Home page
Home | Email me  
Wrap around
Criminal violence
Sales Training

Home > Evidence
EEG Biofeedback for ADHD

Important journal article reviewing the scientific evidence of EEG Biofeedback for ADHD.

Applied Psychophysiology and Biofeedback, Vol. 30, No. 2, June 2005 ( C_ 2005)
DOI: 10.1007/s10484-005-4305-x
Electroencephalographic Biofeedback in the Treatment
of Attention-Deficit/Hyperactivity Disorder

Vincent J. Monastra,1,2,7 Steven Lynn,2 Michael Linden,3 Joel F. Lubar,4
John Gruzelier,5 and Theodore J. LaVaque6

Historically, pharmacological treatments for attention-deficit/hyperactivity disorder
(ADHD) have been considered to be the only type of interventions effective for reducing
the core symptoms of this condition. However, during the past three decades, a series of
case and controlled group studies examining the effects of EEG biofeedback have reported
improved attention and behavioral control, increased cortical activation on quantitative
electroencephalographic examination, and gains on tests of intelligence and academic
achievement in response to this type of treatment. This review paper critically examines the
empirical evidence, applying the efficacy guidelines jointly established by the Association
for Applied Psychophysiology and Biofeedback (AAPB) and the International Society for
Neuronal Regulation (ISNR). On the basis of these scientific principles, EEG biofeedback
was determined to be “probably efficacious” for the treatment of ADHD. Although significant
clinical improvement was reported in approximately 75% of the patients in each of
the published research studies, additional randomized, controlled group studies are needed
in order to provide a better estimate of the percentage of patients with ADHD who will
demonstrate such gains in clinical practice.
KEY WORDS: attention-deficit/hyperactivity disorder; ADHD; EEG biofeedback; neurotherapy; efficacy;
Attention-Deficit/Hyperactivity Disorder is an enduring mental disorder, characterized
by persistent symptoms of inattention alone or in combination with hyperactivity and
impulsivity (American Psychiatric Association, 1994). Prevalence of this disorder in the
United States is reported to be approximately 7% (Gadow & Sprafkin, 1997; Pelham,
1FPI Attention Disorders Clinic, Endicott, New York.
2Binghamton University, Binghamton, New York.
3ADD Treatment Centers, San Juan Capistrano, California.
4University of Tennessee, Memphis, Tennessee.
5Imperial College, London, United Kingdom.
6The Stress Clinic, Green Bay, Wisconsin.
7Address all correspondence to Vincent J. Monastra, PhD, FPI Attention Disorders Clinic, 2102 E. Main St.,
Endicott, New York 13760; e-mail: drmonastra@stny.rr.com.
1090-0586/05/0600-0095/0 C_ 2005 Springer Science+Business Media, Inc.

Gnagy, Greenslade, & Milich, 1992; Wolraich, Hannah, Pinnock, Baumgaertel, & Brown,
1996) with international prevalence rates ranging from 2 to 29% (Barkley, 1998). The
severity of these symptoms is known to significantly impair a person’s ability to function
effectively at home, school, and in the workplace.
Without effective treatment, children and adolescents with ADHD are at greater risk
to develop academic, behavioral, mood, and anxiety disorders (Biederman et al., 1996),
incur accidental injury (Hartsough & Lambert, 1985; Lahey et al., 1998), and struggle with
substance abuse disorders (Claude & Firestone, 1995; Mannuzza et al., 1991). Similarly,
when not systematically treated, adults with a childhood history of ADHD have academic
histories marked by lower average marks, more expulsions, a higher rate of retention in
a grade, and fewer completed grades (Weiss & Hechtman, 1993; Mannuzza et al., 1993,
1998). These patients are more likely to have a higher incidence of substance abuse,
psychiatric disorders, and criminal behavior, and have an employment history of more jobs,
more frequent “layoffs” and an overall job status that was lower than that of peers of similar
intelligence without ADHD (Weiss & Hechtman, 1993; Murphy & Barkley, 1996).
Because of the severity and enduring nature of the functional impairments associated
with ADHD, a substantial amount of scientific effort has been directed at understanding the
causes of ADHD and the identification of effective treatments. Beginning with the early
clinical impressions of Still (1902) and Tredgold (1908), researchers have wondered if
children with problems of behavioral inhibition and lack of sustained attention suffered from
some type of undiagnosed brain disease or injury. Over the past century, the preponderance
of scientific findings now supports the position that ADHD is an inherited disorder, whose
core symptoms are founded in neuroanatomical, neurochemical, and neurophysiological
characteristics that adversely affect neuronal functioning at the cortical level.
During the past decade, numerous scientific studies of twins have revealed a heritability
index of approximately .75 for ADHD (Levy, Hay, McStephen, Wood, & Waldman, 1997;
Silberg et al., 1996; Willcut, Pennington, & DeFries, 2000). Similarly elevated incidence
rates are evident in studies of families including a member with ADHD. In families that
include a child with ADHD, over 30% of the siblings also have ADHD (Biederman et al.,
1992; Biederman, Keenan & Faraone, 1990; Welner, Welner, Stewart, Palkes, & Wish,
1977). In those families that include an adult with ADHD, the likelihood that at least one
child will have this disorder is 57% (Biederman et al., 1995).
Efforts to identify those genes that contributed to these patterns of inheritance have
focused primarily on dopaminergic alleles. This appears to be due to recent advances in
molecular biology, which has revealed that stimulant medications produce their clinical
effects by occupying dopamine reuptake transporters, thereby increasing the availability of
dopamine at the synaptic level (Ding et al., 1997; Volkow et al., 1995). In genetic studies
conducted to date, there is evidence implicating that anomalies of the dopamine receptor-
4 gene (DRD4: Smalley et al., 1998), the dopamine receptoer-2 gene (DRD2; Comings
et al., 1996), and the dopamine reuptake transporter (DAT1) gene (Cook et al., 1995) occur
significantly more frequently in patients with ADHD. The hypothesis derived from these
studies was that such anomalies would limit the number of dopamine receptors and result
in reduction of the size of dopamine-rich brain regions.
Neuroanatomical studies of patients with ADHD supported such a hypothesis by
providing evidence of structural differences between patients with ADHD and healthy age
peers. Because the core symptoms of ADHD are comprised of impaired behavioral control
and lack of sustained attention, neuroimaging studies have focused on those structures
involved in the control of movement (e.g. the basal ganglia and the cerebellum) and
attentional functions (e.g. the anterior cingulate gyrus, the right frontal region, the anterior
and posterior regions of the corpus callosum, and the caudate). As would be anticipated
on the basis of genetic findings, reports of reduced size in each of these regions has been
reported and replicated in the scientific literature (Aylward et al., 1996; Castellanos, 1997;
Castellanos et al., 1994; Giedd et al., 1994; Hynd, Hern, Novey, & Eliopulos, 1993; Hynd,
Semrud-Clikeman, Lorys, & Novey, 1990; Mostofsky, Reiss, Lockhart, & Denckla, 1998;
Semrud-Clikeman, Filipek, Biederman, & Steingard, 1994).
Further indication of the significance of the prefrontal cortex, the basal ganglia circuitry,
and the cerebellum in regulating attention and behavioral control is evident in
the results of studies utilizing single photon emission tomography (SPECT) and positron
emission tomography (PET). Initially, Lou, Henriksen, and Bruhn (1984) reported hypoperfusion
in the prefrontal cortex and basal ganglia during PET examination of patients
with ADHD. Subsequently, Zametkin et al. (1990) and Ernst et al. (1994) reported decreased
glucose metabolism in these regions, indicating cortical underarousal. Researchers
using SPECT imaging (e.g. Kim, Lee, Shin, Cho, & Lee, 2002; Sieg, Gaffney, Preston, &
Hellings, 1995) likewise noted decreased cerebral blood flow in the right lateral prefrontal
cortex, the right middle temporal cortex, and the orbital and cerebellar cortices (bilaterally)
in patients diagnosed with ADHD.
Consistent with the results of neuroimaging studies, neurophysiological researchers
have primarily found evidence of underactivity over frontal and central, midline cortical
regions in approximately 85–90% of patients with ADHD (Chabot, Merkin, Wood,
Davenport, & Serfontein, 1996; Clarke, Barry, McCarthy, & Selikowitz, 2001a; Mann,
Lubar, Zimmerman, Miller, & Nuenchen, 1992; Monastra et al., 1999). The primary electrophysiological
indicators of underactivity that have been identified via quantitative electroencephalographic
(QEEG) analysis of patients with ADHD include: elevated relative
theta power, reduced relative alpha and beta power, and elevated theta/alpha and theta/beta
power ratios, predominately over frontal and central, midline regions.
A secondary pattern of excessive activity or “hyperarousal” over frontal regions has
also been revealed in patients with ADHD (e.g. Chabot & Serfontein, 1996; Clarke, Barry,
McCarthy, & Selikowitz, 2001b). This pattern has been particularly evident in those patients
who have not responded optimally to stimulant medications (Chabot, Orgill, Crawford,
Harris, & Serfontein, 1999). In such patients, QEEG analysis has revealed increased relative
beta power, decreased relative alpha power, and decreased theta/beta power ratios across
all cortical recording sites in comparison to healthy peers.
Additionally, when compared to other patients diagnosed with ADHD, patients with
“hyperaroused” profiles demonstrated greater relative beta activity, decreased relative theta
activity, decreased theta/beta ratios, and decreased relative delta over frontal and central
regions of the cortex. Although it is not clear whether those “ADHD” patients who
demonstrate cortical hyperarousal constitute a different clinical syndrome, EEG biofeedback
protocols have been developed to treat ADHD patients who present with either
hypoarousal or hyperarousal over frontal or central midline regions.
The rationale for EEG biofeedback is derived from substantial neurophysiological
research which clarified the relationship between surface EEG and the underlying thalamocortical
mechanisms that are responsible for its rhythms and frequency modulations. As
reviewed by Sterman (1996), variations in alertness and behavioral control appear directly
related to specific thalamocortical generator mechanisms and that such variations are evident
in distinctive EEG frequency rhythms that emerge over specific topographic regions of
the brain. He hypothesized that neuropathology (such as ADHD) could alter these rhythms
and that EEG feedback training directed at normalizing these rhythms may yield sustaining
clinical benefits. Consistent with this hypothesis, each of the large scale QEEG studies of
patients with ADHD that have been conducted since 1996 (e.g. Chabot et al., 1996; Chabot
& Serfontein, 1996; Clarke et al., 2001a, 2001b; Clarke, Barry, McCarthy, & Selikowitz,
1998; Monastra et al., 1999; Monastra, Lubar, & Linden, 2001) has reported abnormal
QEEG findings in patients with ADHD.
Further impetus for the development of EEG biofeedback for ADHD is derived from
studies demonstrating adverse side effects and insufficient response to existing medical
treatments. Although both stimulant (e.g. methylphenidate, dextroamphetamine and pemoline)
and nonstimulant medications (e.g. atomoxetine and impramine) have been shown
to be efficacious for the treatment of the core symptoms of ADHD in controlled, group
studies, approximately 25% of ADHD patients demonstrate either an adverse response or
no response (Greenhill, Halperin, & Abikoff, 1999; Swanson, McBurnett, Christian, &
Wigel, 1995). In addition, as noted by Pelham and Murphy (1986), only a minority of
ADHD patients show sufficient improvement to be considered within the normal range
following medication treatments and there is great variability in the degree of improvement
noted in those patients who do respond to medication (Pelham & Smith, 2000). Typically
improvements are noted in some functional domains but not in others. As concluded by
Pelham (2002), “other interventions are needed for nonresponders or incomplete responders
to medication” (pp. 12–13).
As previously noted, the vast majority of patients diagnosed with ADHD demonstrate
excessive cortical slowing during QEEG, PET, or SPECT examinations. A smaller
percentage exhibit cortical “hyperarousal.” During the past three decades, specific EEG
biofeedback treatments that target cortical slowing or hyperarousal have been developed
and evaluated in controlled case and group studies. In each of these studies, patients have
participated in training procedures in which they were reinforced (via tone or visual display)
for producing a specific change in cortical activity (e.g. reducing the amplitude of
activity at slower EEG frequencies; increasing activity in faster frequencies). Typically, the
patient had to maintain this desired change for a period of 0.5 s in order to be “rewarded.”
It was hypothesized that if patients could begin to “normalize” the level of activity in
regions responsible for attention and behavioral control, they would begin to demonstrate
developmentally appropriate abilities to attend and maintain behavioral control.
The initial demonstration that biofeedback could yield changes in cortical activity and
that such modifications resulted in observable improvements in behavior/functioning was
provided by Sterman and his colleagues (Sterman, Wywricka, & Roth, 1969; Wywricka &
Sterman, 1968). Much of Sterman’s groundbreaking research examined the electrophysiological
characteristics of behavioral inhibition (Roth, Sterman, & Clemente, 1967; Sterman
& Wywricka, 1967; Wywricka & Sterman, 1968). His methodical examination of EEG
patterns associated with inhibition led to the identification of the “Sensorimotor Rhythm”
(or SMR), which is generated over the Rolandic Cortex. Although initially identified as a
range of activity between 12 and 20 cycles per second, the “peak activity” of the SMR was
noted at 12–14 Hz. Sterman et al. (1969) and Wywricka and Sterman (1968) found that
laboratory animals could be trained to produce this rhythm voluntarily and applied these
findings in the treatment of individuals with a specific type of impaired behavioral control
(epilepsy). As reviewed by Sterman (2000) and Monastra (2003), this application of EEG
biofeedback has been demonstrated to be particularly helpful in the treatment of seizure
disorders in patients who have not responded to pharmacological treatments.
The initial application of SMR training for the treatment of patients with ADHD
was reported by Lubar and Shouse (1976). Their initial demonstration of clinical response
in a hyperactive child stimulated considerable interest in SMR training as a potentially
efficacious treatment for ADHD. Subsequently, in response to scientific understanding of
the role of the frontal lobes in sustained attention, and mounting evidence of excessive
cortical slowing over central, midline and frontal regions in ADHD patients, Lubar and
his colleagues (e.g. Lubar & Lubar, 1984) expanded their EEG biofeedback treatments to
include efforts to increase production of EEG activity in a faster frequency range (“beta”:
16–20 Hz), while suppressing activity at slower speeds (“theta”: 4–8 Hz). These two primary
training approaches (SMR enhancement; theta suppression/beta enhancement) provide the
foundation for each of the protocols that have been examined in the controlled group studies
of EEG biofeedback in the treatment of ADHD conducted to date. Although recent QEEG
findings of a neurophysiological “subtype” of ADHD patients, characterized by excessive
“beta” activity over frontal regions (Chabot & Serfontein, 1996: Clarke et al., 2001a,
2001b), have prompted interest in the development of protocols to suppress excessive beta
appearing frontally, no controlled group studies examining this type of EEG biofeedback
have been reported to date.
At this time, three EEG biofeedback treatment protocols have been primarily examined
in controlled-group studies. Reflecting neuroanatomical findings, these protocols target
cortical regions responsible for attention and behavioral inhibition. A brief description of
each follows:
In this type of EEG biofeedback, patients are encouraged to develop control over
behaviors of hyperactivity and impulsivity by learning to increase their production of the
SMR (12–15 Hz) over one of two sites (C3 or C4), while simultaneously suppressing the
production of theta (4–7 or 4–8 Hz) activity. Typically, recordings are obtained from one
active site, referenced to linked earlobes, with a sampling rate of at least 128 Hz. Auditory
(tones) and visual feedback (counter display; movement of puzzle pieces, graphic designs,
or animated figures) is provided based on patient success in controlling microvolts of theta
or SMR, or the percentage of time that theta is below or SMR is above (SMR) pretreatment
“thresholds.” This type of training was included in the first controlled, group study of EEG
biofeedback for ADHD (Rossiter & LaVaque, 1995).
A secondary type of SMR training has also been examined in a controlled, group study
(Fuchs, Birbaumer, Lutzenberger, Gruzelier, & Kaiser, 2003). In this protocol, patients
with ADHD, Predominately Hyperactive-Impulsive Type are trained to increase SMR (12–
15 Hz) activity, while simultaneously decreasing beta-2 (22–30 Hz) activity. Recordings
are obtained at C4 with linked ear reference. Sampling rate is at least 128 Hz. In Fuchs
et al.’s protocol, patients with a Combined Type of ADHD receive this type of training
during half of each session. During the other half of each session, a theta suppression beta-
1 enhancement protocol (described below) is followed (training site: C3). As with the
“first” SMR protocol, feedback is contingent on patient success in controlling microvolts
of theta, SMR, beta-1 or beta-2.
This protocol has been investigated in three of the five controlled, group studies
published to date (Linden, Habib, & Radojevic, 1996; Monastra, Monastra, & George,
2002; Rossiter & LaVaque, 1995). In this training procedure, patients are encouraged to
increase production of beta-1 activity (16–20 Hz), while suppressing theta activity (4–
8 Hz). Recordings are obtained at Cz with linked ear reference (monopolar); at FCz-PCz
with ear reference, or at Cz-Pz with ear reference. Fuchs et al. (2003) used a variation of
this protocol with patients diagnosed with ADHD, Predominately Inattentive Type, training
theta suppression and beta enhancement at C3. Sampling rate is at least 128 Hz. Feedback
is provided contingent on patient success in controlling microvolts of beta or theta.
A combination of two of these procedures (Protocol 1 and 3) has also been reported in
a controlled, group study (Carmody, Radvanski, Wadhwani, Sabo, & Vergara, 2001). In this
procedure, patients are encouraged to increase production of a restricted range of beta-1
activity (16–18 Hz) while suppressing activity at 2–7 Hz. Recordings are obtained at C3
or Cz with linked ear reference (monopolar). Students who displayed increased aggression
or agitation within the first 13–35 sessions of this type of training were considered to be
“overstimulated.” Such patients were then treated with a SMR training protocol, in which
they were reinforced for increasing activity at 13–15 Hz and suppressing activity at 2–7 Hz.
As noted in reviews by Lubar (2003) and Monastra (2003), there are numerous case
studies demonstrating clinical benefits in patients diagnosed with ADHD. Historically,
training has followed Protocol 1 or Protocol 3, with slight variation in the size of the
SMR or theta bands. The initial report (Lubar & Shouse, 1976) presented the results of
an SMR training protocol (Protocol 1) in the treatment of an 11-year-old boy diagnosed
with hyperkinesis. In their study, Lubar and Shouse demonstrated an electrophysiological
Table I. Summary of the Primary Findings of Studies Examining the Efficacy of EEG Biofeedback for the
Treatment of ADHD: Selected Case Studies
Participants Method Sessions Outcome
Researchers N Ages Dx Design Protocol N/week Total QEEG Beh. CPT
Lubar & Shouse (1976) 1 11 H 1 1 3 158 (+) (+) (+)
Lubar et al. (1995) 17 8–15 C 0 2 5 30–45 (+) NR NR
Thompson & Thompson 111 5–63 I/H/C 0 1, 3 2 40 (+) NR (+)
Kaiser & Othmer (2000) 186 5–67 I/H/C 0 1a 1–5 20–40+ NR NR (+)
Heywood & Beale (2003) 7 7–12 I/H/C 2 1 NR 80 NR (+*) NR
Note. (+): statistically significant change in score on dependent measure; (+*): statistically significant change
only among participants who completed treatment; NR: not reported. Dx code: I = ADHD, predominately
inattentive; H = ADHD, predominately hyperactive; C = ADHD, combined; design: 0 = Single/multiple case
study, repeated measurement; 1 = Single/multiple case study, ABAB (Reversal); 2 = Single/multiple case Study,
ABAB (Reversal) with placebo control.
aVariation of SMR enhancement/theta suppression protocol.
training effect in the laboratory that was associated with a decrease in off-task and oppositional
behaviors, as well as, increased cooperation and completion of school work in
the classroom. By using an ABA case study design, Lubar and Shouse showed that these
clinical gains paralleled patient increases and decreases in control over SMR activity during
training sessions.
Since the publication of this initial case study, there have been other notable case
reports, the most extensive being Thompson and Thompson’s (1998) study of 111 patients
diagnosed with Attention Deficit Disorder (with and without hyperactivity) and Kaiser and
Othmer’s (2000) investigation of EEG biofeedback in 1089 patients (186 diagnosed with
ADHD). Clinical gains included improved scores on tests of attention and impulse control
(Kaiser & Othmer, 2000; Thompson & Thompson, 1998), as well as, an average increase
of 12 points on the Wechsler Full Scale Intelligence Quotient (Thompson & Thompson).
Table I summarizes the characteristics of several important case-studies.
Initial reports of the enduring nature of EEG biofeedback have been provided by
Tansey (1993) and Lubar (2003). Tansey (1993) reported the results of a 10-year follow-up
study, which indicated that a child (initially treated in the fourth grade) was able to maintain
sustained control over hyperactive symptoms during adolescence and early adulthood.
Lubar (2003) conducted a retrospective study of 52 patients who had completed EEG
biofeedback treatment for ADHD over a 10-year period. During telephone interviews conducted
by an independent surveyor, parents (or older patients) were asked to rate the degree
of improvement in 16 targeted symptoms (e.g. fidgeting, restlessness, overactivity, inattention,
failure to complete tasks, outbursts of temper, low frustration tolerance, relationships
with others) since the completion of treatment. The results of the survey were positive,
with primary improvements noted in sustained control over symptoms of hyperactivity,
emotional lability, rate of completing homework, and report card marks.
As in any field of applied clinical research, case studies are necessary in the development
of new treatments. Through such studies, researchers are able to identify potentially
beneficial intervention strategies, as well as, any potential patient risks. Such is the case
with EEG biofeedback for ADHD. During the last 25 years, several training protocols have
been developed and examined in case studies using a variety of procedures to determine
treatment effects. Examination of the outcomes of these case studies reveals consistently
positive results. Each of the studies reported to date indicated improvements in symptoms
of attention and behavioral control in patients diagnosed with hyperkinesis or ADHD
(Inattentive; Hyperactive-Impulsive; or Combined Types) following treatment with EEG
Biofeedback. No significant adverse effects were reported in the case studies, although
deterioration of clinical effects and relapse has been reported in those case studies in which
training has been discontinued prior to completion of treatment (e.g. Lubar & Shouse,
Despite the positive outcomes reported in case studies, information derived from such
studies is considered insufficient to demonstrate the efficacy of any treatment (Chambless
& Hollon, 1998; LaVaque et al., 2002; Nuwer, 1997). Although meta-analysis studies have
concluded that there is often no difference in terms of outcome between the results of case controlled
and prospective-randomized studies (Benson & Hartz, 2000), case studies do not
provide a method for examining nonspecific factors that may influence the effectiveness of
a particular treatment in applied clinical settings.
In evaluating the efficacy of any type of treatment, it is important to use research
designs that can clarify the degree that beneficial effects are due to factors other than the
specific treatment that was administered (in this case, EEG biofeedback). Such nonspecific
factors include therapist characteristics (e.g. degree of compassion, understanding,
displayed knowledge or confidence), patient characteristics (e.g. patient intelligence and
capacity to learn new skills, severity of the disorder, the degree of hope or expectancy, variations
in patient motivation for participating in the study), and treatment characteristics (e.g.
the administration of a pill; the use of computerized EEG equipment), patient exposure to
other therapeutic experiences, other than the treatment under investigation (e.g. counseling,
tutoring, variations in parenting styles), and maturation. Without controls for such factors,
the percentage of patients likely to respond to any treatment is difficult to estimate.
Two controlled, case studies can serve to illustrate the importance of motivation and
capacity to learn new skills in assessing efficacy. In the mid-1990’s Lubar and his colleagues
reported the outcome of a series of studies, including one examining the efficacy
of EEG biofeedback (Lubar, Swartwood, Swartwood, & Timmerman, 1995). In studying
the effects of theta suppression/beta enhancement (Protocol 3) in 17 children diagnosed
with ADHD, these researchers reported that two groups emerged. One group of children
(n = 6) were unable to demonstrate a training effect on any of the EEG measures obtained
during training. Another group (n = 11) was able to “learn” to increase cortical activation
(by lowering the theta/beta power ratio). Although the association between learning to
control cortical activation via EEG biofeedback and degree of clinical response was not
directly assessed, Lubar et al.’s (1995) paper illustrates the importance of directly assessing
neurophysiological indicators of learning in any evaluation of the efficacy of EEG
Heywood and Beale’s (2003) more recent study of EEG biofeedback in seven children
diagnosed with ADHD provides further impetus for examining such nonspecific factors. In
their study, they provided a “bona fide” biofeedback training protocol designed to promote
an increase of SMR and decrease in theta and beta 2 at Cz. The placebo control training
included “noncontingent” EEG biofeedback in which a series of randomly determined
bandwidths were reinforced or inhibited (e.g. 12–29 Hz; 2–6 Hz; 2–18 Hz). In addition,
Heywood and Beale (2003) used a randomized design with an embedded ABAB reversal, to
control for maturation and treatment sequence effects. Children were not informed whether
the training was bona fide or placebo.
Examination of their findings revealed that five of the children completed training,
two did not. Analysis of results indicated that when the data were analyzed for children
who completed treatment, a significant positive effect was noted on neurophysiological
and behavioral measures of attention. However, when the data from the two children
who discontinued treatment were included, and control for overall trend was added to
the analysis, the overall size of these gains diminished. Although it is difficult to draw
conclusions regarding the efficacy of EEG biofeedback from such a small study, Heywood
and Beale’s work illustrates the importance of reporting the results of “nonresponders” and
controlling for nonspecific factors and trend effects in studies examining the efficacy of
EEG biofeedback.
Overall, the results of case studies illustrate the potential benefits of EEG biofeedback
in the treatment of patients with ADHD. However, it is clear from a review of case studies
that there is a percentage of patients who will not “learn” how to regulate cortical activity
and reduce core ADHD symptoms via EEG biofeedback. In reported case studies, that
percentage is comparable to the number of patients who do not respond to stimulant
medications and ranged from 29% (Heywood & Beale, 2003) to 35% (Lubar et al., 1995).
In addition, the results of the Heywood and Beale (2003) study provides evidence that
nonspecific factors (e.g. expectancy, maturation) need to be evaluated/controlled in efficacy
studies of EEG biofeedback for ADHD.
To date, five controlled-group studies have been reported in peer-reviewed journals
(Carmody et al., 2001; Fuchs et al., 2003; Linden et al., 1996; Monastra et al., 2002; Rossiter
&LaVaque, 1995) [see Table II]. Each of these studies sought to examine the effects of EEG
biofeedback in the treatment of patients diagnosed with ADHD, while attempting to control
for certain factors (e.g. age, intelligence, severity of symptoms prior to initiating treatment).
Table II. Summary of the Primary Findings of Studies Examining the Efficacy of EEG Biofeedback for the
Treatment of ADHD: Controlled Group Studies
Participants Method Sessions Outcome
Researchers N Ages Dx Design Protocol N/week Total QEEG Beh. CPT
Rossiter & LaVaque 46 8–21 I/C 1 1,3 3–5 20 NR (+) (+)
Linden et al. (1996) 18 5–15 I/H/C 0 3 2 40 NR (+) (+)
Carmody et al. (2001) 16 8–10 I/H/C/N 0 1, 3a 3–4 36–48 (-) (+) (+)
Monastra et al. (2002) 100 6–19 I/C 1 3 1 34–50 (+) (+) (+)
Fuchs et al. (2003) 34 8–12 I/H/C 1 2 3 36 NR (+) (+)
Note. (+): statistically significant change in score on dependent measure; (-): no statistically significant change
in score on dependent measure; NR: not reported. Dx code: I = ADHD, predominately inattentive; H = ADHD,
predominately hyperactive; C = ADHD combined; AD/LD = ADHD + learning disorder; N = No psychiatric
disorder. design: 0 = controlled group study, random assignment, waiting list control; 1 = Controlled group
study, nonrandom assignment, bona fide treatment comparison (stimulants).
aVariation of theta/suppression/SMR and beta enhancement protocols.
Maturation effects were also controlled in each of these studies and comparisons with a
“bona fide” treatment that has been classified as efficacious (i.e. stimulant medication) were
included in three of the five studies in order to control for placebo and trend effects.
The first of the controlled studies was published by Rossiter and LaVaque (1995).
This study sought to compare the effects of EEG biofeedback and stimulant medication
(methylphenidate or dextroamphetamine) on a continuous performance test (Test of
Variables of Attention, Greenberg & Dupuy, 1993) and a standardized behavioral rating
scale which assessed ADHD symptoms, as well as indicators of other types of behavioral
problems (Behavior Assessment System for Children). After initial pretesting, patients
were matched for age, intelligence, gender, and diagnosis and treated with one of two
EEG biofeedback protocols (Protocol 1 or Protocol 3) or with stimulant medication (as
prescribed, monitored, and adjusted by the patient’s physician). A total of 46 patients
(aged 8–21) participated in the study. Two groups of 23 patients received the treatment of
their (or parent’s) choice (either medication or 20 sessions of EEG biofeedback). Patients
participating in EEG biofeedback were seen three to five times per week (45–50-min
sessions that included 30 min of feedback)
The results of this study indicated significant improvement on the T.O.V.A. and several
subscales of the BASC (e.g. Hyperactivity, Attention Problems, and Externalizing
Behaviors) in patients who completed EEG biofeedback. In addition, comparison with a
bona fide treatment for ADHD (stimulant medication) revealed no difference in the efficacy
of these treatments after 20 sessions. Similarly, there was no significant difference in the
percentage of patients who showed significant improvement with EEG biofeedback (83%)
and stimulant medication (87%).
The second published controlled group study was reported by Linden et al. (1996).
In this study, 18 children (ages 5–15) diagnosed with ADHD were randomly assigned to
either a “waiting list” condition (and received no psychological treatment or medication)
or EEG biofeedback (Protocol 3). Groups were comprised of an equal number of children
diagnosed with ADHD alone (n = 6) or in combination with a learning disorder (n = 3),
for a total of nine children in each group. Power analysis conducted prior to initiating the
study indicated sufficient sample size to detect significant group statistical differences. The
study was conducted over a six month time period. Patients receiving EEG biofeedback
participated in 40, 45-min training sessions. Medications for ADHD were not prescribed.
The results of the Linden et al. (1996) study reflected a significant increase on a
measure of intelligence (Kaufman Brief Intelligence Scale: Kaufman & Kaufman, 1990)
and a reduction in symptoms of inattention on the IOWA-Conners Behavior Rating Scale
in the group of children who received EEG biofeedback. No adverse results were reported.
A randomized, waiting list, controlled group study was also conducted by Carmody
et al. (2001) in a school setting. In their study, 16 children (ages 8–10) were randomly
assigned to an active treatment condition (EEG biofeedback) or a waiting list. Eight of the
children were diagnosed with ADHD; eight were not diagnosed with ADHD or any other
psychiatric disorder. Although pharmacological treatment had been recommended for all
of the children diagnosed with ADHD, none of their parents selected that type of treatment.
Carmody et al. (2001) utilized a variation of Protocols 1 and 3 in their study. During
the active phase of treatment, participants received 3–4 EEG biofeedback sessions
per week, completing between 36 and 48 sessions during a six month period. Dependent
variables of interest included several QEEG measures (“delta-theta” amplitude; beta amplitude;
SMR amplitude), home and school versions of a behavioral rating scale assessing
frequency of ADHD symptoms (ADDES; McCarney, 1989) and a continuous performance
test (T.O.V.A., Greenberg & Dupuy, 1993).
The results of the Carmody et al. (2001) study indicated that children with ADHD
who were treated with EEG biofeedback reduced symptoms of impulsivity on the T.O.V.A.
and were rated as more attentive by their teachers on the School Version of the ADDES.
However, no consistent pattern of improvement was evident on the QEEG measures selected
by this research team.
Monastra et al. (2002) published the largest, controlled-group study in the literature.
Similar to Rossiter and LaVaque (1995), the effects of EEG biofeedback were compared
with a “bona fide” treatment (Ritalin). In their study, 100 patients (aged 6–19) participated in
a multimodal treatment program that included: stimulant medication (dosage titrated based
on the results of behavioral measures and the T.O.V.A.), a 10 week parenting program
(Monastra, 2004) with subsequent, individualized parent-counseling provided as needed,
and academic support at school (via an Individual Education Plan or 504 Accommodation
Plan). Patients were also given the opportunity to receive EEG biofeedback (Protocol 3)
as part of their treatment program. Fifty-one families chose to include EEG biofeedback
(49 did not). The average dose of Ritalin administered to the patients of both groups was
25 mg (10 mg after breakfast, 10 mg after lunchtime, 5 mg after school). The range was
15–45 mg per day.
EEG biofeedback sessions were conducted on a weekly basis (45–50 min) and continued
until the patient could demonstrate a level of cortical activity on the QEEG scan
that was within 1.0 standard deviation of age peers (Monastra et al., 1999 database) and
could maintain this level of arousal for three consecutive, training sessions (40 min each).
The average number of sessions needed to reach this goal was 43 (range 34–50). All of the
participants who received EEG biofeedback achieved this goal.
Pretreatment screening included tests of intelligence, behavioral rating scales, a continuous
performance test, and a QEEG assessment (Monastra et al., 1999). All of the
participants needed to demonstrate evidence of cortical slowing on the QEEG measure in
order to be included in the study. There were no significant differences on pretreatment
measures between patients who received EEG biofeedback as part of their treatment and
those who did not.
Posttreatment evaluation was conducted 1 year after initial evaluation, under two
conditions. First, participants were evaluated while continuing to take stimulant medication.
Subsequent to this assessment, medication was discontinued for 1 week, and participants
were evaluated following this medication “wash-out.” All participants remained in the study
for the year required to complete this research.
Results of the Monastra et al. (2002) study supported the efficacy of stimulant medication
as well as EEG biofeedback, and indicated that parenting style was a moderating
factor in both treatments. In their study, significant improvement was noted in both groups
on posttreatment evaluations that were conducted while the patients were using medication.
However, following a week-long medication wash-out, relapse was noted on behavioral and
CPT measures in each of the participants who had not received EEG biofeedback and no
sustained improvement was noted on the QEEG measure among the members of that group.
In contrast, patients who received EEG biofeedback as part of their treatment demonstrated
sustained improvement on the T.O.V.A. and on behavioral measures, and maintained
gains on QEEG measures of cortical arousal even when tested after a 1-week medication
washout. In both the EEG biofeedback and the “non-biofeedback” groups, parents who
were systematically using the strategies taught in the parenting program had children who
displayed fewer attentional and behavioral control problems at home.
The fifth controlled-group study was reported by Fuchs et al. (2003). In this study,
a comparison between EEG biofeedback and a bona fide treatment for ADHD (stimulant
medication) was investigated. A total of 34 children (aged 8–12) participated in the study.
Twelve were treated with Ritalin (mean dose: 10 mg, t.i.d.; Range: 10–60 mg per day).
Neurofeedback sessions (Protocol 2) were conducted three times per week (30–60 min in
duration). All participants were treated for a 12-week period. Assignment to the treatment
groups was based on parental preference.
As with the other controlled-group studies, pretreatment measures included a test of
intelligence (WISC-R), computerized tests of attention (T.O.V.A.; the Attention Endurance
Test, Brickenkamp, 1994), and behavioral rating scales (IOWA-Conners Behavior Rating
Scale). Statistical analysis of pretreatment measures indicated that the groups were
comparable in terms of intelligence and severity of impairment associated with ADHD.
Posttreatment analysis revealed that both EEG biofeedback and Ritalin were associated
with significant improvements on computerized tests of attention and on behavioral rating
scales. The degree of improvement noted in patients treated with EEG biofeedback was
comparable with that noted in patients treated with Ritalin. No adverse effects were reported.
Controlled-group studies of EEG biofeedback in the treatment of ADHD have demonstrated
beneficial effects of EEG biofeedback on measures of intelligence, on behavioral
ratings scales assessing the frequency of the core symptoms of ADHD, on computerized
tests of attention, and on QEEG measures of cortical arousal. In contrast to case-studies,
these studies have compared patient outcomes obtained following EEG biofeedback training
with those noted following a bona fide treatment of ADHD (stimulant medication),
as well as a waiting list control. These consistent reports of significant, beneficial effects
in controlled, group studies following the use of a nonpharmacological treatment (EEG
biofeedback), represents a significant step in the identification of effective psychological
treatments for ADHD. To date, no other type of psychological treatment has been
demonstrated to exert a significant effect on the core symptoms of ADHD (i.e. inattention,
hyperactivity, and impulsivity).
Despite the positive results of studies examining the efficacy of EEG biofeedback,
data from controlled-group studies that randomly assign participants to EEG biofeedback
or comparison groups (e.g., stimulant medication, noncontingent biofeedback, or a waiting
list control group that has comparable amount of therapist contact) are needed in order to
clarify the percentage of patients diagnosed with ADHD who will respond to EEG biofeedback
in clinical practice. Although the studies reported to date have indicated a positive
response in over 75% of patients treated with EEG biofeedback, these studies have been
conducted by highly experienced therapists, with patients who volunteered to receive this
type of treatment. As such, the number of “treatment responders” and the degree of clinical
improvement reported in these studies may exceed results obtained in clinical practice.
As noted previously, differences in patient characteristics (e.g. motivation for change,
expectancy or hope that a new treatment will “work,” interest in learning new skills) and
in therapist characteristics (e.g. degree of compassion, understanding of protocols, level of
confidence displayed in sessions, ability to conduct treatment sessions with a high degree
of fidelity) can affect response to treatment. Randomized, controlled-group studies that
monitor and control for such factors are still needed. Such studies will facilitate a better
understanding of the percentage of patients likely to respond to EEG biofeedback for
ADHD in clinical practice.
The Guidelines for Evaluation of Clinical Efficacy of Psychophysiological Interventions
(LaVaque et al., 2002), which have been accepted by the Association for Applied
Psychophysiology & Biofeedback (AAPB) and the International Society for Neuronal
Regulation (ISNR), specify five types of classification for the effectiveness of biofeedback
procedures, ranging from “Not empirically supported” to “Efficacious and Specific.” The
requirements for each classification level is summarized below.
Criteria for Levels of Evidence of Efficacy
Level 1: Not empirically supported. This classification is assigned to those treatments that
have only been described and supported by anecdotal reports and/or case studies in
non-peer reviewed journals.
Level 2: Possibly efficacious. This classification is considered appropriate for those treatments
that have been investigated in at least one study that had sufficient statistical
power, well identified outcome measures, but lacked randomized assignment to a control
condition internal to the study.
Level 3: Probably efficacious. Treatment approaches that have been evaluated and shown
to produce beneficial effects in multiple observational studies, clinical studies, wait list
control studies, and within-subject and between-subject replication studies merit this
Level 4: Efficacious. In order to be considered “efficacious,” a treatment must meet the
following criteria:
(a) In a comparison with a no-treatment control group, alternative treatment group,
or sham (placebo) control utilizing randomized assignment, the investigational
treatment is shown to be statistically significantly superior to the control condition
or the investigational treatment is equivalent to a treatment of established
efficacy in a study with sufficient power to detect moderate differences;
(b) The studies have been conducted with a population treated for a specific problem,
from whom inclusion criteria are delineated in a reliable, operationally
defined manner;
(c) The study used valid and clearly specified outcome measures related to the
problem being treated;
(d) The data are subjected to appropriated data analysis;
(e) The diagnostic and treatment variables and procedures are clearly defined in a
manner that permits replication of the study by independent researchers, and
(f) The superiority or equivalence of the investigational treatment have been shown
in at least two independent studies” (LaVaque et al., 2002, p. 280).
Level 5: Efficacious and Specific. To meet the criteria for this classification, the treatment
needs to be demonstrated to be statistically superior to a credible sham therapy, pill, or
bona fide treatment in at least two independent studies.
Review of the scientific literature revealed both controlled case and group studies on
the effects of EEG biofeedback in treating the core symptoms of ADHD. These studies
examined the efficacy of well-defined treatment protocols in the treatment of patients diagnosed
with hyperkinesis, as well as, those diagnosed with each of the primary subtypes of
ADHD (Inattentive, Hyperactive-Impulsive, or Combined). The results of these studies indicated
improvement on standardized tests of intelligence, attention, and behavioral control
following EEG biofeedback. Increased level of cortical arousal was also reported during
QEEG examination of patients treated with EEG biofeedback. Comparisons with a bona
fide treatment for ADHD (stimulant medication) indicated that EEG biofeedback yielded
equivalent or superior results. The results of randomized, controlled group studies using
a waiting list control also indicated the superiority of EEG biofeedback. Such findings
suggest the efficacy of EEG biofeedback in the treatment for ADHD.
However, because of the small sample size in the two, randomized group studies
reported, and the absence of control for patient and therapist characteristics that could
influence outcome in any of the five, controlled-group studies, our determination (based
on AAPB/ISNR Guidelines) is that EEG biofeedback is probably efficacious for the treatment
of ADHD. Although it is clear from the outcomes of each of the published case
and controlled studies of EEG biofeedback for ADHD, that significant, beneficial effects
have consistently been reported in patients/families who volunteered to receive this type
of treatment, additional controlled, group studies (with random assignment to treatment
condition) are needed in order to promote a clearer understanding of the number of patients
and degree of improvement that can be anticipated in clinical practice.
Selection Criteria
The following exclusion criteria have been utilized in case and controlled-group studies
of biofeedback for ADHD. The treatment protocols described in this paper have not been
systematically evaluated in individuals with the following characteristics:
• Age under 6 years,
• mental retardation,
• presence of another medical or psychiatric condition known to adversely affect
attention or behavioral control (e.g. anemia; hypoglycemia; diabetes; psychosis,
severe depression, or bi-polar disorder),
• history of neurological disease (including seizure; traumatic brain injury),
• substance abuse or dependence, and
• families with significant marital discord that interferes with participation in the
treatment process.
Training Protocols
The following protocols for EEG biofeedback training for ADHD have been supported
by controlled group studies. However, given recent findings indicating at least
two neurophysiological subtypes of ADHD, QEEG evaluation of the patient may be
helpful prior to initiating any of these training procedures. Such databased comparisons
of a patient with healthy age peers can be useful in defining the location and type of
EEG abnormality(ies) and contribute to the selection of a particular treatment protocol:
Protocol 1: SMR Enhancement/Theta Suppression
Electrode placement C3 or C4 (linked ear lobe reference)
Reward frequency 12–15 Hz
Inhibit frequency 4–7 or 4–8 Hz
Duration of behavior needed to obtain
reward (auditory/visual)
0.5 s.
Sampling rate 128 Hz (minimum)
Rate of reward Initial settings for REEG and IEEG should
provide approximately 15–20 auditory/
visual “rewards” per minute
Clinical goals Improve behavioral control, reduce symptoms
of hyperactivity and impulsivity
Protocol 2: SMR Enhancement/Beta-2 Suppression
Electrode placement C4 (linked ear lobe reference)
Reward frequency 12–15 Hz
Inhibit frequency 22–30 Hz
Duration of behavior needed to obtain
reward (auditory/visual)
0.5 s.
Sampling rate 128 Hz (Minimum)
Rate of reward Same as Protocol 1
Clinical goal Improve behavioral control, reduce symptoms
of hyperactivity and impulsivity
Protocol 3: Theta Suppression/Beta Enhancement
Electrode placement Cz or C3 (linked ear lobe reference)
FCz-PCz (ear lobe reference)
Cz-Pz (ear lobe reference)
Reward frequency 16–20 Hz
Inhibit frequency 4–8 Hz*
Duration of behavior needed to Obtain
reward (auditory/visual)
0.5 s.
Sampling rate 128 Hz (Minimum)
Rate of reward Same at Protocol 1.
Clinical goal Improve attention and behavioral control,
primarily in patients with cortical slowing.
*Lubar (2003) also reports a training protocol
that reinforces suppression of an expanded
“alpha” range (6–10 Hz) when
treating adolescents and adults with this
protocol. However, this has not been evaluated
in controlled, clinical group studies.
Treatment Schedules
Positive response has been noted with both massed (3–5 sessions per week) and spaced
(1 session per week) training. Sessions range in duration from 30–45 min of biofeedback
training. In each session, a “baseline” or “warm-up” condition is initially conducted, during
which no feedback is provided (2–5 minutes in duration). Subsequently, “training” segments
are conducted and EEG biofeedback is provided. The duration of these training segments
varies, often beginning with 5-min periods, gradually increasing to 9–10 min depending on
patient learning curves and clinical response.
Course of treatment is variable, ranging from 20 to 50 sessions. Calculation and
review of quantitative indicators of patient progress at the conclusion of each session (e.g.
microvolts of theta, beta-1, beta-2, or SMR; percentage of time that the patient exceeds
reward or inhibitory thresholds) and examination of the graphic depiction of such data is
critical in shaping the training protocol. Additionally, information derived from continuous
performance tests and behavioral rating scales is useful in evaluating patient progress.
Adverse Effects
Although no side-effects were reported in case or controlled studies, those clinical
researchers who have examined the effects of EEG biofeedback in conjunction with stimulant
medication have noted increased irritability, moodiness, and hyperactivity in patients
who are being treated with both types of treatments concurrently (Lubar, 2003; Monastra,
2003). This type of occurrence appears during the mid to late phases of biofeedback training,
most commonly in patients who are demonstrating improved cortical activation via
EEG biofeedback. Reduction in the dosage of stimulant medication (with or without introduction
of a “nonstimulatory” ADHD medication) has been associated with elimination
of this type of side effect. Other side effects (headaches; dizziness) can occur in 1–3% of
patients, but typically respond to a brief resting period (30 min) or consumption of food.
Adjunctive Treatments
Because ADHD has been associated with significant impairment of educational performance,
collaboration between the clinician and teachers is recommended, in order to
promote the child’s success at school during the treatment process. In the United States,
students with ADHD are entitled to either an Individual Education Plan (I.E.P.) or the
development of a 504 Accommodation Plan, depending on their need for special education
services. Such plans are intended to identify specific areas of functional impairment associated
with ADHD (e.g. disorganization, difficulty completing school assignments in class
and at home, and poor study skills) and define interventions to provide accommodation
and remediation for these problems. Whether specified via an I.E.P., an Accommodation
Plan, or an informal arrangement with teachers, efforts to ensure that patients are receiving
assistance at school typically improve classroom performance, reduce stress at home and
create a less conflictual learning environment for the child.
Parent counseling is also recommended in the treatment of children with ADHD.
Specifically, teaching parents strategies for systematically using reinforcement principles
has been shown to enhance EEG biofeedback treatments for ADHD (Monastra et al., 2002).
Similarly, social skills training programs, utilizing contingency management strategies (i.e.
point/token reward systems, time-out, and response cost) have been shown to promote
improved classroom functioning and the development of positive peer relationships in
children diagnosed with ADHD (see review by Pelham, 2002).
None of the traditional psychotherapeutic techniques that have been effective in treating
other disorders has been determined to be efficacious in the treatment of the core symptoms
of ADHD (i.e. inattention, hyperactivity, and impulsivity). As reported in the NIH
Consensus Statement on the Diagnosis and Treatment of ADHD (1998), insight-oriented
treatments do not exert a significant effect on these symptoms. Similarly, more recently
developed “cognitive-behavioral” treatments (e.g. self-monitoring, verbal self-instruction,
problem-solving training, self-reinforcement) have also failed to promote improvement in
the primary symptoms of ADHD or significant changes in the behavior or academic functioning
of children diagnosed with ADHD (Abikoff et al., 1988; Bloomquist, August, &
Ostrander, 1991; Brown, Borden, Wynne, Spunt, & Clingerman, 1987; National Institute
of Health [NIH], 1998). However, children and teens who are being subjected to parental
neglect or abuse will often respond favorably to individual and family therapy (as well as
community-based interventions from Child Protective Agencies) that address these issues.
Abikoff, H., Ganeles, D., Reiter, G., Blum, C., Foley, C., & Klein, R. (1988). Cognitive training in academically
deficient ADD-H boys receiving stimulant medication. Journal of Abnormal Child Psychology, 16(24),
Aylward, E. E., Reiss, A. L., Reader, M. J., Singer, H. S., Brown, J. E., & Denckla, M. B. (1996). Basal ganglia
volumes in children with attention-deficit hyperactivity disorder. Journal of Child Neurology, 11, 112–115.
American Psychiatric Association. (1994). Diagnostic and statistical manual of mental disorders (4th ed.).
Washington, DC: Author.
Barkley, R. A. (1998). Attention-deficit hyperactivity disorder: A handbook for diagnosis and treatment (2nd ed.).
New York: Guilford Press.
Biederman, J., Faraone, S., Keenan, K., Benjamin, J., Krifcher, B., Moore, C., et al. (1992). Further evidence for
family-genetic risk factors in attention deficit hyperactivity disorder: Patterns of comorbidity in probands and
relatives in psychiatrically and pediatrically referred samples. Archives of General Psychiatry, 49, 728–738.
Biederman, J., Faraone, S. V., Mick, E., Spencer, T., Wilens, T., Kiely, K., et al. (1995). High risk for attention
deficit hyperactivity disorder among children of parents with childhood onset of the disorder: A pilot study.
American Journal of Psychiatry, 152, 431–435.
Biederman, J., Faraone, S., Milberger, S., Guite, J., Mick, E., Chen, L., et al. (1996). A prospective 4-year
follow-up study of attention-deficit hyperactivity and related disorders. Archives of General Psychiatry, 53,
Biederman, J., Keenan, K., & Faraone, S. V. (1990). Parent-based diagnosis of attention deficit disorder predicts
a diagnosis based on teacher report. Journal of the American Academy of Child and Adolescent Psychiatry,
33, 842–848.
Benson, K., & Hartz, A. J. (2000). A comparison of observational studies and randomized, controlled trials, New
England Journal of Medicine, 342(25), 1878–1886.
Bloomquist, M. L., August, G. J., & Ostrander, R. (1991). Effects of a school-based cognitive-behavioral intervention
for ADHD children. Journal of Abnormal Child Psychology, 19, 591–605.
Brickenkamp, R. (1994). Test d2, Aufmerksamkeits-Belastungs-Test (8th ed.), Gottingen: Hogrefe. (Test d2.
Attention test)
Brown, R. T., Borden, K. A., Wynne, M. E., Spunt, A. L., & Clingerman, S. R. (1987). Compliance with
pharmacological and cognitive treatment for attention deficit disorder. Journal of the American Academy of
Child and Adolescent Psychiatry, 26, 521–526.
Carmody, D. P., Radvanski, D. C., Wadhwani, S., Sabo, M. J., & Vergara, L. (2001). EEG biofeedback training
and attention-deficit/hyperactivity disorder in an elementary school setting. Journal of Neurotherapy, 43(3),
Castellanos, F.X. (1997). Toward a pathophysiology of attention-deficit/hyperactivity disorder. Clinical Pediatrics,
36, 381–393.
Castellanos, F. X., Giedd, J. N., Eckburg, P., Marsh, W. L., Vaituzis, A. C., Kaysen, D., et al. (1994). Quantitative
morphology of the caudate nucleus in attention deficit hyperactivity disorder. American Journal of Psychiatry,
151, 1791–1796.
Chabot, R. A., & Serfontein, G. (1996). Quantitative electroencephalographic profiles of children with attention
deficit disorder. Biological Psychiatry, 40, 951–963.
Chabot, R. A., Merkin, H., Wood, L. M., Davenport, T. L., & Serfontein, G. (1996). Sensitivity and specificity
of QEEG in children with attention deficit or specific developmental learning disorders. Clinical Electroencephalography,
27, 26–34.
Chabot,R. A., Orgill, A. A., Crawford, G., Harris, M. J.,&Serfontein,G. (1999).Behavioral and electrophysiologic
predictors of treatment response to stimulants in childrenwith attention disorders, Journal of Child Neurology,
14(6), 343–351.
Chambless, D. L., & Hollon, S. D. (1998). Defining empirically supported therapies. Journal of Consulting and
Clinical Psychology, 66(1), 7–18.
Clarke, A. R., Barry, R. J., McCarthy, R., & Selikowitz, M. (1998). EEG analysis in attention-deficit/hyperactivity
disorder: A comparative study of two subtypes. Psychiatry Research, 81, 19–29.
Clarke, A. R., Barry, R. J., McCarthy, R., & Selikowitz, M. (2001a). Electroencephalogram differences in two
subtypes of attention-deficit/hyperactivity disorder. Psychophysiology, 38, 212–221.
Clarke, A. R., Barry, R. J., McCarthy, R., & Selikowitz, M. (2001b). Excess beta activity in children with
attention-deficit/hyperactivity disorder: An atypical electro-physiological group. Psychiatry Research, 103,
Claude, D., & Firestone, P. (1995). The development of ADHD boys: A 12 year follow-up. Canadian Journal of
Behavioral Science, 27, 226–249.
Comings, D. E., Wu, S., Chiu, C., Ring, R. H., Gade, R., Ahn, C., et al. (1996). Polygenic inheritance of Tourette
syndrome, stuttering, attention deficit hyperactivity, conduct, and oppositional defiant disorders: The additive
and subtractive effect of the three dopaminergic genes-DRD2,DBH, andDAT1. American Journal of Medical
Genetics, 67(3), 264–288.
Cook, E. H., Stein, M. A., Krasowski, M. D., Cox, N. J., Olkon, D. M., Kieffer, J. E., et al. (1995). Association
of attention deficit disorder and the dopamine transporter gene. American Journal of Human Genetics, 56,
Ding, Y. S., Fowler, J., Volkow, N., Dewey, S., Wang, G. J., Logan, J., et al. (1997). Clinical drugs: Comparison
of the pharmacokinetics of [11 C]d-threo and 1-threo-methylphenidate in the human and baboon brain.
Psychopharmacology, 131, 71–78.
Ernst, M., Liebenauer, L. L., King, A. C., Fitzgerald, G. A., Cohen, R. M., & Zametkin, A. J. (1994). Reduced
brain metabolism in hyperactive girls. Journal of the American Academy of Child and Adolescent Psychiatry,
33(6), 858–868.
Fuchs, T., Birbaumer, N., Lutzenberger, W., Gruzelier, J. H., & Kaiser, J. (2003). Neurofeedback treatment
for attention-deficit/hyperactivity disorder in children: A comparison with methylphenidate. Applied Psychophysiology
and Biofeedback, 28(1), 1–12.
Gadow, K. D., & Sprafkin, J. (1997). Child symptom inventory 4: Norms manual. Stony Brook, NY: Checkmate
Giedd, J. N., Castellanos, F. X., Casey, B. J., Kozuch, P., King, A. C., Hamburger, S. D., et al. (1994). Quantitative
morphology of the corpus callosum in attention deficit hyperactivity disorder. American Journal of Psychiatry,
151, 665–669.
Greenberg, L.M., & Dupuy, T. R. (1993). Interpretation manual for the test of variables of attention. Los Alamitos,
CA: Universal Attention Disorders.
Greenhill, L. L., Halperin, J. M., & Abikoff, H. (1999). Stimulant medications. Journal of the American Academy
of Child and Adolescent Psychiatry, 38(5), 503–512.
Hartsough, C. S., & Lambert, N. M. (1985). Medical factors in hyperactive and normal children: Prenatal,
developmental, and health history findings. American Journal of Orthopsychiatry, 55, 190–210.
Heywood, C., & Beale, I. (2003). EEG biofeedback vs placebo treatment for attention-deficit/hyperactivity
disorder: A pilot study. Journal of Attention Disorders, 7(1), 41–53.
Hynd, G. W., Hern, K. L., Novey, E. S., & Eliopulos, D. (1993). Attention deficit-hyperactivity disorder and
asymmetry of the caudate nucleus. Journal of Child Neurology, 8, 339–343.
Hynd, G. W., Semrud-Clikeman, M., Lorys, A. R., & Novey, E. S. (1990). Brain morphology in developmental
dyslexia and attention deficit disorder/hyperactivity. Archives of Neurology, 47, 919–926.
Kaiser, D. A., & Othmer, S. (2000). Effect of neurofeedback on variables of attention in a large multi-center trial.
Journal of Neurotherapy, 4(1), 5–28.
Kim, B.-N., Lee, J.-S., Shin, M.-S., Cho, S.-C., & Lee, D.-S. (2002). Regional cerebral perfusion abnormalities
in attention deficit/hyperactivity disorder: Statistical parametric mapping analysis. European Archives of
Psychiatry and Clinical Neuroscience, 252, 219–225.
Kaufman, A., & Kaufman, N. (1990). K-BIT: Kaufman brief intelligence test manual. Circle Pines, MN: American
Guidance Service.
Lahey, B. B., Pelham, W. E., Stein, M. A., Loney, J., Trapani, C., Nugent, K., et al. (1998). Validity of DSM-IV
attention-deficit/hyperactivity disorder for younger children. Journal of the American Academy of Child and
Adolescent Psychiatry, 37(7), 695–702.
LaVaque, T. J., Hammond, D. C., Trudeau, D., Monastra, V. J., Perry, J., & Lehrer, P. (2002). Template for
developing guidelines for the evaluation of the clinical efficacy of psychophysiological interventions. Applied
Psychophysiology and Biofeedback, 27(4), 273–281.
Levy, R., Hay, D. A., McStephen, M., Wood, C., & Waldman, I. (1997). Attention-deficit hyperactivity disorder:
A category or a continuum? Genetic analysis of a large-scale twin study. Journal of the American Academy
of Child and Adolescent Psychiatry, 36, 737–744.
Linden, M., Habib, T., & Radojevic, V. (1996). A controlled study of the effects of EEG biofeedback on cognition
and behavior of children with attention deficit disorder and learning disabilities. Biofeedback and Self-
Regulation, 21(1), 35–49.
Lou, H. C., Henriksen, L., & Bruhn, P. (1990). Focal cerebral hypoperfusion in children with dysphasia and/or
attention deficit disorder. Archives of Neurology, 41(8), 825–829.
Lubar, J. F. (2003) Neurofeedback for the management of attention deficit disorders. In M. S. Schwartz &
F. Andrasik (Eds.), Biofeedback: A practitioner’s guide (3rd ed., pp. 409–437). New York: Guilford Press.
Lubar, J. O., & Lubar, J. F. (1984). Electroencephalographic biofeedback of SMR and beta for treatment of
attention deficit disorders in a clinical setting. Biofeedback and Self Regulation, 9, 1–23.
Lubar, J. F., & Shouse, M. N. (1976). EEG and behavioral changes in a hyperkinetic child concurrent with training
of the sensorimotor rhythm (SMR): A preliminary report. Biofeedback and Self Regulation, 1, 293–306.
Lubar, J. F., Swartwood, M. O., Swartwood, J. N., & Timmermann, D. L. (1995). Quantitative EEG and auditory
event-related potentials in the evaluation of attention-deficit disorder: Effects of methylphenidate and implications
for neurofeedback training. Journal of Psychoeducational Assessment Monographs, (Special ADHD
Issue). 143–160.
Mann, C., Lubar, J., Zimmerman, A., Miller, C., & Nuenchen, R. (1992).Quantitative analysis of EEG in boys with
attention-deficit-hyperactivity disorder: Controlled study with clinical implications. Pediatric Neurology, 8,
Mannuzza, S., Gittelman-Klein, R., Bessler, A., Malloy, P., & LaPadula, M. (1993). Adult outcome of hyperactive
boys: Educational achievement, occupational rank, and psychiatric status. Archives of General Psychiatry,
50, 565–576.
Mannuzza, S., Klein, R. G., Bessler, A., Malloy, P., & LaPadula, M. (1998). Adult psychiatric status of hyperactive
boys grown up. American Journal of Psychiatry, 155, 493–498.
Mannuzza, S., Klein, R. G., Bonagura, N., Malloy, P., Giampino, H., & Addalli, K. A. (1991). Hyperactive boys
almost grown up: Replication of psychiatric status. Archives of General Psychiatry, 48, 77–83.
McCarney, S. B. (1989). Attention Deficit Disorders Evaluation Scale. Columbia, MO: Hawthorne Educational
Services, Inc.
Monastra, V. J. (2003). Clinical applications of electroencephalographic biofeedback. In M. S. Schwartz &
F. Andrasik (Eds.), Biofeedback: A practitioner’s guide (3rd ed., pp. 438–463). New York: Guilford Press.
Monastra, V. J. (2004). Parenting children with ADHD: Lessons that medicine cannot teach. Washington, DC:
American Psychological Association.
Monastra, V. J., Lubar, J. F., & Linden, M. (2001). The development of a quantitative electroencephalographic
scanning process for attention deficit-hyperactivity disorder: Reliability and validity studies. Neuropsychology,
15, 136–144.
Monastra, V. J., Lubar, J. F., Linden, M., VanDeusen, P., Green, G., Wing, W., et al. (1999). Assessing attention
deficit hyperactivity disorder via quantitative electroencephalography: An initial validation study.
Neuropsychology, 13(3), 424–433.
Monastra, V. J., Monastra,D.M., & George, S. (2002). The effects of stimulant therapy, EEG biofeedback, and parenting
style on the primary symptoms of attention-deficit/hyperactivity disorder. Applied Psychophysiology
and Biofeedback, 27(4), 231–249.
Mostofsky, S. H., Reiss, A. L., Lockhart, P., & Denckla, M. B. (1998). Evaluation of cerebellar size in attention deficit
hyperactivity disorder. Journal of Child Neurology, 13, 434–439.
Murphy, K., & Barkley, R. A. (1996). Attention deficit hyperactivity disorder adults: Comorbidities and adaptive
impairments. Comprehensive Psychiatry, 37, 393–401.
National Institutes of Health. (1998). Consensus statement on the diagnosis and treatment of attention deficit/
hyperactivity disorder. Bethesda, MD: Author.
Nuwer, M. (1997).Assessment of digital EEG, quantitative EEG, and EEG brain mapping: Report of the American
Academy of Neurology and the American clinical Neurophysiology Society, Neurology, 49, 277–292.
Pelham, W. E. (2002). Psychosocial interventions for ADHD. In P. S. Jensen & J. R. Cooper (Eds.). Attention
deficit hyperactivity disorder: State of the science: Best Practices (pp. 12-1–12-36), Kingston, NJ: Civic
Research Institute.
Pelham, W. E., Gnagy, E. M., Greenslade, K. E., & Milich, R. (1992). Teacher ratings of DSM-III-R symptoms
for the disruptive behavior disorders. Journal of the American Academy of Child and Adolescent Psychiatry,
31, 210–218.
Pelham, W. E., & Murphy, H. H. (1986). Attention deficit and conduct disorder. In M. Hersen (Ed.), Pharmacological
and behavioral treatment: An integrative approach (pp. 108–148). New York: Wiley.
Pelham, W. J., & Smith, B. H. (2000) Prediction and measurement of individual responses to ritalin by children
and adolescents with ADHD. In L. Greenhill & B. Osman (Eds.), Ritalin: Theory and patient management
(2nd ed.). New York: Mary Ann Liebert.
Rossiter, T. R., & LaVaque, T. J. (1995). A comparison of EEG biofeedback and psycho-stimulants in treating
attention deficit/hyperactivity disorders. Journal of Neurotherapy, 1, 48–59.
Roth, S. R., Sterman, M. B., & Clemente, C. C. (1967). Comparison of EEG correlates of reinforcement, internal
inhibition, and sleep. Electroencephalography and Clinical Neurophysiology, 23, 509–520.
Semrud-Clikeman, M., Filipek, P. A., Biederman, J., & Steingard, R. (1994). Attention-deficit hyperactivity disorder:
Magnetic resonance imaging morphometric analysis of the corpus callosum. Journal of the American
Academy of Child and Adolescent Psychiatry, 33, 875–881.
Sieg, K. G., Gaffney, G. R., Preston, D. F., & Hellings, J. A. (1995). SPECT brain imaging abnormalities in
attention deficit hyperactivity disorder. Clinical Nuclear Medicine, 20(1), 55–60.
Silberg, J., Rutter, M., Meyer, J., Maes, H., Hewitt, J., Simonoff, E., et al. (1996). Genetic and environmental
influences on the covariation between hyperactivity and conduct disturbance in juvenile twins. Journal of
Child Psychology and Psychiatry and Allied Disciplines, 37, 803–816.
Smalley, S. L., Bailey, J. N., Palmer, C. G., Cantwell, D. PO., McGough, J. J., Del-Homme, M. A., et al. (1998).
Evidence that the dopamine D4 receptor is a susceptibility gene in attention deficit hyperactivity disorder.
Molecular Psychiatry, 3, 427–430.
Sterman, M. B. (1996). Physiological origins and functional correlates of EEG rhythmic activities: Implications
for self-regulation. Biofeedback and Self-Regulation, 21(1), 3–49.
Sterman, M. B. (2000). Basic concepts and clinical findings in the treatment of seizure disorders with EEG operant
conditioning. Clinical Electroencephalography, 31, 45–55.
Sterman, M. B., &Wywricka,W. (1967). EEG correlates of slep: Evidence for separate forebrain substrates. Brain
Research, 6, 143–163.
Sterman, M. B., Wywricka, W., & Roth, S. R. (1969). Electrophysiological correlates and neural substrates of
alimentary behavior in the cat. Annals of the New York Academy of Science, 157, 723–739.
Still, G. F. (1902). Some abnormal psychical conditions in children. Lancet, 1, 1008–1012, 1077–1082, 1163–
Swanson, J. M., McBurnett, K., Christian, D. L., & Wigal, T. (1995). Stimulant medication and treatment of
children with ADHD. In T. H. Ollendick & R. J. Prinz (Eds.), Advances in clinical child psychology (Vol.
17, pp. 265–322). New York: Plenum Press.
Tansey, M. (1993). Ten-year stability of EEG biofeedback results for a hyperactive boy who failed the fourth
grade perceptually impaired class. Biofeedback and Self-Regulation, 18(1), 33–38.
Thompson, L., & Thompson, M. (1998). Neurofeedback combined with training in metacognitive strategies:
Effectiveness in students with ADD. Applied Psycho-physiology and Biofeedback, 23(4), 243–263.
Tredgold, A. F. (1908). Mental deficiency (amentia). New York: W. Wood.
Volkow, N. D., Ding, Y. S., Fowler, J. S., Wang, G. J., Logan, J., Gatley, J. S., et al. (1995). Is methylphenidate
like cocaine? Studies on their pharmacokinetics and distribution in the human brain. Archives of General
Psychiatry, 52, 456–463.
Weiss, G., & Hechtman, L. (1993). Hyperactive children grown up (2nd ed.). New York: Guilford Press.
Welner, Z., Welner, A., Stewart, M., Palkes, H., & Wish, E. (1977). A controlled study of siblings of hyperactive
children. Journal of Nervous and Mental Disease, 165, 110–117.
Willcut, E. G., Pennington, B. F., & DeFries, J. C. (2000). Twin study of the etiology of comorbidity between
reading disability and attention-deficit/hyperactivity disorder. American Journal of Medical Genetics, 96,
Wolraich, M. L., Hannah, J. N., Pinnock, T. Y., Baumgaertel, A., & Brown, J. (1996). Comparison of diagnostic
criteria for attention-deficit hyperactivity disorder in a country wide sample. Journal of the American Academy
of Child and Adolescent Psychiatry, 35, 319–324.
Wywricka, W., & Sterman, M. B. (1968). Instrumental conditioning of sensorimotor cortex EEG spindles in the
waking cat. Physiology and Behavior, 3, 703–707.
Zametkin, A. J., Nordahl, T. E., Gross, M., King, A. C., Semple, W. E., Rumsey, J., et al. (1990). Cerebral
glucose metabolism in adults with hyperactivity of childhood onset. New England Journal of Medicine, 323,

Print it Printer-friendly version

Related content

Olympic Peak Performance Training with Biofeedback
CBS TV news on ADD
Neurofeedback Bibliography

© Copyright 2004, Gary Ames
Terms | About