also found to produce

Summary

At least 22 well-controlled neurofeedback studies have been published, with several additional pilot or older studies providing further directions for future research. Figure 1 summarizes ES findings from this review when available.

“Neurofeedback” refers to a broad category of therapies, and different target frequencies have been found to produce different outcomes. For example, SMR training enhanced healthy participants’ attention and reduced CPT errors, while beta training reduced reaction

Field limitations and future directions

Several limitations arise in reviewing this literature. First, relatively few neurofeedback studies are well-designed, controlled studies, and those that exist are rarely manualized. Because the framework of Chambless et al. (1998) requires manualized protocols and comparisons to established treatments, neurofeedback is only eligible as efficacious and specific for ADHD treatment with theta/beta or SCP. In addition, publication bias means published data is skewed toward the significant and

Potential neurofeedback mechanisms

Another current limitation of the neurofeedback literature is the lack of research and consensus as to underlying mechanism. Below is a summary of different theories about mechanism of neurofeedback, as well as concrete suggestions for studies that may help elucidate their validity.

Conclusions

Neurofeedback alters brain activity intrinsically, without introducing new elements such as electrical activity, magnetic activity, or pharmacological agents, into the brain. It has been found to produce symptom relief and changes in brain activity that endure over time in at least some psychological disorders. The theoretical appeal of neurofeedback over other therapeutic methods is its intrinsic nature, wherein the brain is taught to produce more adaptive activation rather than to depend on

Acknowledgments

I would like to thank Dr. Siegfrid Othmer, and Susan and Kurt Othmer of EEG Info, Dr. Paul Kulkosky, and Dr. Anna Benson of the Naval Hospital at Camp Pendleton for guidance and personal communication.

References (113)

  • M.E.J. Kouijzer et al.

    Long-term effects of neurofeedback treatment in autism

    Research in Autism Spectrum Disorders

    (2009)
  • M.E.J. Kouijzer et al.

    Neurofeedback improves executive functioning in children with autism spectrum disorders

    Research in Autism Spectrum Disorders

    (2009)
  • M.E.J. Kouijzer et al.

    Neurofeedback treatment in autism. Preliminary findings in behavioral, cognitive, and neuropsychological functioning

    Research in Autism Spectrum Disorders

    (2010)
  • J. Lévesque et al.

    Effect of neurofeedback training on the neural substrates of selective attention in children with attention-deficit/hyperactivity disorder: A functional magnetic resonance imaging study

    Neuroscience Letters

    (2006)
  • H.N. Logemann et al.

    The effectiveness of EEG-feedback on attention, impulsivity and EEG: A sham feedback controlled study

    Neuroscience Letters

    (2010)
  • V. Menon

    Large-scale brain networks and psychopathology: A unifying triple network model

    Trends in Cognitive Neuroscience

    (2011)
  • Y. Nir et al.

    Widespread functional connectivity and fMRI fluctuations in human visual cortex in the absence of visual stimulation

    Neuroimage

    (2006)
  • J.A. Pineda et al.

    Positive behavioral and electrophysiological changes following neurofeedback training in children with autism

    Research in Autism Spectrum Disorders

    (2008)
  • A.M. Speer et al.

    Opposite effects of high and low frequency rTMS on mood in depressed patients: Relationship to baseline cerebral activity on PET

    Journal of Affective Disorders

    (2009)
  • E. Angelakis et al.

    EEG neurofeedback: A brief overview and an example of peak alpha frequency training for cognitive enhancement in the elderly

    Clinical Neuropsychology

    (2007)
  • L.E. Arnold et al.

    EEG neurofeedback for ADHD: Double-blind sham-controlled randomized pilot feasibility trial

    Journal of Attention Disorders (online)

    (2012)
  • Yucha, C., & Montgomery, D. (Eds.). (2008). Evidence based practice in biofeedback and neurofeedback. Association for...
  • E. Baehr et al.

    The clinical use of an alpha asymmetry protocol in the neurofeedback treatment of depression: Two case studies

    Journal of Neurotherapy

    (1997)
  • E. Baehr et al.

    Clinical use of an alpha asymmetry neurofeedback protocol in the treatment of mood disorders: Follow-up study one to five years post therapy

    Journal of Neurotherapy

    (2001)
  • R.A. Baer

    Mindfulness training as a clinical intervention: A conceptual and empirical review

    Clinical Psychology: Science & Practice

    (2003)
  • M.N. Baliki

    Beyond feeling: Chronic pain hurts the brain, disrupting the default-mode network dynamics

    Journal of Neuroscience

    (2008)
  • T. Banaschewski et al.

    Annotation: What electrical brain activity tells us about brain function that other techniques cannot tell us – A child psychiatric perspective

    Journal of Child Psychology and Psychiatry

    (2007)
  • D.S. Bassett et al.

    Small-world brain networks

    Neuroscientist

    (2006)
  • J. Becerra et al.

    Follow-up study of learning-disabled children treated with neurofeedback or placebo

    Clinical EEG Neuroscience

    (2006)
  • J. Becerra et al.

    Neurofeedback in healthy elderly human subjects with electroencephalographic risk for cognitive disorder

    Journal of Alzheimer’s Disease

    (2012)
  • M.G. Berman

    Neural and behavioral effects of interference resolution in depression and rumination

    Cognitive Affective & Behavioral Neuroscience

    (2011)
  • N. Birbaumer et al.

    Slow potentials of the cerebral cortex and behavior

    Physiological Reviews

    (1990)
  • D.V.M. Bishop

    The children’s communication checklist

    (2003)
  • J.A. Brefczynski-Lewis et al.

    Neural correlates of attention expertise in long-term meditation practitioners

    Proceedings of the National Academy of Sciences

    (2007)
  • M.H. Breteler et al.

    Improvements in spelling after QEEG-based neurofeedback in dyslexia: A randomized controlled treatment study

    Applied Psychophysiology and Biofeedback

    (2010)
  • S.J. Broyd et al.

    Attention-induced deactivations in very low frequency EEG oscillations: Differential localisation according to ADHD symptom status

    PLoS One

    (2011)
  • R.L. Buckner et al.

    The brain’s default network: Anatomy, function, and relevance to disease

    Annals of the New York Academy of Sciences

    (2008)
  • R.L. Buckner et al.

    Molecular, structural, and functional characterization of Alzheimer’s Disease: Evidence for a relationship between default activity, amyloid, and memory

    Journal of Neuroscience

    (2005)
  • Butcher, J. N., Graham, J. R., Ben-Porath, Y. S., Tellegen, A., Dahlstrom, W. G., Kraemmer, B. (2001). MMPI-2 Manual...
  • B.R. Cahn et al.

    Meditation states and traits: EEG, ERP, and neuroimaging studies

    Psychological Bulletin

    (2006)
  • D.S. Cantor et al.

    Computerized EEG analyses of autistic children

    Journal of Autism & Developmental Disorders

    (1986)
  • D.L. Chambless et al.

    Update on empirically validated therapies II

    The Clinical Psychologist

    (1998)
  • D. Chan et al.

    Effects of level of meditation experience on attention focus: Is the efficiency of executive or orientation networks improved?

    Journal of Alternative and Complementary Medicine

    (2007)
  • B.H. Cho et al.

    Neurofeedback training with virtual reality for inattention and impulsiveness

    Cyberpsychology and Behavior

    (2004)
  • S.W. Choi et al.

    Is alpha wave neurofeedback effective with randomized clinical trials in depression? A pilot study

    Neuropsychobiology

    (2011)
  • L.A. Clark et al.

    Diagnosis and classification of psychopathology: Challenges to the current system and future directions

    Annual Review of Psychology

    (1995)
  • R. Coben et al.

    Assessment-guided neurofeedback for autistic spectrum disorders

    Journal of Neurotherapy

    (2007)
  • A. Cortoos et al.

    An exploratory study on the effects of tele-neurofeedback and tele-biofeedback on objective and subjective sleep in patients with primary insomnia

    Applied Psychophysiology and Biofeedback

    (2010)
  • R.W. Cox et al.

    Real-time functional magnetic resonance imaging

    Magnetic Resonance in Medicine

    (1995)
  • H.D. Critchley

    Neural mechanisms of autonomic, affective, and cognitive integration

    Journal of Computational Neuroscience

    (2005)
  • Cited by (113)

    • Biosensors and Biofeedback in Clinical Psychology

      2022, Comprehensive Clinical Psychology, Second Edition
    • Emotional self-regulation, virtual reality and neurofeedback

      2021, Computers in Human Behavior Reports
      Citation Excerpt :

      The repetition of neurofeedback sessions enables the creation or reinforcement of connections and brain pathways, due to the brain's neuroplasticity. Consequently, these alterations in the brain can lead to positive changes in the individual's behaviour and feelings (Canadian Agency for Drugs, 2014; Niv, 2013; Sitaram et al., 2017; White et al., 2017). Neurofeedback has been used as a complementary and alternative treatment to several mental disorders and has been showing potential for the treatment of anxiety (Gomes et al., 2016; Marzbani et al., 2016; Omejc et al., 2019), revealing improvements in individuals with this pathology (Banerjee & Argaez, 2017; Mennella et al., 2017; Moradi et al., 2011; Simkin et al., 2014).

    • Predicting the success rate of healthy participants in beta neurofeedback: Determining the factors affecting the success rate of individuals

      2021, Biomedical Signal Processing and Control
      Citation Excerpt :

      The person is encouraged with auditory and visual feedback if their brain activities are improved. This encourages the brain to spend more time producing the desired pattern [20–24]. To date, the neurofeedback technique has been successfully used in the treatment and decrease of symptoms of nervous disorders, such as seizures, attention deficit hyperactivity disorder (ADHD), stress, depression, and Alzheimer’s disease [25–37].

    View all citing articles on Scopus
    View full text