Behavioral and electroencephalographic correlates of 40-Hz EEG biofeedback training in humans

Two groups of eight adults successfully trained with biofeedback for increases in 40-Hz EEG responses in left or right hemispheres also demonstrated significant 40-Hz EEG increases during baseline periods, and increases in the contralateral hemisphere during training periods. No changes in heart rate, 40-Hz EMG, or 21- to 31-Hz beta, alpha, or theta EEG occurred over training days. Three subjects returning for additional training demonstrated suppression of 40-Hz EEG. A group of four subjects experiencing daily bidirectional training produced substantial within-session control of 40-Hz EEG but no changes over days. Data from posttraining tests without feedback for successful subjects in both groups indicated significant control of 40-Hz EEG responses in the initial parts of these sessions, and some correlated changes in other EEG responses. Measures of successful subjects' experiences during training and control tests indicated awareness of changes in subjective concomitants of EEG responses. This study suggests further strategies for research on behavioral correlates of EEG activity.     

Biofeedback in psychomotor training. Electrophysiological bases

Comparison of influence of usual musical practice and the same trainings but using biofeedback on electrophysiological and psychological markers of optimal psychomotor functioning in 39 students-musicians revealed that the obvious musical practice caused psychomotor pressure in most students (with initially low individual alpha peak frequency), whereas similar practice combined with an individualized session of alpha-EEG/EMG biofeedback was accompanied by increase of alpha-activity in all examinees and a decrease (reduction) of integrated EMG that indicated reaching of optimal psychomotor functioning. It appears that the psychomotor learning ability depends on the baseline individual alpha-activity. Individual alpha peak frequency was associated with fluency and efficiency of psychomotor performance, individual alpha band width--with plasticity and creativity, individual amount of alpha suppression in response to opening eyes--with the level of selfactualization. These alpha activity EEG indices correlated with efficiency of the biofeedback training.     

Biofeedback heart rate training during exercise

Eighteen healthy human subjects participated in weekly sessions of five 10-minute trials of walking on a treadmill at 2.5 mph and 6% grade. Eight experimental subjects received beat-to-beat heart rate biofeedback during the exercise and were instructed to try to lower their heart rates; ten control subjects did not receive feedback. By the end of 5 weeks (25 trials), the experimental group showed a significantly lower mean heart rate (96.8 vs. 108.6 bpm), systolic blood pressure (114.0 vs. 131.3 mmHg), and rate-pressure product (11.0×10³ vs. 14.3×10³ bpm-mmHg) during exercise than the control group. These differences were maintained after crossover of the feedback provision for five more weeks.     

Biofeedback training and human functional state control

Biofeedback (BFB) training paradigm has outstanding place among various approaches to non-phrarmacological human functional state correction. Being an universal way for voluntary self-regulation of physiological functions, it is characterized by efficacy, accessibility and absence of side effects. However, the lack of fundamental knowledge about the BFB mechanisms leads to existence of numerous difficulties and problems that seriously limit the BFB possibilities. Most difficulties seem to concern the problem of adequate choice of BFB type or parameter being voluntary controlled via feedback signals. Some ways to solve this problem are drown on the base of general systems theory. It is shown that BFB procedures could be especially effective in conditions of close interaction between the BFB mechanisms and the central regulatory mechanisms. Such interaction could be reacheb by utilization of certain characteristics of brain electrical activity reflected in the electroencephalogram (EEG). The most perspective seems to be the utilization of discrete narrow band EEG spectral components, individual resonance EEG oscillators or some correlates of human EEG amplitude modulation processes.     

Steps Toward Developing an EEG Biofeedback Treatment for Chronic Pain

Chronic pain, usually refractory to analgesics, is a significant problem for many individuals with spinal cord injury (SCI). Preliminary studies suggest that electroencephalography (EEG) biofeedback (also known as neurofeedback, NF) has the potential to help patients with otherwise refractory chronic pain. However, there remain many unanswered questions about the effects and mechanisms of this treatment. We studied 13 individuals with SCI and chronic pain with NF. Ten of the 13 individuals completed 4 sessions each of three different neurofeedback protocols assigned in random order for a total of 12 NF sessions. All three protocols had similar immediate effects on pain intensity. In addition, the participants reported modest pre- to post-treatment decreases in worst pain and pain unpleasantness following completion of the 12 NF sessions. These improvements were maintained at 3-month follow-up. The majority of the participants felt they benefited from and were satisfied with the treatment. No significant effects on measures of other outcome domains (sleep quality, pain interference and fatigue) were observed, although there was a non-significant trend for an increase in fatigue. Finally, pre- to post-treatment changes in EEG bandwidth activity, consistent with the training protocols, were observed in θ and α but not β frequencies. The findings provide preliminary support for the potential efficacy of NF for the treatment of SCI-related pain, and suggest that further clinical studies are warranted.     

Regarding the Database for the Peniston Alpha-Theta EEG Biofeedback Protocol

Five papers by Peniston and colleagues, which constitute the basic literature for alpha-theta EEG biofeedback treatment for alcoholism and posttraumatic stress disorder, are reviewed. As a result, we raise three questions: (a) Are the samples studied independent? (b) What was the clinical status of the participants prior to treatment? (c) What treatment did the participants actually receive? In seeking answers to these questions we aim to strengthen the database for neurofeedback with specific procedural information so that claims of efficacy can be tested and accepted or rejected on an objective basis.     

Changes in EEG Power Spectra During Biofeedback of Slow Cortical Potentials in Epilepsy

The goal of the study was to explore parallel changes in EEG spectral frequencies during biofeedback of slow cortical potentials (SCPs) in epilepsy patients. Thirty-four patients with intractable focal epilepsy participated in 35 sessions of SCP self-regulation training. The spectral analysis was carried out for the EEG recorded at the same electrode site (Cz) that was used for SCP feedback. The most prominent effect was the increase in the 2 power (6.0–7.9 Hz) and the relative power decrement in all other frequency bands (particularly 1, 2, and 2) in transfer trials (i.e., where patients controlled their SCPs without continuous feedback) compared with feedback trials. In the second half of the training course (i.e., sessions 21–35) larger power values in the , , and bands were found when patients were required to produce positive versus negative SCP shifts. Both across-subject and across-session (within-subject) correlations between spectral EEG parameters, on the one hand, and SCP data, on the other hand, were low and inconsistent, contrary to high and stable correlations between different spectral variables. This fact, as well as the lack of considerable task-dependent effects during the first part of training, indicates that learned SCP shifts did not directly lead to the specific dynamics of the EEG power spectra. Rather, these dynamics were related to nonspecific changes in patients' brain state.     

Spatial synchronization of the segmental EEG in humans

Topographic features of spatial synchronization of sharp changes, or rapid transition processes (RTP), were studied in human EEG recorded from longitudinal and transversal electrode arrays. A new algorithm, the EEG Threshold Scanning, was proposed for the detection of the RTP. Synchronization of the RTP was estimated by Operational Synchrony Index (OSI) based on the difference between the actual and stochastic frequency of RTP coincidence in a pair of EEG channels. The relationship between the OSI and interelectrode distance was not monotonous. The OSI depended also on the extent of morpho-functional similarity between two cortical areas. Similar results were obtained for crosscorrelation calculated for the same pairs of the EEG derivations. The existence of dynamic spatial modules which incorporate different brain areas by complementary stabilization of their functional states is discussed.     

Biofeedback training in frontalis muscle relaxation and enhancement of belief in personal control

The hypothesis that biofeedback training in frontalis muscle relaxation increases beliefs in internal (personal) locus of control was tested. Subjects were divided into two groups (internals and externals) based on Mirels' (1970) factor analyzedpersonal control subscale of Rotter's (1966) I-E Scale. Internal and external subjects were assigned randomly to one of three conditions: biofeedback (BF), false feedback (FF), or no feedback (NF). All subjects were measured on frontalis electromyographic (EMG) activity. Training consisted of three sessions spaced 1 week apart. Each session was comprised of a 5-minute baseline (nonfeedback) trial followed by a 20-minute experimental session. After each experimental session, subjects completed a questionnaire which assessed the extent to which they attributed their EMG performance to personal and environmental sources. After three sessions, subjects were posttested on the I-E Scale. Results indicated that subjects receiving BF reduced their EMG activity more than did subjects in either the FF or NF conditions, and this effect was maintained across all three sessions. Subjects who received BF shifted toward internal personal locus of control from pre- to posttesting, whereas no such change was found for either FF or NF subjects. Also, the relationship between BF training and change in personal locus of control was mediated by subjects attributing their EMG reduction more to personal effort than to properties of the task. Results are discussed in terms of the importance of contingent feedback as a determinant of cognitions of control.     

Analysis of the segmental structure of EEG alpha-activity in humans

Phasic organisation of human EEG alpha activity was studied in a pilot investigation using a previously suggested EEG segmental analysis methodology. The EEG was recorded in three normal subjects under resting conditions. The segmentation procedure enabled effective identifying of the periods with different amplitude in alpha band and the short-term transitions between them. Mean intersegmental variability of amplitude envelope were computed for the eyes closed and eyes open EEG in each of 16 standard derivations. Analysis of segment amplitude distributions showed that the difference between the average alpha activity amplitude in these conditions were determined mainly by variations in the number of segments of different amplitude classes and not by a shift of the distribution or by change of its width. Distribution and quartile analysis of mean segment amplitudes provide evidence for possible functional heterogeneity of upper and middle subranges of the amplitude range.     

Decoding sequence learning from single-trial intracranial EEG in humans

We propose and validate a multivariate classification algorithm for characterizing changes in human intracranial electroencephalographic data (iEEG) after learning motor sequences. The algorithm is based on a Hidden Markov Model (HMM) that captures spatio-temporal properties of the iEEG at the level of single trials. Continuous intracranial iEEG was acquired during two sessions (one before and one after a night of sleep) in two patients with depth electrodes implanted in several brain areas. They performed a visuomotor sequence (serial reaction time task, SRTT) using the fingers of their non-dominant hand. Our results show that the decoding algorithm correctly classified single iEEG trials from the trained sequence as belonging to either the initial training phase (day 1, before sleep) or a later consolidated phase (day 2, after sleep), whereas it failed to do so for trials belonging to a control condition (pseudo-random sequence). Accurate single-trial classification was achieved by taking advantage of the distributed pattern of neural activity. However, across all the contacts the hippocampus contributed most significantly to the classification accuracy for both patients, and one fronto-striatal contact for one patient. Together, these human intracranial findings demonstrate that a multivariate decoding approach can detect learning-related changes at the level of single-trial iEEG. Because it allows an unbiased identification of brain sites contributing to a behavioral effect (or experimental condition) at the level of single subject, this approach could be usefully applied to assess the neural correlates of other complex cognitive functions in patients implanted with multiple electrodes.     

EEG Biofeedback Treatment Improves Certain Attention and Somatic Symptoms in Fibromyalgia: A Pilot Study

Fibromyalgia (FMS) is a chronic, painful disorder often associated with measurable deficiencies in attention. Since EEG biofeedback (EEG-BF) has been used successfully to treat attention problems, we reasoned that this modality might be helpful in the treatment of attention problems in FMS. We also speculated that improvement in central nervous system (CNS) function might be accompanied by improvement in FMS somatic symptoms. We studied fifteen FMS patients with attention problems, demonstrated by visual and auditory continuous performance testing (CPT), while completing 40 or more EEG-BF sessions. Training consisted of a “SMR protocol” that augmented 12–15 Hz brainwaves (sensory motor rhythm; SMR), while simultaneously inhibiting 4–7 Hz brainwaves (theta) and 22–30 Hz brainwaves (high beta). Serial measurements of pain, fatigue, psychological distress, morning stiffness, and tenderness were also obtained. Sixty-three FMS patients who received standard medical care, but who did not receive EEG-BF, served as controls. Visual, but not auditory, attention improved significantly (P < 0.008). EEG-BF treated subjects also showed improvement in tenderness, pain and fatigue. Somatic symptoms did not change significantly in controls. Visual attention parameters and certain somatic features of FMS appear to improve with an EEG-BF SMR protocol. EEG-BF training in FMS deserves further study.     

The Relative Efficacy of Connectivity Guided and Symptom Based EEG Biofeedback for Autistic Disorders

Autism is a neurodevelopmental disorder characterized by deficits in communication, social interaction, and a limited range of interests with repetitive stereotypical behavior. Various abnormalities have been documented in the brains of individuals with autism, both anatomically and functionally. The connectivity theory of autism is a recently developed theory of the neurobiological cause of autisic symptoms. Different patterns of hyper- and hypo-connectivity have been identified with the use of quantitative electroencephalogray (QEEG), which may be amenable to neurofeedback. In this study, we compared the results of two published controlled studies examining the efficacy of neurofeedback in the treatment of autism. Specifically, we examined whether a symptom based approach or an assessment/connectivity guided based approach was more effective. Although both methods demonstrated significant improvement in symptoms of autism, connectivity guided neurofeedback demonstrated greater reduction on various subscales of the Autism Treatment Evaluation Checklist (ATEC). Furthermore, when individuals were matched for severity of symptoms, the amount of change per session was significantly higher in the Coben and Padolsky (J Neurother 11:5–23, 2007) study for all five measures of the ATEC. Our findings suggest that an approach guided by QEEG based connectivity assessment may be more efficacious in the treatment of autism. This permits the targeting and amelioration of abnormal connectivity patterns in the brains of people who are autistic.     

Effects of training history on resurgence in humans

This experiment assessed the effects of training history on resurgence in three college students. Four-choice arbitrary-matching-to-sample trials occurred in two components of a multiple schedule. An A1 or A2 sample stimulus and four (B) comparison stimuli occurred on AB trials, and a C1 or C2 sample stimulus and four (D) comparison stimuli occurred on CD trials. By the end of training, accuracy and latency measures were comparable across separate discriminations, selecting B2 in the presence of A2 and selecting D2 in the presence of C2, despite a lengthier training correlated with the former discrimination. Next, in the presence of A2 and C2, respectively, responses to B2 and D2 were extinguished and responses to B3 and D3 were reinforced. These responses to B3 and D3 then were extinguished in a final condition. In this final condition, resurgence to B2 occurred for each participant, whereas resurgence to D2 occurred for only one participant. Thus, there was greater resurgence of the discrimination with the lengthier training history, despite the discriminations being similar in terms of accuracy and latency before extinction. This result, therefore, can be classified as a latent, or remote, behavioral history effect.