ReviewEEG-neurofeedback for optimising performance. I: A review of cognitive and affective outcome in healthy participants
Introduction
Since the 1960s (Kamiya, 1968, Kamiya, 1969) the ability has been demonstrated for learned control of brain electrical activity through instantaneous feedback in the form of spectral power, event-related potentials or slow cortical potentials, putatively through operant conditioning or volitional control. This has now been extended to fMRI (e.g., Yoo et al., 2004, Weiskopf et al., 2004, deCharms, 2008, Rota et al., 2009, Hamilton et al., 2010, Zotev et al., 2011, Berman et al., 2012, Ruiz et al., 2013), transcranial doppler sonography (Duschek et al., 2011) and near infrared spectrometry (NIRS; Mihara et al., 2012, Kober et al., 2013). However, in contrast to autonomic and somatic peripheral biofeedback which became an established domain of Health Psychology (Feuerstein et al., 1988, Brannon and Feist, 2009), EEG-biofeedback was sidelined by science in the 1980s largely due to flawed studies and clinical overstatement, combined with the equivocal outcome of theoretically simplistic applications of alpha training for relaxation, when at the time psychophysiological understanding of alpha was at an early stage and was under the sway of unitary arousal models (Lindsley, 1952, Duffy, 1957). From the 1980s university research on EEG-biofeedback, later branded neurofeedback, was confined to a few centres, notably under the direction of Sterman (e.g., Sterman and Friar, 1972, Sterman et al., 1970, Sterman et al., 1974, Sterman, 1996, Sterman, 2000) and Lubar (e.g., Lubar and Shouse, 1976, Lubar and Lubar, 1984, Lubar et al., 1995a, Lubar et al., 1995b) in the USA and Birbaumer in Germany (Elbert et al., 1984, Rockstroh, 1989). Meanwhile a largely dedicated practitioner following arose outside of universities, especially in North America, encouraged by instrumentation companies. While helping keep the field alive and inventing diverse treatment protocols, this following mostly proceeded without scientific validation, sometimes accompanied by pseudo theorising and advertising speak.
Over the last decade or so university research, largely in Europe, has revisited neurofeedback, a revival of interest which the Society of Applied Neuroscience (SAN) has encouraged, and, as this review shows scientific evaluation and an evidence-base for applications is growing exponentially. This has come at a time when enhancing potential by ‘brain training’ is fashionable in contemporary culture (Owen et al., 2010, Rabipour and Raz, 2012), making the cause of scientific validation ever more essential and urgent, for aside from false promises, premature popularisation has led science to discard a field more than once.
While ‘neurofeedback’ has now been applied to a range of brain imaging modalities, here the focus will be on the accumulating evidence of validation particularly this millennium in favour of neurofeedback applications with the EEG in healthy participants, commonly called the ‘optimal’ or ‘peak performance’ field. Validation has taken the form of controlled studies showing differential group outcomes advantaging a neurofeedback protocol, and more importantly has included correlation between the feedback learning and the outcome allowing the mediation of neurofeedback learning to be inferred. The review will be initially structured around neurofeedback protocols in conjunction with psychological processes, followed by applications in sport and with the elderly. A companion review, Part II, will cover applications in the performing arts and creativity (Gruzelier, 2013a) while Part III will be devoted to methodological and theoretical issues in order to help advance this re-emergent field (Gruzelier, in preparation). The review will not concern clinical applications which have been the main concern of the field to date. To give some examples there are reviews on Attention Deficit Hyperactivity Disorder (ADHD; Arns et al., 2009, Lofthouse et al., 2012), epilepsy (Tan et al., 2009), autism spectrum disorder (Coben et al., 2010); controlled studies on addiction (Scott et al., 2005), tinnitus (Hartmann et al., 2013) and insomnia (Cortoos et al., 2010); case studies on stroke (Bearden et al., 2003), anxiety and depression (Hammond, 2005) and cognitive disorganisation with anhedonia in conjunction with drug misuse (Unterrainer et al., 2013). Similarly there are reviews on the burgeoning approach branded Brain Computer Interface (BCI), one typically focussing on the neuro-rehabilitation of patients with tetraplegia from brain or spinal cord injuries enabling patients through EEG feedback to communicate and/or physically interact with their environment, and up until now largely consisting of engineering innovations and a small clinical evidence base (Birbaumer et al., 2008, Mak and Wolpaw, 2009, Silvoni et al., 2011).
As will be seen a diversity of neurofeedback training protocols has been applied for optimising performance. The most popular one has involved training-up the amplitude of the Sensory Motor Rhythm (SMR) 12–15 Hz band while inhibiting outer-lying bands in the EEG spectrum. This had followed evidence that within the 12–15 Hz frequency range recordings from sensory-motor and pre-motor cortices showed a distinctive oscillation which was maximal during periods of quiet wakefulness, with reduced muscle tone, and was absent during goal directed activity and desynchronising with motor intention (Sterman and Wyrwicka, 1967, Wyrwicka and Sterman, 1968, Sterman and Friar, 1972, Sterman et al., 1974). Notably application of the SMR neurofeedback protocol has reduced motor seizure rates in epileptic patients while normalising their sleep patterns and EEG (Sterman, 2000, Sterman and Friar, 1972, Sterman et al., 1970, Sterman et al., 1974). By extrapolating to ADHD the potential of reducing the excitability of the sensorimotor system with concomitant suppression of theta, and following SMR training with training up adjacent low beta activity (16–22 Hz; beta1) an index of EEG desynchronisation, improvements in attention and hyperactivity were first demonstrated in case studies and early controlled trials (e.g., Lubar and Shouse, 1976, Lubar et al., 1995a, Rossiter and LaVaque, 1995, Linden et al., 1996) and now have a substantive evidence base (Monastra et al., 2005, Arns et al., 2009, Lofthouse et al., 2012).
Another pioneering protocol involved raising the theta-alpha ratio with auditory feedback and eyes closed, termed alpha/theta (A/T) training. Following on from the earliest attempts to up-train alpha for relaxation and reduce anxiety (Budzynski and Stoyva, 1972, Hardt and Kamiya, 1978), the focus on theta first grew out of diverse cultural evidence that the deeply relaxing, hypnogic reverie or twilight theta state was conducive to creative insights (see Gruzelier, 2009). From clinical studies the goal evolved of elevating theta over alpha to achieve crossover. Early on this had demonstrable benefits for addiction and PTSD which included enhanced well-being when introduced as a central part of a therapeutic package (e.g., Peniston and Kulkosky, 1989, Peniston and Kulkosky, 1991, Saxby and Peniston, 1995).
Subsequently the SMR and A/T protocols have been contrasted for their optimal performance effects in healthy participants, while new neurofeedback protocols have been developed from contemporary neuroscience including training upper-alpha, peak alpha frequency, gamma, and various theta protocols, the subject of this review. Historically self-regulation of slow cortical potentials (SCPs) had received extensive validation (Elbert et al., 1984, Rockstroh, 1989), but has not attracted interest in the optimal performance field despite promise in trials with ADHD where it has been compared favourably with EEG-spectrum training (Gevensleben et al., 2009).
In what must be a necessarily concise selection of study features to be considered the following issues have been documented.
What evidence is there that feedback learning occurred? Have learning indices been reported or is learning inferred from demonstration that a group receiving neurofeedback out-performed a comparison group? What would evidence of learning consist of: learning curves within sessions, across sessions, the correlation of learning indices with outcome assessments? If the most basic theoretical premise about neurofeedback holds, namely that the brain's rhythms are changed by training, is learning reflected in subsequent training sessions including baselines?
There are issues of specificity. (i) Is there band specificity or independence such that only the trained bands are influenced or is there leakage or even reciprocity within the EEG spectrum? (ii) Is there specificity and independence regarding cognitive/affective outcome such that performance enhancement is specific to some processes leaving other processes unchanged? (iii) Is there topographical specificity such that the EEG outcome is specific to the training site, or is it distributed locally beyond the training site, or is it only distal from the training site?
Are there sufficient sessions to give learning a chance given that a learning process is being built? Can learning even be obtained from one-session and if so what is the validation? What is the interval between sessions given there are considerations for learning of spaced versus distributed practice. Are some people unable to learn to self-regulate their brain rhythms – sometimes termed non-responders? The outsider may be surprised at how few subjects are typically included in most intervention studies. Consider though that with say fourteen subject sessions to include a ten session course of training plus two pre and post-training outcome assessments, then for a study involving three groups of ten this would add up to 420 experimenter sessions to acquire data, and not allowing for dropout replacements which are inevitable when enterprising, mostly student subjects are required to fit fourteen sessions into their busy lives; let alone the logistics of engaging as trainees professionals such as eye surgeons (Ros et al., 2009).
All these issues will be reconsidered in detail in Part III focussing on methodology and theory (Gruzelier, in preparation). In Part I the over-riding objective will be to weigh up the now rapidly accumulating evidence base in the search of validation of neurofeedback, a concern of the author's from an early review (Gruzelier et al., 2006). As will be seen the majority of studies report evidence of neurofeedback learning and in this respect the optimal performance field is far ahead of other neurofeedback domains in reporting evidence of learning.
Section snippets
Sustained attention, selective attention and memory: SMR and beta1 training
SMR and beta1 neurofeedback protocols widely used with ADHD were found to have a positive impact on the sustained attention of healthy subjects in two studies (Egner and Gruzelier, 2001, Egner and Gruzelier, 2004a) which were an adjunct to music performance enhancement (Egner and Gruzelier, 2003; see for review Gruzelier, 2012, Gruzelier, 2013a). In the first music study as a secondary aim SMR (12–15 Hz, C4) and beta1 (15–18 Hz, C3) protocols with theta (4–7 Hz) and high beta (22–30 Hz; beta2)
Alpha/theta training
In establishing what was the first evidence of operant control over the theta/alpha ratio with eyes closed, Egner et al. (2002) had shown in healthy subjects that when comparing a contingent with a non-contingent control A/T protocol, both protocols led to identical ratings on Activation Deactivation self-report scales (Thayer, 1967), whereas only contingent training produced an increase in the theta/alpha ratio. One implication from this was that there was likely to be more to the reported
Sporting skills
Applications of neurofeedback to improve sporting performance and to compare elite with novice performance are at an early stage but will be apposite (Thompson et al., 2008). Little progress has been made since the pioneering studies of Landers et al. (1991) who reported that the feedback of an EEG analysis of slow potentials improved performance in pre-elite archers. They followed evidence that in sportsmen prior to the execution of a skill there was a unilateral slowing of left temporal
Validation
Having reviewed the efficacy of EEG-neurofeedback for optimising function in healthy individuals, before concluding Part I there are two sources of evidence in support of validation to be summarised. The first is where a neurofeedback experimental group is characterised by a uniquely successful cognitive and/or affective outcome when compared with a comparison group and/or a control group; should in the absence of a control group two neurofeedback protocols show the same benefits these are not
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