Neurofeedback Research Overview (V2)

Overview of Neurofeedback Research
This document contains summaries of the current research related to EEG neurofeedback as
applied in seven major areas of brain health: attention-deficit hyperactivity disorder (ADHD),
addictive disorders, anxiety, cognitive decline, depression, peak performance, and
post-traumatic stress disorder (PTSD). This is followed by lists of academic references for
studies reporting on neurofeedback research in a wide range of brain health applications, as
well as references on conceptual and methodological considerations, and a list of references
that include guidelines for clinicians and researchers. Each reference list is subdivided into
studies, case reports, and reviews.
Research Summaries
Attention-Deficit Hyperactivity Disorder (ADHD)
ADHD is the most well-studied condition in neurofeedback research. Based on
meta-analyses and large multicenter randomized controlled trials (RCTs), two frequency
neurofeedback protocols researched for more than 40 years have been shown efficacious and
specific for ADHD: theta-beta ratio (TBR) and sensorimotor rhythm (SMR) (AAPB Guidelines; La
Vaque et al., 2002). Frequency neurofeedback for ADHD received a grade 1 (‘‘best support’’)
rating from the American Academy of Pediatrics in 2013.
TBR aims to decrease theta (4–7 Hz) and/or increase beta (12–21 Hz) power in central
and frontal locations to reduce the high theta-beta ratios, high theta power, and/or low beta
power characteristic of children and adults with ADHD. Recent RCTs suggest that 30–40
sessions of TBR neurofeedback were as effective as methylphenidate in ameliorating inattentive
and hyperactivity symptoms and were even associated with superior post-treatment academic
performance (Duric et al., 2012; Meisel et al., 2013). SMR over the sensorimotor strip
(predominantly right-central) is based on the functional association of the sensorimotor rhythm
with behavioral inhibition in ADHD. In seminal studies (Lubar & Shouse, 1976; Shouse & Lubar,
1979), it was demonstrated that the beneficial hyperactivity-reducing effects of combined
SMR/theta training were maintained even after psychostimulants were withdrawn in hyperactive
children. Studies suggest that TBR and SMR reduce inattentive and hyperactive/impulsive
symptoms to a similar extent and after a comparable number of training sessions.
A series of meta-analyses have shown that the standard TBR and SMR protocols
improve ADHD symptoms, especially inattention (Arns et al., 2009; Micolaud-Franchi et al.,
2014; Bussalb et al., 2019; Riesco-Matías et al., 2019). Efficacy is clear for parentally-rated
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symptoms and less certain for teacher-rated symptoms (Micolaud-Franchi et al., 2014; Cortese
et al., 2016; Razoki, 2018; Bussalb et al. 2019). However, parent ratings are associated with
candidate gene pathways (Bralten et al., 2013), and teachers may be less sensitive to change
(Cortese et al., 2016; Bussalb et al., 2019). Using objective cognitive outcomes, a recent
meta-analysis found neurofeedback to be more efficacious than cognitive training in
ameliorating symptoms of inhibition (Lambez et al., 2020). Critically, a meta-analysis focusing
on long-term maintenance found that after an average 6 months from completion of
neurofeedback, the beneficial effects of neurofeedback were superior to semi-active control
groups and methylphenidate (Van Doren et al., 2019). These findings demonstrate that whereas
medication efficacy diminishes over time, neurofeedback efficacy increases. The best evidence
for efficacy comes from double-blind placebo-controlled RCTs, though it is challenging to devise
a placebo condition that properly controls for psychosocial factors like perceptibility and
motivation (Gaume et al., 2016). One of the largest and most comprehensive such trials is
currently being carried out (International Collaborative ADHD Neurofeedback; ICAN; Arnold et
al., 2013; 2018; 2019), with conclusive results anticipated soon.
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Addictive Disorders
EEG neurofeedback has been applied to addictive disorders for over 30 years,
demonstrating promising results in well-controlled intervention studies, good adherence,
reduced addiction severity, and psychosocial benefits even in patients with severe substance
abuse. Consequently, EEG neurofeedback has been classified as “probably efficacious” as an
adjunctive treatment for substance abuse (AAPB Guidelines; La Vaque et al., 2002; Sokhadze
et al., 2008).
Known as the Peniston protocol (or alpha-theta training), the classical neurofeedback
protocol for addictive disorders was originally applied in the treatment of alcoholism (Peniston &
Kulkosky, 1989; Peniston & Kulkosky, 1990). The Peniston protocol assesses EEG activity in an
eyes-closed resting condition while clients aim to increase parietal alpha (8-12 Hz) and theta
(4-7 Hz) associated with a relaxed state, reducing EEG hyperarousal and augmenting coping
skills (Gruzelier, 2009). Due to commonalities between substance use and ADHD, the Peniston
protocol was later supplemented with initial sessions that aim to enhance central sensorimotor
rhythm (SMR; 12-15 Hz) as is done for ADHD. Called the Scott-Kaiser modification, this
composite protocol has been efficacious in individuals with polydrug abuse and high levels of
impulsivity (Scott et al., 1998; Scott et al., 2005); other ADHD-based protocols (e.g., enhance
SMR, inhibit theta and high-beta; Fielenbach et al., 2019) have also been applied. Given
variation in type, duration, and severity of substance use, a neurofeedback protocol
personalized for the observed brain activity has been advocated (Sokhadze et al., 2008).
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A recent review (Schmidt et al., 2017) identified 7 EEG neurofeedback clinical
intervention trials in substance use since 2010, including 4 randomized controlled trials (RCTs).
Disorders included misuse of: opiates (2 studies; Dehghani-Arani et al., 2010; Dehghani-Arani
et al., 2013), stimulants like cocaine and methamphetamine (3 studies; Hashemian et al., 2015;
Horrell et al., 2010; Rostami & Dehghani-Arani, 2015), alcohol (1 study; Lackner et al., 2015),
and mixed substance and polydrugs (1 study; Keith et al., 2015). Sample sizes ranged from
10-100, and the number of neurofeedback sessions varied from 10-30. Neurofeedback
protocols were mainly the Peniston protocol (some with adjustments; see also Dalkner et al.,
2017) and Scott-Kaiser modification. In all studies, neurofeedback supplemented other
interventions (e.g., pharmacotherapy, psychosocial like cognitive behavioral therapy [CBT]).
Except for the alcohol dependence study, all studies reported positive addiction-related
outcomes, especially reductions of addiction severity and craving. There were also global
psychological and health improvements in most studies. Two studies reported objective
measures, showing substance use abstinence in a urine test (Horrell et al., 2010) and improved
scores on neuropsychological tests of attention and impulsivity (Keith et al., 2015). Changes in
baseline alpha and theta activity were found in alcohol dependence, as well as changes in the
overall EEG, SMR and (reduced) gamma in opiate dependence. The one sham-controlled study
revealed superiority of alpha-theta neurofeedback in clients with methamphetamine misuse
compared with sham (Hashemian, 2015). Critically, one study showed the superiority of
neurofeedback to psychotherapy, with equivalent efficacy for clinician- and computer-guided
neurofeedback (Keith et al., 2015). In sum, recent studies show promising short-term effects of
EEG neurofeedback in reducing craving and modifying dysfunctional brain activity. Additional
RCTs are needed that aim to control for nonspecific effects by comparison with other
psychophysiological treatments (e.g., electrodermal/HRV biofeedback); RCTs with long-term
follow-up are needed to evaluate the occurrence of relapse.
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Anxiety
Alpha-theta (alpha, theta, alpha-theta enhancement) neurofeedback training, which
reduces arousal, has been applied to reduce anxiety (as well as addiction) and create a
generally relaxed state of well-being (Moore, 2000; Gruzelier, 2009). EEG neurofeedback offers
an attractive option, as medication is only mildly more effective than placebo in treating anxiety
disorders. Training is typically administered with eyes closed while listening to auditory feedback
for a total of 7-12 hours of training.
As applied to generalized anxiety disorder (GAD), 9 of 10 neurofeedback studies
reviewed by Moore (2000) and Hammond (2005a,b) produced positive changes in clinical
outcome, with evidence for an anxiety reduction that endures even after 18 months (Watson et
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al., 1978). Indeed, for anxiety disorders, neurofeedback qualifies for the evidence-based
designation of an efficacious treatment (Hammond, 2005a,b), with GAD and phobic anxiety
disorder (as well as PTSD, summarized separately), demonstrating effects beyond placebo and
meeting criteria for “probably efficacious” on the basis of American Psychological Association
Clinical Psychology Division (Chambless & Hollon, 1998) and biofeedback specialty criteria (La
Vaque et al., 2002). A recent systematic review of biofeedback in anxiety disorders (Tolin et al.,
2020) reported a large advantage for EEG neurofeedback over wait list control groups, with
higher quality studies showing superior effects; there was no clear benefit relative to active
control groups, though few such studies were available to be included.
In a GAD study of high-talent musicians performing under stressful conditions, only
musicians who received alpha-theta (enhancement) training yielded enhanced musical
performance under stress (Egner & Gruzelier, 2003). In one RCT of test anxiety, neurofeedback
participants generated 33% more alpha and showed a significant reduction in anxiety; by
comparison, untreated participants and those receiving relaxation training experienced no
significant symptom reduction (Garrett & Silver, 1976). A recent study in adolescents with
self-reported attention and anxiety (e.g., thoughts of worry) symptoms found enhanced alpha
and sensorimotor rhythm (SMR) along with improved symptoms (by visual analogue scales)
after neurofeedback training of alpha, theta, and SMR twice a week for five weeks (Tsatali et al.,
2019).
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Cognitive Decline
Neurofeedback has been applied to improve cognitive function in a variety of conditions,
most prominently attention-deficit hyperactivity disorder (ADHD), associated with impaired
attention and executive function (see separate research summary). There is now an emerging
body of research on neurofeedback for improving cognitive function in such conditions as stroke
(Kober et al., 2015; 2017) and multiple sclerosis (Kober et al., 2019; Keune et al., 2019), with a
particular focus on Alzheimer’s disease (AD), the most common form of dementia, as well as
mild cognitive impairment (MCI), a pre-dementia condition (Petersen et al., 2004; Albert et al.,
2011), in the hopes of delaying the insidious cognitive decline and dementia onset.
Memory impairment is the hallmark of early AD and its precursor amnestic MCI (aMCI);
other cognitive domains may also be impaired. In the EEG, MCI and AD are generally
characterized by an increase in slow frequencies (delta: 2-4 Hz; theta: 4-8 Hz) and a decrease
in faster frequencies (alpha: 8-12 Hz; beta: 13-20 Hz) (Vigil & Tataryn, 2017). These EEG
features have been linked to poor cognitive performance (Klimesch, 1999), atrophy of thalamus,
hippocampus and basal ganglia (Moretti et al., 2012; Wolf et al., 2004), and the formation of
amyloid-beta plaques (Sharma & Nadkarni, 2020). Notably, a smaller change in alpha between
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eyes-open and eyes-closed states has been tied to psychomotor and cognitive slowing, as well
as memory impairment in MCI (Van der Hiele et al., 2007) and AD (Pritchard et al., 1991).
Neurofeedback protocols in healthy and mildly impaired older adults have mainly targeted
enhancing alpha, inhibiting theta, or increasing the alpha-theta ratio at posterior sites (e.g.,
Chapin & Russel-Chapin, 2014). Some have used attention training to enhance sensorimotor
rhythm (SMR; low beta) (SMR) or reduce theta-beta ratio (TBR) at central sites (Jiang et al.,
2017; Jang et al., 2019), given that enhancing attention improves encoding, maintenance and
retrieval of items held in working memory.
Several recent studies have reported better memory performance in MCI following
neurofeedback. Lavy and colleagues (2019) found improved verbal memory after ten 30-minute
sessions in which MCI participants enhanced individual central-parietal upper-alpha;
improvement was maintained at 30-day follow-up. Jirayucharoensak and colleagues (2019)
used alpha- and beta-enhancement neurofeedback (twenty 30-minute sessions) as an add-on
to usual care in healthy or aMCI women and found improved rapid visual processing and spatial
working memory. A small MCI study that enhanced beta over dorsolateral prefrontal cortex
found improved memory, cognitive flexibility, complex attention, reaction time, and executive
function (Jang et al., 2019). In AD, studies using individualized neurofeedback protocols have
reported improved cognitive screener performance (Surmeli et al., 2016) and memory/executive
function as compared with wait list control (Berman & Frederick, 2009).
To summarize, initial evidence suggests that EEG neurofeedback is a promising
methodology for timely, effective intervention for cognitive decline. Large-scale controlled trials
with follow-up are needed to identify/validate the optimal protocols to delay MCI onset and
conversion to dementia, as well as elucidate the relationship between neurofeedback and
particular cognitive functions.
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Depression
Neurofeedback for depression is based on well-established EEG research indicating that
the left frontal area is more associated with positive affect, while the right frontal area is more
involved with negative emotion (see, e.g., Davidson, Philos. Trans. R. Soc. Lond. B, 2004). A
biologic predisposition for depression exists when there is an asymmetry in brain wave activity,
such that there is excessive left frontal alpha (8-12 Hz) reflecting less activation and failure to
suppress the subcortical structures that mediate depression (Walker et al., 2007). Indeed
research has shown that when the left frontal region is “stuck” in an alpha idling rhythm, there is
both reduced positive affect and more withdrawal behavior. Conversely, when there is increased
left frontal beta (15-18 Hz), there is more activation and a greater sense of wellbeing.
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One neurofeedback protocol for modifying this suboptimal brain state involves modifying
the left-right alpha balance at electrodes F3 and F4 (with a Cz reference). Research supports
the efficacy of this ALAY (“alpha asymmetry”) protocol (Choi et al., 2011; Peeters et al., 2014),
including evidence indicating changes in the asymmetry and depressive symptoms endure 1
and 5 years after the end of treatment (Baehr et al., 2001). In a recent study, major depressive
disorder (MDD) most participants who received 1-hour/week ALAY intervention for 6 weeks
regulated their asymmetry and showed improvement in depressive symptoms, though 43%
were non-responders (Wang et al., 2016). Notably, although pharmacologic intervention yields
remission of depression, it does not affect the frontal alpha asymmetry, suggesting that
individuals who receive such intervention continue to have this biomarker for future depression.
Another neurofeedback protocol directly targets reducing left frontal alpha rather than
modifying the left-right alpha balance (Walker et al., 2007). This protocol involves enhancing
left-frontal beta (typically 15-18 Hz) and inhibiting left-frontal theta or alpha to yield greater
activation, which, in turn, generally triggers improved mood. Studies have shown that enhancing
beta and inhibiting theta or alpha at C3 reduced depressive symptoms in most patients (Walker
et al., 2007). In a recent controlled trial, Liu (2017) applied an enhance beta/inhibit alpha
protocol at F3 in 32 college students with MDD. In addition to regulating brainwaves, the
neurofeedback intervention was protective, significantly reducing recurrence and intensity of
depressive symptoms for 3 weeks post-intervention; in contrast, depressive symptoms
increased in active control participants.
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Peak Performance
EEG neurofeedback for ‘peak’ or ‘optimal’ performance focuses on facilitating brain
performance in healthy individuals to achieve maximal brain functioning. Specifically, peak
performance protocols aim to control level of arousal, attention and motivation, optimizing level
of autonomic control and ability to shift states. A concrete goal of peak performance training is
the completion of a specific function or task with fewer errors and greater efficiency, resulting in
a more positive outcome (Vernon, 2005). Twenty-three controlled studies have reported
neurofeedback learning indices along with beneficial outcomes, including gains in: sustained
attention, orienting and executive attention, the P300b event-related potential, memory, spatial
rotation, reaction time, complex psychomotor skills, implicit procedural memory, recognition
memory, perceptual binding, intelligence, mood and well-being (Gruzelier et al., 2014). Gains
have been achieved by a variety of neurofeedback protocols, including: sensorimotor rhythm
(SMR), beta and gamma, theta, and alpha power. Indeed peak performance surpasses other
neurofeedback domains in that the majority of studies demonstrate evidence of learning.
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Neurofeedback may optimize cognitive processing and learning by modifying white
matter pathways and gray matter volume resulting in faster conduction velocity in neural
networks. With regard to alpha power training, it has been suggested that engaging in a
well-practiced task is associated with elevated alpha power, reflecting decreased cortical
information processing and a more automatic stage of skill acquisition (Mirifar et al., 2017). In
one study, increased SMR power improved accuracy and speed of surgery skills (Ros et al.,
2009). In another study, inhibition of theta power reduced radar detection errors (Beatty et al.,
1974). Egner and Gruzelier (2004) reported faster reaction time in an attention task following an
inhibit theta/enhance mid-beta protocol, and memory improvement has been reported following
upper-alpha training (Escolano et al., 2011; Zoefel et al., 2011). A recent review found that 12 of
14 full studies reported positive effects in athletes, with 7 of 10 showing positive effects on
performance, 3 of 6 studies reporting improved affective outcomes, and 3 of 3 reporting better
cognitive outcomes (Mirifar et al., 2017). Though the evidence is overwhelmingly encouraging,
sample sizes are small, and little is known about how methodological characteristics (e.g.,
number of training sessions, particular neurofeedback protocol) impact outcomes (Vernon et al.,
2009; Mirifar et al., 2017). Thus larger, controlled studies are needed to address these issues
and provide a clear understanding of the specific effects of neurofeedback on peak
performance.
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Post-Traumatic Stress Disorder (PTSD)
Evidence-based practice guidelines for PTSD recommend trauma-focused cognitive
behavioral therapy (CBT) and eye movement desensitization and reprocessing (EMDR) as
effective treatment modalities. However, the dropout rate for these therapies is high (Bisson et
al., 2013; National Institute of Clinical Excellence (NICE), 2005). Pharmacological treatment
(e.g., selective serotonin reuptake inhibitors; SSRIs) may also be effective, but the evidence is
weaker. Further, treatment with pharmacological and psychotherapy-based therapies may last
several years and are ineffectual for ~40% of patients (Bradley et al., 2005; NICE, 2005; Stein et
al., 2006).
EEG neurofeedback is a non-pharmacologic alternative that meets “probably efficacious”
criteria for PTSD (Hammond, 2005a,b; Reiter et al., 2016) on the basis of American
Psychological Association Clinical Psychology Division (Chambless & Hollon, 1998) and
biofeedback specialty criteria (La Vaque et al., 2002). A recent systematic review and
meta-analysis pooled data across four randomized controlled trials (RCTs) in PTSD (n=123)
and revealed a very large effect size (standard mean difference of -2.30; 95% CI: -4.37 to -0.24)
for improvement in PTSD symptoms that exceeded effect sizes for internet-based cognitive
therapy and meditation-related exercises (Steingrimsson et al., 2020). The studies consistently
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favored neurofeedback in terms of symptom severity and number of patients achieving
remission. Specifically, PTSD symptoms were reduced by 34-66% in the neurofeedback group,
but ranged from a reduction of 15% to an increase of 13% in the control groups (3 passive, 1
active). The one study with follow-up (van der Kolk et al., 2016) reported 46% symptom
reduction posttreatment and 51% symptom reduction at 1-month follow-up (compared with
reductions of 13% posttreatment and 14% at 1-month follow-up in controls). At 1-month
follow-up, 58% (11/19) of neurofeedback patients achieved remission as compared with 11%
(2/19) of controls. In one study (Noohi et al., 2017), neurofeedback significantly improved
performance on cognitive tests of executive function. In another (Peniston & Kulkosky, 1991), all
neurofeedback patients (14/14) reduced psychotropic medication use as compared with one
patient (1/13) in the control group.
Though the extant evidence is encouraging (see also reviews by Reiter et al. 2016;
Panisch & Hai, 2018), additional controlled studies are desirable for greater confidence and
clarity regarding the efficacy of neurofeedback in PTSD. Indeed small, heterogeneous samples
and different study designs preclude specific recommendations for the optimal neurofeedback
protocol. Enhance alpha/inhibit theta protocols are often used for PTSD (e.g., Pensiston &
Kulkosky, 1991; Noohi et al., 2017), but there is considerable variation in the frequency bands
trained (e.g., Pop-Jordanova & Zorcec, 2004 used SMR enhancement), session duration (e.g.,
Kluetsch et al., 2013: single session; Peniston & Kulkosky, 1991: 30 sessions), inter-session
interval and duration of treatment. Also, only one RCT included an active control group (van der
Kolk et al., 2016; standard treatment), and no studies have incorporated a sham control.
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Academic Reference Lists
Attention-Deficit Hyperactivity Disorder (ADHD) 11
STUDIES 11
CASE REPORTS 19
REVIEWS 19
Addictive Disorders 25
STUDIES 25
CASE REPORTS 27
REVIEWS 27
Anxiety 28
STUDIES 28
CASE REPORTS 31
REVIEWS 31
Autism Spectrum Disorders (ASD) 33
STUDIES 33
CASE REPORTS 34
REVIEWS 34
Chronic Fatigue Syndrome and Fibromyalgia 35
STUDIES 35
CASE REPORTS 35
REVIEWS 35
Cognitive Decline 36
STUDIES 36
CASE REPORTS 38
REVIEWS 39
Depression 39
STUDIES 39
CASE REPORTS 40
REVIEWS 41
Eating Disorders 41
STUDIES 41
REVIEWS 42
Epilepsy 43
STUDIES 43
CASE REPORTS 44
REVIEWS 45
Learning & Developmental Disabilities 46
STUDIES 46
CASE REPORTS 47
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REVIEWS 48
Medical Conditions 48
STUDIES 48
CASE REPORTS 50
REVIEWS 50
Obsessive Compulsive Disorder 51
STUDIES 51
REVIEWS 51
Pain and Headache 52
STUDIES 52
CASE REPORTS 53
REVIEWS 53
Peak Performance 53
STUDIES 53
CASE REPORTS 55
REVIEWS 55
Post Traumatic Stress Disorder (PTSD) 56
STUDIES 56
CASE REPORTS 58
REVIEWS 58
Schizophrenia 59
STUDIES 59
CASE REPORTS 60
REVIEWS 60
Sleep 60
STUDIES 60
CASE REPORTS 61
REVIEWS 61
Traumatic Brain Injury (TBI), Stroke, Coma, & Cerebral Palsy 62
STUDIES 62
CASE REPORTS 64
REVIEWS 65
Conceptual/Theoretical 67
STUDIES 67
REVIEWS 68
Methodology & Mechanisms 71
STUDIES 71
REVIEWS 74
Guidelines for Research & Clinical Practice 77
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Attention-Deficit Hyperactivity Disorder (ADHD)
STUDIES
Arnold, L. E., DeBeus, R., Kerson, C., Monastra, V. J., Rice, R. R., Barterian, J. A., and Pan, X.
(2019). One-year follow-up of double-blind RCT of neurofeedback for ADHD. Journal of
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Arnold, L. E., Kerson, C., Monastra, V., Pan, J., Kraemer, H., Rice, R., Barterian, J. A.,
Schrader, C., and Rhodes, R. (2018). Outcomes of double-blind RCT of neurofeedback
for ADHD. Journal of the American Academy of Child & Adolescent Psychiatry 57, S283.
doi:10.1016/j.jaac.2018.07.666.
Arnold, L. E., Lofthouse, N., Hersch, S., Pan, X., Hurt, E., Bates, B., Kassouf, K., Moone, S.,
and Grantier, C. (2013). EEG neurofeedback for ADHD: Double-blind sham-controlled
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Arns, M., Feddema, I., and Kenemans, J. L. (2014). Differential effects of theta/beta and SMR
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Arns, M., Kleinnijenhuis, M., Fallahpour, K., and Breteler, R. (2008). Golf performance
enhancement and real-life neurofeedback training using personalized event-locked EEG
profiles. J. Neurother. 11, 11–18. doi:10.1080/10874200802149656.
Bhayee, S., Tomaszewski, P., Lee, D. H., Moffat, G., Pino, L., Moreno, S., and Farb, N. A. S.
(2016). Attentional and affective consequences of technology supported mindfulness
training: A randomised, active control, efficacy trial. BMC Psychol. 4, 60.
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Bink, M., Bongers, I. L., Popma, A., Janssen, T. W. P., & van Nieuwenhuizen, C. (2016). 1-year
follow-up of neurofeedback treatment in adolescents with attention-deficit hyperactivity
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Bink, M., van Nieuwenhuizen, C., Popma, A., Bongers, I. L., & van Boxtel, G. J. M. (2015).
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trial. European Child & Adolescent Psychiatry, 24(9), 1035–1048.
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Bioulac, S., Purper-Ouakil, D., Ros, T., Blasco-Fontecilla, H., Prats, M., Mayaud, L., and
Brandeis, D. (2019). Personalized at-home neurofeedback compared with long-acting
methylphenidate in an European non-inferiority randomized trial in children with ADHD.
BMC Psychiatry 19, 237. doi:10.1186/s12888-019-2218-0.
Bluschke, A., Friedrich, J., Schreiter, M. L., Roessner, V., and Beste, C. (2018). A comparative
study on the neurophysiological mechanisms underlying effects of methylphenidate and
neurofeedback on inhibitory control in attention deficit hyperactivity disorder.
Neuroimage Clin. 20, 1191–1203. doi:10.1016/j.nicl.2018.10.027.
Boyd, W. D., and Campbell, S. E. (1998). EEG biofeedback in the schools: The use of EEG
biofeedback to treat ADHD in a school setting. J. Neurother. 2, 65–71.
doi:10.1300/J184v02n04_05.
Boynton, T. (2001). Applied research using alpha/theta training for enhancing creativity and
well-being. J. Neurother. 5, 5–18. doi:10.1300/J184v05n01_02.
Breteler, R., Pesch, W., Nadorp, M., Best, N., and Tomasoa, X. (2012). Neurofeedback in
residential children and adolescents with mild mental retardation and ADHD behavior. J.
Neurother. 16, 172–182. doi:10.1080/10874208.2012.705742.
Carmody, D. P., Radvanski, D. C., Wadhwani, S., Sabo, M. J., and Vergara, L. (2000). EEG
biofeedback training and attention-deficit/hyperactivity disorder in an elementary school
setting. J. Neurother. 4, 5–27. doi:10.1300/J184v04n03_02.
Cho, B.-H., Kim, S., Shin, D. I., Lee, J. H., Lee, S. M., Kim, I. Y., and Kim, S. I. (2004).
Neurofeedback training with virtual reality for inattention and impulsiveness.
Cyberpsychol. Behav. 7, 519–526. doi:10.1089/cpb.2004.7.519.
Cueli, M., Rodríguez, C., Cabaleiro, P., García, T., and González-Castro, P. (2019). Differential
efficacy of neurofeedback in children with ADHD presentations. J. Clin. Med. 8, 204.
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Deiber, M.-P., Hasler, R., Colin, J., Dayer, A., Aubry, J.-M., Baggio, S., Perroud, N., and Ros, T.
(2019). Linking alpha oscillations, attention and inhibitory control in adult ADHD with
EEG neurofeedback. Neuroimage Clin. 25, 102145. doi:10.1016/j.nicl.2019.102145.
Dobrakowski, P., and Łebecka, G. (2020). Individualized neurofeedback training may help
achieve long-term improvement of working memory in children with ADHD. Clin. EEG
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Dupuy, F. E., Clarke, A. R., and Barry, R. J. (2013). EEG activity in females with
attention-deficit/hyperactivity disorder. J. Neurother. 17, 49–67.
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Duric, N. S., Assmus, J., Gundersen, D., Duric Golos, A., and Elgen, I. B. (2017). Multimodal
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Duric, N. S., Assmus, J., Gundersen, D., and Elgen, I. B. (2012). Neurofeedback for the
treatment of children and adolescents with ADHD: A randomized and controlled clinical
trial using parental reports. BMC Psychiatry 12, 107. doi:10.1186/1471-244X-12-107.
Egner, T., and Gruzelier, J. H. (2003). Ecological validity of neurofeedback: Modulation of slow
wave EEG enhances musical performance. Neuroreport 14, 1221–1224.
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Egner, T., and Gruzelier, J. H. (2004). EEG Biofeedback of low beta band components:
Frequency-specific effects on variables of attention and event-related brain potentials.
Clin. Neurophysiol. 115, 131–139. doi:10.1016/S1388-2457(03)00353-5.
Egner, T., and Gruzelier, J. H. (2001). Learned self-regulation of EEG frequency components
affects attention and event-related brain potentials in humans. Neuroreport 12,
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Stankus, T. (2008). Can the brain be trained? Comparing the literature on the use of EEG
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24

Addictive Disorders
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drug-related cues in cocaine addiction. J. Neurother. 14, 195–216.
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29

children: A randomized controlled trial. Comput. Human Behav. 63, 321–333.
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CASE REPORTS
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Rozelle, G. R., and Budzynski, T. H. (1995). Neurotherapy for stroke rehabilitation: A single
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31

Autism Spectrum Disorders (ASD)
STUDIES
Coben, R., and Padolsky, I. (2007). Assessment-guided neurofeedback for autistic spectrum
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Drysdale, M. T. B., Martinez, Y. J., and Thompson, L. (2012). The effects of humorous literature
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Chronic Fatigue Syndrome and Fibromyalgia
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34

Cognitive Decline
Note: These references include studies relevant to individuals identified as having cognitive
decline or studies in healthy adults with direct implications for adults with cognitive decline.
For studies relevant to enhancing cognitive function in healthy individuals, see the separate
Peak Performance bibliography.
STUDIES
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Neurofeedback training with a motor imagery-based BCI: Neurocognitive improvements
35

and EEG changes in the elderly. Med. Biol. Eng. Comput. 54, 1655–1666.
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Obsessive Compulsive Disorder
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Diaz Hernandez, L., Rieger, K., and Koenig, T. (2018). Low motivational incongruence predicts
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REVIEWS
Alkoby, O., Abu-Rmileh, A., Shriki, O., and Todder, D. (2018). Can we predict who will respond
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Batail, J. M., Bioulac, S., Cabestaing, F., Daudet, C., Drapier, D., Fouillen, M., Fovet, T.,
Hakoun, A., Jardri, R., Jeunet, C., et al. (2019). EEG neurofeedback research: A fertile
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Guidelines for Research & Clinical Practice
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78

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