ReviewClinical efficacy and potential mechanisms of neurofeedback
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.
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2021, Computers in Human Behavior ReportsCitation 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 ControlCitation 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].