This unit covers the Clinical uses and efficacy of EEG biofeedback (VI-D).
Students completing this unit will be able to discuss:
Clinicians monitor EEG activity using the International 10-20 System for standardized electrode placement. They often record from several sites and measure the amplitude of EEG signals within frequency bands (like alpha and theta) to provide a more complete picture of brain activity. The Quantitative EEG (QEEG) measures EEG amplitudes within selected frequency bands. EEG topography displays the QEEG on a cortical surface map to show the spatial distribution of EEG activity.
The International 10-20 System is a standardized system for EEG electrode placement based on the distance from the nasion to the inion (front to back of the skull) and left preauricular notch to the right preauricular notch (side to side). The standard 19 active electrode positions are found taking either 10% or 20% of the two distances. The two reference electrodes are usually placed on the earlobes.
Neurofeedback training procedures can be divided into amplitude control and frequency control methods. Frequency control is preferred because it results in more precise EEG control.
Amplitude control methods train patients to increase EEG amplitude (signal strength) instead of frequency. This training strategy can raise the amplitude of both a target rhythm (beta) and an unwanted rhythm (alpha) since it does not teach frequency discrimination. This may result in worse clinical outcomes than a frequency control strategy since control is less refined (Fahrion, 1988).
Frequency control methods teach patients to increase the amplitude of one frequency (SMR) while suppressing another (theta). This procedure refines EEG control and may result in better clinical outcomes than amplitude control (learning to raise the amplitude of one or more frequencies) (Fahrion, 1988).
Below is a BioTrace+ / NeXus-10 EEG assessment screen showing the raw EEG signal, spectral amplitudes, and a three-dimensional topographical plot of amplitude, frequency, and time that can be viewed in real-time. The raw EEG signal display is critical because it can reveal contamination by artifact.
Menninger ON-OFF-ON EEG training teaches a patient to increase the amplitude within a frequency band, reduce the amplitude, and then increase the amplitude again during 100 s or 200 s segments. Example, a patient may increase 8-13 Hz alpha activity for 100 s, decrease it for 100 s, and then increase it for 100 s. This approach may produce superior control when compared to procedures that only train alpha or theta increase (Norris, 1988).
The Menninger alpha-theta protocol, places the active electrode 1 cm above and left of the inion (the bony prominence located on the back of the head) with a reference on the left earlobe. This protocol teaches EEG control using 100-s or 200-s “ON-OFF-ON” exercises.
Temperature and frontal SEMG biofeedback precede alpha-theta training. Patients receive 3-4 weekly sessions of temperature biofeedback followed by 3-4 weekly sessions of frontal SEMG biofeedback. Judy Green has likened the temperature and SEMG biofeedback sessions to settling elementary school students in their seats so they can pay attention without distraction. These sessions also teach patients the strategy of passive volition (allowing), which is critical to alpha-theta training.
The patient then receives 10-12 bi-weekly sessions of alpha-theta biofeedback using ON-OFF-ON exercises. Training attempts to gradually slow the EEG until the patient can increase alpha and theta amplitude without falling asleep.
Egner, Strawson, and Gruzelier (2002) addressed the question of whether the effects of alpha-theta neurofeedback depend on with-session EEG changes or are nonspecific and shared with other relaxation procedures. They compared the effect of contingent and noncontingent alpha-theta neurofeedback on theta/alpha ratios within and across sessions.
The contingent group achieved increased within-session theta/alpha ratios, while the noncontingent group did not. The contingent group also achieved higher theta/alpha ratios than the noncontingent group during some of the training sessions. There were no group differences in subjective reports of activation, since both groups reported significantly lower activation following training. Both contingent and noncontingent neurofeedback were relaxing. This study validated the assumption underlying alpha-theta neurofeedback that accurate feedback results in higher within-session theta/alpha ratios than does noncontingent neurofeedback.
The National Comorbidity Survey estimated that the lifetime prevalence for alcohol dependence exceeded 20% for men and 8% for women (Kessler et al., 1994).
Researchers often observe deficient slow-wave activity (delta, theta, and alpha) and excessive beta activity in alcoholics. Alcohol consumption slows their alpha frequency and increases its amplitude (Peniston & Kulkosky, 1990).
The Peniston-Kulkosky (1989) addiction protocol is a multimodal approach that incorporates both biofeedback and non-biofeedback components. Patients start with visualization training, receive 6 temperature biofeedback sessions, learn rhythmic breathing techniques, participate in autogenic training exercises, learn to construct personalized imagery, and experience guided imagery (where the therapist directs the patient's visualization). This training prepares the patient for 30 alpha-theta sessions in which the patient learns to slow the EEG to increase alpha and theta amplitude using the Menninger alpha-theta training procedure. Following the alpha-theta biofeedback sessions, the supervising physician may need to adjust patient medication.
Experimental patients who received Peniston and Kulkosky’s alpha-theta protocol for alcoholism and control patients were assessed over a 24-month follow-up period. Across this period, 8 of the 10 experimental patients and none of the 10 controls maintained abstinence from alcohol.
Due to the multimodal nature of the Peniston-Kulkosky addiction protocol, we cannot identify the components responsible for clinical improvement. Further clinical research that "dismantles" this protocol will be required to isolate the active treatment components.
Evidence-Based Practice in Biofeedback and Neurofeedback (2004) rates neurofeedback for alcoholism at level 3 efficacy, probably efficacious. The criteria for level 3 efficacy include "Multiple observational studies, clinical studies, wait list controlled studies, and within subject and intrasubject replication studies that demonstrate efficacy" (pp. 6-7).
Peniston and Kulkosky (1990) reported that patients who received alpha-theta neurofeedback achieved significantly greater decreases on Millon Clinical Multiaxial Inventory factors than those who received conventional medical treatment. Alcoholics who received alpha-theta neurofeedback improved on schizoid, avoidant, passive-aggressive, schizotypal, borderline, paranoid, anxiety, somatoform, dysthymic, alcohol abuse, psychotic thinking, psychotic depression, and psychotic delusional factors.
Schneider et al. (1993) reported that 6 of 10 male alcoholics remained abstinent 4 months after completion of slow cortical potential neurofeedback.
Taub and colleagues (1994) randomly assigned 118 chronic alcoholics to one of four treatments: Alcoholics Anonymous and counseling (RTT), RTT combined with Transcendental Meditation, RTT combined with SEMG biofeedback, or RTT plus sham neurotherapy. The sham neurofeedback condition involved "electrocranial stimulation" and not alpha-theta biofeedback. Rates of self-reported abstinence were 25%, 65%, 55%, and 28%, respectively. While the addition of Transcendental Meditation and EMG biofeedback seemed to increase abstinence, sham neurotherapy did not. The addition of Transcendental Meditation or EMG biofeedback to RTT produced abstinence rates comparable to those reported for the addition of alpha-theta biofeedback.
Saxby and Peniston (1995) demonstrated in a controlled study that alpha-theta neurofeedback can reduce depression in alcoholics and increase the rate of abstinence assessed over a 21-month follow-up period.
Kelley’s (1997) three-year follow-up study of 20 Native American alcoholic inpatients reported the following changes: increased EEG synchrony and alpha-theta amplitudes, extinction of drinking behavior, less personally damaging behavior (81%), and lower Beck Depression Inventory scores.
There are about 1.9 million cases of skull fracture or intracranial injury in the United States each year. In 1992, firearms caused the most deaths from traumatic brain injury (Vinas & Pilitsis, 2004).
Ayers (1995) reported treating 32 level two coma patients, who were comatose for more than 2 months, noninvasively with neurofeedback. In a level two coma on the Rancho Los Amigos Cognitive Scale, there is a generalized response where patients move aimlessly and inconsistently. If they open their eyes, patients do not focus on objects.
Twenty-five of 32 patients emerged from their comas after 1-6 treatments. Neurofeedback for coma involved inhibiting 4-7 Hz activity and then reinforcing the replacement of 4-7 Hz with 15-18 Hz activity.
Ayers and colleagues started neurofeedback for open head trauma at the somatosensory cortex. They trained these patients to decrease 4-7 Hz activity and increase 15-18 Hz activity.
About 6.6% of Americans (13-14 million adults) suffer from a depressive disorder each year (Kessler et al., 2003). The lifetime prevalence of major depressive disorder (MDD) is 20% in women and 12% in men. MDD is diagnosed twice as often in women as in men (Aronson, 2005).
If untreated, 25-30% of adult depressive attempt or commit suicide.Most cases of major depression involve another comorbid psychological disorder that is primary (Zimmerman et al., 2002). Only 21% of annual cases of depression are adequately treated (Kessler et al., 2003).
The rationale for alpha asymmetry neurofeedback for mood disorders is that the left frontal cortex mediates approach behavior, while the right mediates negative affect.
Clinical depression is associated with less activation of the left frontal lobe than the right. Since alpha is an "idling frequency," this asymmetry is seen when alpha amplitude is greater in the left (F3) than the right frontal lobe (F4). The goal of alpha asymmetry neurofeedback for depression is to correct this imbalance, decreasing left frontal alpha with respect to right frontal alpha.
Before EEG asymmetry training, patients are trained using diaphragmatic breathing and autogenic phrases to teach them to relax and warm their hands. The hand-warming criterion is 95 degrees F.
Patients are seen once or twice a week for one-hour sessions, which consist of 30 minutes of EEG training followed by 30 minutes of psychotherapy. Scalp sites F3 and F4 are used and are referenced to CZ. A bell or clarinet tone reinforces behavior when the asymmetry score exceeds 0 (right alpha amplitude exceeds left).
The two BioTrace+ /NeXus-10 graphs below show the asymmetry between sensor placements F3 and F4 using two separate EEG channels.
The upper graph represents asymmetry in the 15-18 Hz band and the lower graph represents asymmetry in the 8-11 Hz band. When the tracing rises above zero (positive value), this represents higher amplitude at F3 compared to F4. When the tracing falls below zero (negative value), this represents lower amplitude at F3 compared to F4.
Typically, it is desirable for 15-18 Hz amplitude to be higher and 8-11 Hz amplitude to be lower at F3 compared to F4. Notice that the reverse is true in this example. This movie was generously provided by John S. Anderson.
Evidence-Based Practice in Biofeedback and Neurofeedback (2004) rates neurofeedback for depressive disorder at level 2 efficacy, possibly efficacious. The criteria for level 2 efficacy include "At least one study of sufficient statistical power with well identified outcome measures, but lacking randomized assignment to a control condition internal to the study" (p. 116). A level 2 rating was awarded due to lack of controlled studies.
Baehr et al. (1999) reported that 3 of 6 patients discontinued antidepressant medication before the close of the fourth treatment quarter and that their proportion of A (alpha asymmetry) scores remained stable.
Case studies reported by Kumano et al. (1996) and Rosenfeld (2000), and a pilot study by Waldkoetter and Sanders (1997) support the Baehr et al. (1999) finding that neurofeedback can reduce the symptoms of clinical depression.
Corrado and Gottlieb (1999) compared biofeedback-assisted relaxation with a wait-list control condition in chronic pain patients. The biofeedback-assisted relaxation group achieved improved Beck Depression Inventory scores.
DSM-IV-TR (2000) identifies five main categories of anxiety disorders: Phobia, Panic Disorder, Generalized Anxiety Disorder, Stress Disorders (Posttraumatic Stress Disorder and Acute Stress Disorder), and Obsessive-Compulsive Disorder. Excessive anxiety and worry are core features of Generalized Anxiety Disorder.
Estimated lifetime prevalence rates for anxiety disorders in the United States are panic disorder (2.3-2.7%), generalized anxiety disorder (4.1-6.6%), OCD (2.3-2.6%), PTSD (1-9.3%), and social phobia (2.6-13.3%). The male-to-female ratio for a lifetime anxiety disorder is 3 to 2 (Yates, 2005).
Evidence-Based Practice in Biofeedback and Neurofeedback (2004) rates biofeedback for anxiety at level 4 efficacy, efficacious. The criteria for level 4 efficacy include:"
The majority of controlled, randomized experiments have found that
biofeedback (electrodermal, neurofeedback, SEMG, and temperature)
produces comparable anxiety reductions to relaxation procedures like
meditation and Progressive Relaxation. Biofeedback and relaxation
procedures may achieve equivalent results because anxiety involves
disordered attention and cognition in addition to abnormal physiological
Rice, Blanchard, and Purcell (1993) studied 45 patients with generalized anxiety. Thirty-eight of these patients satisfied the DSM-III criteria for Generalized Anxiety Disorder (GAD) and 7 were subclinical for GAD and only met 2 of these criteria. They randomly assigned patients to one of five conditions: frontal EMG biofeedback, EEG biofeedback to increase alpha, EEG biofeedback to decrease alpha, pseudomeditation, or a wait-list control. For the two EEG biofeedback conditions, the electrodes were placed at OZ, the right mastoid process, and the forehead. All four treatment groups received eight 60-minute sessions and achieved significant reductions on STAI-Trait Anxiety scores and Psychosomatic Symptom Checklist (PSC) scores.
Only the alpha-increase condition decreased heart rate reactivity to stressors. Subjects in the frontal EMG, alpha-increase, and alpha suppression conditions maintained improvement in STAI-Trait Anxiety and PSC scores at 6 weeks posttreatment. The alpha-increase and alpha-suppression groups actually showed further improvement in Psychosomatic Symptom Checklist scores at 6 weeks posttreatment.
Vanathy, Sharma, and Kumar (1998) randomly assigned subjects who met the diagnostic criteria for Generalized Anxiety Disorder (GAD) to a wait-list control, alpha-increase biofeedback, or theta-increase biofeedback. EEG biofeedback consisted of 15 sessions of training to enhance alpha or theta and suppress beta.
Both the alpha-increase and theta-increase groups reduced self-reported (STAI-State Anxiety) and blind observer-rated anxiety (Hamilton Anxiety Rating Scale) in comparison to the control group. These results may have been due to Type 1 error caused by the use of multiple t-tests without statistical correction. The authors' failure to observe changes in EEG power in the alpha or theta bands following EEG training suggests that non-specific treatment components, and not EEG training, may have produced clinical improvement, assuming that the findings of symptom improvement were valid.
Epilepsy is a family of neurological disorders featuring short, periodic attacks of motor, sensory, or cognitive malfunction. Epileptic seizures have been divided into (1) partial or focal seizures, (2) primary generalized seizures, (3) status epilepticus, and (4) recurrence patterns.
Petit mal seizures feature loss of consciousness without abnormal movement (patient appears to be daydreaming). The patient, typically a child, may suffer hundreds of these seizures daily for periods lasting up to 30 seconds.
Tonic-clonic seizures (grand mal seizures) are primary generalized seizures featuring a peculiar cry, loss of consciousness, fall, tonic-clonic convulsions of all extremities, incontinence, and amnesia for the episode. These seizures are diagnosed in fewer than 20% of adult epileptics.
The sensorimotor cortex is a central cortical area defined by the central sulcus (fissure of Rolando) separating the frontal and parietal lobes. Sterman (1977) recorded the EEG over the left sensorimotor cortex from sites 10% and 30% lateral to the vertex (slightly medial to C3 and T3).
The sensorimotor rhythm (SMR) is an EEG rhythm from 12-14 Hz located over the sensorimotor cortex (central sulcus). This rhythm is associated with inhibition of movement and reduced muscle tone.
In the United States, the lifetime probability of experiencing an epileptic seizure is about 9% and of receiving a diagnosis of epilepsy is about 3%. The prevalence of active epilepsy is 0.8%. Seizures result in death in a minority of cases and most result from accidents caused by impaired consciousness (Cavazos & Lum, 2005).
Sterman's protocol trains an epileptic patient to increase SMR (12-14 Hz) amplitude and duration while theta (4-7 Hz), beta (20+ Hz), epileptiform spikes, and EMG artifact are suppressed during 36 sessions. The aim is to normalize the waking and sleep EEG with elevated SMR and suppressed theta and beta activity.
Sterman (2000) summarized 18 peer-reviewed studies in which 174 patients were trained using his SMR protocol. The outcome data were impressive; 82% clinically improved, reducing seizures by more than 30%. The average seizure reduction was greater than 50%. Many studies found decreased seizure severity. Five percent of patients remained seizure free for as long as one year. In those studies where researchers recorded pretreatment and posttreatment EEG amplitudes, 66% normalized their EEG power spectra.
La Vaque (2003) considers slow cortical potential (SCP) training to be highly effective in controlling "drug-resistant" epilepsy.
Kotchoubey, Schneider, et al. (1996) reported that SCP neurofeedback decreased the baseline seizure frequency in drug-resistant epileptics and Kotchoubey, Blankenhorn, et al. (1997) showed that this improvement was maintained 6 months post-treatment.
Kotchoubey, Busch, Strehl, and Birbaumer (1999) concluded that both SMR and SCP protocols improve epilepsy control in about 66% of patients. While the mechanism underlying SCP training remains unclear, it may involve increased 6.0-7.9 Hz theta activity during training trials without feedback.
Joy Andrews, Reiter, et al. (2000) found that a neurofeedback protocol, involving 5 consecutive days of training, enabled 79% of patients to control their seizures.
Kotchoubey, Strehl, et al. (2001) treated patients with refractory epilepsy with an anti-epileptic drug and psychosocial counseling, a breathing training control group, or SCP neurofeedback in a controlled clinical study. Only the drug and SCP groups significantly reduced seizure frequency.
Evidence-Based Practice in Biofeedback and Neurofeedback (2004) rates neurofeedback for epilepsy at level 3 efficacy, probably efficacious. The criteria for level 3 efficacy include "Multiple observational studies, clinical studies, wait list controlled studies, and within subject and intrasubject replication studies that demonstrate efficacy" (pp. 18-19).
Ramaratnam, Baker, and Goldstein (2001), in a Cochrane Database Systematic Review, challenged the efficacy of neurofeedback for epilepsy due to methodological flaws and small sample size.
DSM-IV-TR (2000) identifies three subtypes of ADHD: Attention-Deficit/Hyperactivity Disorder, Combined Type; Attention-Deficit/Hyperactivity Disorder, Predominantly Inattentive Type; and Attention-Deficit/Hyperactivity Disorder, Predominantly Hyperactive-Impulsive Type.
314.00 Attention-Deficit/Hyperactivity Disorder, Predominantly Inattentive Type requires that the following criteria are met and the criteria for the Predominantly Hyperactive-Impulsive Type are not met during this time for the past 6 months.
314.01 Attention-Deficit/Hyperactivity Disorder, Predominantly Hyperactive-ImpulsiveType requires that the following criteria are met and the criteria for the Predominantly Inattentive Type are not met during this time for the past 6 months.
314.01 Attention-Deficit/Hyperactivity Disorder, Combined Type requires that both sets of criteria are met for the past 6 months.
In the United States, estimates of the incidence of ADHD in school-age children range from 3-7%. In children, ADHD is diagnosed 3-5 times more often in boys than in girls. The inattentive subtype of ADHD is more often diagnosed in girls than in boys. About 15-20% of children diagnosed with ADHD retain this diagnosis as adults. In adults, the ratio between men and women is almost even. In adults, the prevalence rate is approximately 2-7% (Chang, 2005).
Monastra, Lynn, Linden, Lubar, Gruzelier, and La Vaque (2005) summarized three main protocols for ADHD treatment that had been evaluated in controlled group studies. The following tables were adapted from the Appendix.
Evidence-Based Practice in Biofeedback and Neurofeedback (2004) rates neurofeedback for ADD and ADHD at level 4 efficacy, efficacious. The criteria for level 4 efficacy include:"
Monastra and colleagues (2005) assigned a more conservative rating of probably efficacious for EEG biofeedback for ADHD in an AAPB White Paper. Despite significant improvement in about 75% of patients in the published studies they examined, the authors concluded that more randomized, controlled group studies that control for therapist and patient characteristics are needed to calculate the percentage of patients diagnosed with ADHD who will achieve these gains in typical clinical settings.
Neurofeedback appears to be superior to no treatment and comparable to
stimulant medication. Patients require at least 20 sessions, and as many
as 50 sessions, to produce clinical improvement. The table below is adapted from Table 2.
Lubar, Swartwood, Swartwood, and O'Donnell (1995) reported that training to reduce slow EEG activity increased WISC-R and Test of Variables of Attention (TOVA) scores. Full-scale WISC-R scores increased about 12 points. The increase in TOVA scores correlated with decreased slow EEG activity.
Lubar (1995) followed 52 patients treated with neurofeedback for as long as 10 years. Their improvement on the Connors scale, used to measure attention, remained stable at follow-up.
Rossiter and La Vaque (1995) matched and randomly assigned 46 subjects to either Ritalin or neurofeedback. Both groups improved on TOVA measures of inattention, impulsivity, information processing, and response variability.
Linden, Habib, and Radojevic's (1996) controlled study of 18 children demonstrated that neurofeedback to increase beta and suppress theta activity increased intelligence scores and reduced inattention rated by their parents, when compared to a wait-list control group.
Thompson and Thompson (1998) reported the successful treatment of 98 children and 13 adults over 40 50-minute sessions using Lubar's ADHD protocol. The percentage of children using Ritalin declined from 30% at the start of the study to 6% posttreatment. Theta/beta ratios significantly declined for children, but not for adults. Study participants achieved impressive pretreatment to posttreatment gains on intelligence, TOVA, and Wide Range Achievement Test scores.
Case studies by Ramos (1998) and Wadhwani, Radvanski and Carmody (1998) support the efficacy of neurofeedback for ADD and ADHD.
Camp (1999) reported that theta suppression biofeedback training compared favorably with cognitive behavior modification, based on pretreatment to posttreatment changes in 48 children on TOVA, parent and teacher ratings, and ADHD scales.
The Kaiser and Othmer (2000) multi-center study involved 1,089 patients ranging from 5-67 years and demonstrated that SMR-beta neurofeedback training produced significant gains on TOVA measures of attentiveness, impulse control, and response variability.
Carmody and colleagues (2001) randomly assigned 16 children (ages 8-10) to either EEG biofeedback or a wait-list control condition. Eight of the 16 children were diagnosed with ADHD and 8 had received no diagnosis of any disorder. In the EEG biofeedback condition, participants received 3-4 weekly sessions of EEG biofeedback (using a synthesis of Protocols 1 and 3) for 6 months and completed 36-48 sessions. The children diagnosed with ADHD who received EEG biofeedback decreased impulsivity as measured by the T.O.V.A. and their teachers' ratings of attentiveness on the School Version of the ADDES improved. Selected QEEG measures did not consistently validate improvement by participants in the EEG biofeedback condition.
Monastra, Monastra, and George (2002) compared 49 children diagnosed with ADHD who participated in 1-year multimodal program (Ritalin, parent counseling, and academic consultation) with 51 children who participated in the multimodal program combined with neurofeedback (weekly 30 to 40-min sessions using the Lubar protocol with a cash reward for increased frontal cortical arousal). Both groups significantly improved performance on TOVA and the Attention Deficit Disorders Evaluation Scale when medicated with Ritalin, but only the group that received neurofeedback maintained performance gains when unmedicated. A QEEG scan only showed reduced cortical slowing in children who received neurofeedback. Parenting style moderated behavioral symptoms at home, but not in the classroom.
Fuchs, Birbaumer, Lutzenberger, Gruzelier, and Kaiser (2003) compared the efficacy of 3 months of sensorimotor rhythm (12-15 Hz) and beta1 (15-18 Hz) neurofeedback against methylphenidate in 46 ADHD children. The children were assigned to the neurofeedback (22) and medication (12) based on their parents' preference (assignment was nonrandom). Both treatment groups improved on all TOVA subscales, and on speed and accuracy on the d2 Attention Endurance Test. Teacher and parent ratings of ADHD behaviors on the IOWA-Conners Behavior Rating Scale also improved for both groups.
Below is a BioTrace+ / NeXus-10 ADHD neurofeedback training screen that is used to teach children to decrease theta activity and increase SMR and beta activity.
Now that you have completed this module, describe your personal training experience with EEG biofeedback. Which training approach (e.g., amplitude control or frequency control) did you use? Which placement did you use? Which EEG biofeedback application interests you the most? Why?
American Psychiatric Association (2000). Diagnostic and statistical manual of mental disorders (4th ed., DSM-IV-TR). Washington, DC: Author.
Andreassi, J. L. (2000). Psychophysiology: Human behavior and physiological
response. Hillsdale, NJ: Lawrence Erlbaum and Associates, Inc.
Aronson, S. C. (2005). Depression. eMedicine.
Ayers, M. E. (1995). EEG neurofeedback to bring individuals out of level 2 coma [Abstract]. Biofeedback and Self-Regulation, 20(3), 304-305.
Ayers, M. E. (1995). Long-term follow-up of EEG neurofeedback with absence seizures. Biofeedback & Self-Regulation, 20(3), 309-310.
Baehr, E., Miller, E., Rosenfeld, J. P., & Baehr, R. (2004). Changes in frontal brain asymmetry associated with premenstrual dysphoric disorder: A single case study. Journal of Neurotherapy, 8(1), 29-42.
Baehr, E., Rosenfeld, J. P., & Baehr, R. (1997). The clinical use of an alpha asymmetry protocol in the neurofeedback treatment of depression: Two case studies. Journal of Neurotherapy, 2(3), 10-23.
Baehr, E., Rosenfeld, J. P., & Baehr, R. (2001). Clinical use of an alpha asymmetry neurofeedback protocol in the treatment of mood disorders: Follow-up study one to five years post therapy. Journal of Neurotherapy, 4(4), 11-18.
Camp, B. W. (1999). Attention deficit hyperactivity disorders: Studies of EEG patterns and biofeedback training (Final Report, Grant No. H113G40130), Washington, DC: U.S. Office of Education.
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, 4(3), 5-27.
Cavazos, J. E., & Lum, F. (2005). Seizures and epilepsy: Overview and classification. eMedicine.
Chang, K. D. (2005). Attention Deficit Hyperactivity Disorder. eMedicine.
Corrado, P., & Gottlieb, H. (1999). The effect of biofeedback and relaxation training on depression in chronic pain patients. American Journal of Alternative Medicine, 9, 18-21.
Egner, T., Strawson, E., & Gruzelier, J. H. (2002). EEG signature and phenomenology of alpha/theta neurofeedback training versus mock feedback. Applied Psychophysiology and Biofeedback, 27(4), 261-270.
Evans, J. R., & Abarbanel, A. (1999). Introduction to quantitative EEG and neurofeedback. San Diego: Academic Press.
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).
Hammond, D. C. (2001). Neurofeedback treatment of depression with the Roshi. Journal of Neurotherapy, 4(2), 45-56.
Hammond, D. C. (2001). Neurofeedback training for anger control. Journal of Neurotherapy, 5(4), 98-103.
Hammond, D. C. (2005). Neurofeedback with anxiety and affective disorders. Child & Adolescent Psychiatric Clinics of North America, 14(1), 105-123.
Joy Andrews, D., Reiter, J. M., Schonfeld, W., Kastl, A., & Denning, P. (2000). A neurobehavioral treatment for unilateral complex partial seizure disorders: A comparison of right- and left-hemisphere patients. Seizure, 9(3), 189-197.
Kaiser, D. A., & Othmer, S. (2000). Effect of neurofeedback on variables of attention in a large multi-center trial. Journal of Neurotherapy, 4(1), 5-15.
Kelley, M. J. (1997). Native Americans, neurofeedback, and substance abuse theory. Three year outcome of alpha/theta neurofeedback training in the treatment of problem drinking among Dine’ (Navajo) people. Journal of Neurotherapy, 2, 24–60.
Kessler, R. C., McGonagle, K. A., Zhao, S., Nelson, C. B., Hughes, M., Eshleman, S., Wittchen, H. U., & Kendler, K. S. (1994). Lifetime and 12-month prevalence of DSM-III-R psychiatric disorders in the United States. Results from the National Comorbidity Survey. Archives of General Psychiatry, 51(1), 8-19.
Kessler, R. C., et al. (2003). The epidemiology of major depressive disorder: Results from the National Comorbidity Survey Replication (NCS-R). JAMA, 289, 3095-3105.
Kotchoubey, B., Blankenhorn, V., Froscher, W., Strehl, U., & Birbaumer, N. (1997). Stability of cortical self-regulation in epilepsy patients. Neuroreport, 27(8), 1867-1870.
Kotchoubey, B., Blankenhorn, V., Froscher, W., Strehl, U., Uhlmann, C., Blankenhorn, V., et al. (1996).Self-regulation of slow cortical potentials in epilepsy: A retrial with analysis of influencing factors. Epilepsy Research, 25(3), 269-276.
Kotchoubey, B., Busch, S., Strehl, U., & Birbaumer, N. (1999). Changes in EEG power spectra during biofeedback of slow cortical potentials in epilepsy. Applied Psychophysiology and Biofeedback, 24(4), 213-233.
Kotchoubey, B., Schneider, D., Schleichert, H., Strehl, U., Uhlmann, C., Blankenhorn, V., et al. (1996). Stability of cortical self-regulation in epilepsy patients. Neuroreport, 27(8), 1867-1870.
Kotchoubey, B., Strehl, U., Holzapfel, S., Blankenhorn, V., Froscher, W., & Birbaumer, N. (1999). Negative potential shifts and the prediction of the outcome of neurofeedback therapy in epilepsy. Clinical Neurophysiology, 110(4), 683-686.
Kotchoubey, B., Strehl, U., Uhlmann, C., Holzapfel, S., Konig, M., Froscher, W., et al. (2001). Modification of slow cortical potentials in patients with refractory epilepsy: A controlled outcome study. Epilepsia, 42(3), 406-416.
Kumano, H., Horie, H., Shidara, T., Kuboki, T., Suematsu, H., & Yasushi, M. (1996). Treatment of a depressive disorder patient with EEG-driven photic stimulation. Biofeedback and Self-Regulation, 21(4), 323-334.
La Vaque, T. J. (2003). Neurofeedback, neurotherapy, and quantitative EEG. In D. Moss, A. McGrady, T. Davies, and I. Wickramasekera (Eds.), Handbook of mind-body medicine for primary care. Thousand Oaks, CA: Sage Publications, Inc.
Lubar, J. F. (1985). EEG biofeedback and learning disabilities. Theory into Practice, 26, 106-111
Lubar, J. F. (1995). Neurofeedback for the management of
attention-deficit/hyperactivity disorder. In M. S. Schwartz & Associates
(Eds.), Biofeedback: A practitioner's guide (2nd ed.). New
Lubar, J. F. (2003). Neurofeedback for the management of attention‑deficit / hyperactivity disorders. In M. S. Schwartz, & F. Andrasik (Eds.), Biofeedback: A practitioner's guide (3rd ed.). New York: Guilford.
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., Swartwood, M. O., Swartwood, J. N., & O'Donnell, P. (1995). Evaluation of the effectiveness of EEG neurofeedback training for ADHD in a clinical setting as measured by changes in TOVA scores, behavioral ratings, and WISC-R performance. Biofeedback and Self-Regulation, 20, 83-99.
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, 30-36.
Monastra, V. J., Lynn, S., Linden, M., Lubar, J. F., Gruzelier, J., &
LaVaque, T. J. (2005). Electroencephalographic biofeedback in the
treatment of Attention Deficit/Hyperactivity Disorder. Applied
Psychophysiology and Biofeedback, 30(2), 95-114.
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.
Peniston, E. G., & Kulkosky, P. J. (1989). Alpha-theta brainwave training and beta-endorphin levels in alcoholics. Alcoholism, Clinical and Experimental Research,13(2), 271-279.
Peniston, E. G., & Kulkosky, P. J. (1990). Alcoholic personality and alpha-theta brainwave training. Medical Psychotherapy, 3, 37-55.
Peniston, E. G., Marrinan, D. A., Deming, W. A., & Kulkosky, P. J. (1993). EEG alpha-theta brainwave synchronization in Vietnam theater veterans with combat-related post-traumatic stress disorder and alcohol abuse. Advances in Medical Psychotherapy, 6, 37-50.
Ramaratnam, S., Baker, G. A., & Goldstein, L. (2001). Psychological treatments for epilepsy. Cochrane Database of Systematic Reviews Online Update Software, 4, CD002029.
Ramos, F. (1998). Frequency band interaction in ADD/ADHD neurotherapy. Journal of Neurotherapy, 3(1), 26-41.
Rice, K. M., Blanchard, E. B., & Purcell, M. (1993). Biofeedback treatments of generalized anxiety disorder: Preliminary results. Biofeedback and Self-Regulation, 18(2), 93-105.
Rosenfeld, J. P. (2000). An EEG Biofeedback protocol for affective disorders. Clinical Electroencephalography, 31(1), 7-12.
Rosenfeld, J. P., Baehr, E., Baehr, R., Gotlib, I. H., & Ranganath, C. (1996). Preliminary evidence that daily changes in frontal alpha asymmetry correlate with changes in affect in therapy sessions. International Journal of Psychophysiology, 23, 137-141.
Rossiter, T. R. (1998). Patient-directed neurofeedback for AD/HD. Journal of Neurotherapy, 2(4), 54-63.
Rossiter, T. R., & La Vaque, T. J. (1995). A comparison of EEG biofeedback and psychostimulants in treating attention deficit/hyperactivity disorders. Journal of Neurotherapy, 1(1), 48-59.
Saxby, E., & Peniston, E. G. (1995). Alpha-theta brainwave neurofeedback training: An effective treatment for male and female alcoholics with depressive symptoms. Journal of Clinical Psychology, 51(5), 685-693.
Schneider, F., Elbert, T., Heimann, H., Welker, A., Stetter, F., Mattes, R., et al. (1993). Self-regulation of slow cortical potentials in psychiatric patients: Alcohol dependency. Biofeedback and Self-Regulation, 18(1), 23-32.
Sterman, M. B. (1973a). Neurophysiological and clinical studies of sensorimotor EEG biofeedback training: Some effects on epilepsy. Seminars in Psychiatry, 5(4), 507-525.
Sterman, M. B. (1973b). Neurophysiological and clinical studies of sensorimotor EEG biofeedback training: Some effects on epilepsy. L. Birk (Ed.), Biofeedback: Behavioral Medicine. New York: Grune & Stratton, pp. 147-165.
Sterman, M. B. (1977). Sensorimotor EEG operant conditioning: Experimental and clinical effects. Pavlovian Journal of Biological Sciences, 12(2), 63-92.
Sterman, M. B. (1986). Epilepsy and its treatment with EEG feedback therapy. Annals of Behavioral Medicine, 8, 21-25.
Sterman, M. B. (1997).The challenge of EEG biofeedback in the treatment of epilepsy: A view from the trenches. Biofeedback, 25(1), 6-7, 20-21, 23.
Sterman, M. B. (2000). Basic concepts and clinical findings in the treatment of seizure disorders with EEG operant conditioning. Clinical Electroencephalography, 31(1), 45-55.
Sterman, M. B., & Friar, L. (1972). Suppression of seizures in epileptics following sensorimotor EEG feedback training. Electroencephalography & Clinical Neurophysiology, 33, 89-95.
Sterman, M. B., & Lantz, D. (2001). Changes in lateralized memory performance in subjects with epilepsy following neurofeedback training. Journal of Neurotherapy, 5, 63-72.
Sterman, M. B., & Macdonald, L. R. (1978). Effects of central cortical EEG feedback training on incidence of poorly controlled seizures. Epilepsia, 19(3), 207-222.
Sterman, M. B., Macdonald, L. R., & Stone, R. K. (1974). Biofeedback training of the sensorimotor electroencephalogram rhythm in man: Effects on epilepsy. Epilepsia, 15(3), 395-416.
Sterman, M. B., & Shouse, M. N. (1980). Quantitative analysis of training, sleep EEG and clinical response to EEG operant conditioning in epileptics. Electroencephalography & Clinical Neurophysiology, 49, 558-576.
Taub, E., Steiner, S. S., Weingarten, E., & Walton, K. G. (1994). Effectiveness of broad spectrum approaches to relapse prevention in severe alcoholism: A long-term, randomized, controlled trial of Transcendental Meditation, EMG biofeedback and electronic neurotherapy. Alcoholism Treatment Quarterly, 11(1-2), 187-220.
Thompson, L., & Thompson, M. (1998). Neurofeedback combined with training in metacognitive strategies: Effectiveness in students with ADD. Applied Psychophysiology and Biofeedback, 23(4), 243-263.
Thompson, M., & Thompson, L. (2003). The biofeedback book: An introduction to basic concepts in applied psychophysiology. Wheat Ridge, CO: Association for Applied Psychophysiology and Biofeedback.
Vanathy, S., Sharma, P. S. V. N., & Kumar, K. B. (1998). The efficacy of alpha and theta neurofeedback training in treatment of generalized anxiety disorder. Indian Journal of Clinical Psychology, 25(2), 136-143.
Vinas, F. C., & Pilitsis, J. (2004). Penetrating head trauma. eMedicine.
Wadhwani, S., Radvanski, D. C., & Carmody, D. P. (1998). Neurofeedback training in a case of attention deficit hyperactivity disorder. Journal of Neurotherapy, 3(1), 42-49.
Waldkoetter, R. O., & Sanders, G. O. (1997). Auditory brainwave stimulation in treating alcoholic depression. Perceptual and Motor Skills, 84(1), 226.
Yates, W. R. (2005). Anxiety disorders. eMedicine.
Yucha, C. B., & Gilbert, C. D. (2004). Evidence-based practice in biofeedback and neurofeedback. Wheat Ridge: AAPB.
Zimmerman, M., et al. (2002). Major depressive disorder and Axis I diagnostic comorbidity. Journal of Clinical Psychiatry, 63, 187-193.