No Effects of Successful Bidirectional SMR Feedback Training on Objective and Subjective Sleep in Healthy Subjects

There is a growing interest in the application of psychophysiological signals in more applied settings. Unidirectional sensory motor rhythm-training (SMR) has demonstrated consistent effects on sleep. In this study the main aim was to analyze to what extent participants could gain voluntary control over sleep-related parameters and secondarily to assess possible influences of this training on sleep metrics. Bidirectional training of SMR as well as heart rate variability (HRV) was used to assess the feasibility of training these parameters as possible brain computer interfaces (BCI) signals, and assess effects normally associated with unidirectional SMR training such as the influence on objective and subjective sleep parameters. Participants (n?=?26) received between 11 and 21 training sessions during 7 weeks in which they received feedback on their personalized threshold for either SMR or HRV activity, for both up- and down regulation. During a pre- and post-test a sleep log was kept and participants used a wrist actigraph. Participants were asked to take an afternoon nap on the first day at the testing facility. During napping, sleep spindles were assessed as well as self-reported sleep measures of the nap. Although the training demonstrated successful learning to increase and decrease SMR and HRV activity, no effects were found of bidirectional training on sleep spindles, actigraphy, sleep diaries, and self-reported sleep quality. As such it is concluded that bidirectional SMR and HRV training can be safely used as a BCI and participants were able to improve their control over physiological signals with bidirectional training, whereas the application of bidirectional SMR and HRV training did not lead to significant changes of sleep quality in this healthy population.     

Proprioceptive Feedback and Brain Computer Interface (BCI) Based Neuroprostheses

Brain computer interface (BCI) technology has been proposed for motor neurorehabilitation, motor replacement and assistive technologies. It is an open question whether proprioceptive feedback affects the regulation of brain oscillations and therefore BCI control. We developed a BCI coupled on-line with a robotic hand exoskeleton for flexing and extending the fingers. 24 healthy participants performed five different tasks of closing and opening the hand: (1) motor imagery of the hand movement without any overt movement and without feedback, (2) motor imagery with movement as online feedback (participants see and feel their hand, with the exoskeleton moving according to their brain signals, (3) passive (the orthosis passively opens and closes the hand without imagery) and (4) active (overt) movement of the hand and rest. Performance was defined as the difference in power of the sensorimotor rhythm during motor task and rest and calculated offline for different tasks. Participants were divided in three groups depending on the feedback receiving during task 2 (the other tasks were the same for all participants). Group 1 (n = 9) received contingent positive feedback (participants'' sensorimotor rhythm (SMR) desynchronization was directly linked to hand orthosis movements), group 2 (n = 8) contingent “negative” feedback (participants'' sensorimotor rhythm synchronization was directly linked to hand orthosis movements) and group 3 (n = 7) sham feedback (no link between brain oscillations and orthosis movements). We observed that proprioceptive feedback (feeling and seeing hand movements) improved BCI performance significantly. Furthermore, in the contingent positive group only a significant motor learning effect was observed enhancing SMR desynchronization during motor imagery without feedback in time. Furthermore, we observed a significantly stronger SMR desynchronization in the contingent positive group compared to the other groups during active and passive movements. To summarize, we demonstrated that the use of contingent positive proprioceptive feedback BCI enhanced SMR desynchronization during motor tasks.     

The Efficiency of the Brain-Computer Interfaces Based on Motor Imagery with Tactile and Visual Feedback

In this study we compared tactile and visual feedbacks for the motor imagery-based brain–computer interface (BCI) in five healthy subjects. A vertical green bar from the center of the fixing cross to the edge of the screen was used as visual feedback. Vibration motors that were placed on the forearms of the right and the left hands and on the back of the subject’s neck were used as tactile feedback. A vibration signal was used to confirm the correct classification of the EEG patterns of the motor imagery of right and left hand movements and the rest task. The accuracy of recognition in the classification of the three states (right hand movement, left hand movement, and rest) in the BCI without feedback exceeded the random level (33% for the three states) for all the subjects and was rather high (67.8% ± 13.4% (mean ± standard deviation)). Including the visual and tactile feedback in the BCI did not significantly change the mean accuracy of recognition of mental states for all the subjects (70.5% ± 14.8% for the visual feedback and 65.9% ± 12.4% for the tactile feedback). The analysis of the dynamics of the movement imagery skill in BCI users with the tactile and visual feedback showed no significant differences between these types of feedback. Thus, it has been found that the tactile feedback can be used in the motor imagery-based BCI instead of the commonly used visual feedback, which greatly expands the possibilities of the practical application of the BCI.     

A Co-Adaptive Brain-Computer Interface for End Users with Severe Motor Impairment

Co-adaptive training paradigms for event-related desynchronization (ERD) based brain-computer interfaces (BCI) have proven effective for healthy users. As of yet, it is not clear whether co-adaptive training paradigms can also benefit users with severe motor impairment. The primary goal of our paper was to evaluate a novel cue-guided, co-adaptive BCI training paradigm with severely impaired volunteers. The co-adaptive BCI supports a non-control state, which is an important step toward intuitive, self-paced control. A secondary aim was to have the same participants operate a specifically designed self-paced BCI training paradigm based on the auto-calibrated classifier. The co-adaptive BCI analyzed the electroencephalogram from three bipolar derivations (C3, Cz, and C4) online, while the 22 end users alternately performed right hand movement imagery (MI), left hand MI and relax with eyes open (non-control state). After less than five minutes, the BCI auto-calibrated and proceeded to provide visual feedback for the MI task that could be classified better against the non-control state. The BCI continued to regularly recalibrate. In every calibration step, the system performed trial-based outlier rejection and trained a linear discriminant analysis classifier based on one auto-selected logarithmic band-power feature. In 24 minutes of training, the co-adaptive BCI worked significantly (p = 0.01) better than chance for 18 of 22 end users. The self-paced BCI training paradigm worked significantly (p = 0.01) better than chance in 11 of 20 end users. The presented co-adaptive BCI complements existing approaches in that it supports a non-control state, requires very little setup time, requires no BCI expert and works online based on only two electrodes. The preliminary results from the self-paced BCI paradigm compare favorably to previous studies and the collected data will allow to further improve self-paced BCI systems for disabled users.     

Model analyses of visual biofeedback training for EEG-based brain-computer interface

The primary goal of this study was to construct a simulation model of a biofeedback brain-computer interface (BCI) system to analyze the effect of biofeedback training on BCI users. A mathematical model of a man-machine visual-biofeedback BCI system was constructed to simulate a subject using a BCI system to control cursor movements. The model consisted of a visual tracking system, a thalamo-cortical model for EEG generation, and a BCI system. The BCI system in the model was realized for real experiments of visual biofeedback training. Ten sessions of visual biofeedback training were performed in eight normal subjects during a 3-week period. The task was to move a cursor horizontally across a screen, or to hold it at the screen’s center. Experimental conditions and EEG data obtained from real experiments were then simulated with the model. Three model parameters, representing the adaptation rate of gain in the visual tracking system and the relative synaptic strength between the thalamic reticular and thalamo-cortical cells in the Rolandic areas, were estimated by optimization techniques so that the performance of the model best fitted the experimental results. The serial changes of these parameters over the ten sessions, reflecting the effects of biofeedback training, were analyzed. The model simulation could reproduce results similar to the experimental data. The group mean success rate and information transfer rate improved significantly after training (56.6 to 81.1% and 0.19 to 0.76 bits/trial, respectively). All three model parameters displayed similar and statistically significant increasing trends with time. Extensive simulation with systematic changes of these parameters also demonstrated that assigning larger values to the parameters improved the BCI performance. We constructed a model of a biofeedback BCI system that could simulate experimental data and the effect of training. The simulation results implied that the improvement was achieved through a quicker adaptation rate in visual tracking gain and a larger synaptic gain from the visual tracking system to the thalamic reticular cells. In addition to the purpose of this study, the constructed biofeedback BCI model can also be used both to investigate the effects of different biofeedback paradigms and to test, estimate, or predict the performances of other newly developed BCI signal processing algorithms.     

Real-time knee adduction moment feedback for gait retraining through visual and tactile displays

The external knee adduction moment (KAM) measured during gait is an indicator of tibiofemoral joint osteoarthritis progression and various strategies have been proposed to lower it. Gait retraining has been shown to be an effective, noninvasive approach for lowering the KAM. We present a new gait retraining approach in which the KAM is fed back to subjects in real-time during ambulation. A study was conducted in which 16 healthy subjects learned to alter gait patterns to lower the KAM through visual or tactile (vibration) feedback. Participants converged on a comfortable gait in just a few minutes by using the feedback to iterate on various kinematic modifications. All subjects adopted altered gait patterns with lower KAM compared with normal ambulation (average reduction of 20.7%). Tactile and visual feedbacks were equally effective for real-time training, although subjects using tactile feedback took longer to converge on an acceptable gait. This study shows that real-time feedback of the KAM can greatly increase the effectiveness and efficiency of subject-specific gait retraining compared with conventional methods.     

Operant conditioning of EEG rhythms and ritalin in the treatment of hyperkinesis

Enhanced voluntary motor inhibition regularly accompanies conditioned increases in the sensorimotor rhythm (SMR), a 12--14-Hz Rolandic EEG rhythm in cats.A similar rhythm, presumably SMR, has also been identified in the human EEG. The clinical effectiveness of SMR operant conditioning has been claimed for epilepsy, insomnia, and hyperkinesis concurrent with seizure disorders. The present report attempts to follow up and replicate preliminary findings that suggested the technique's successful application to hyperkinesis uncomplicated by a history of epilepsy. SMR was defined as 12--14-Hz EEG activity in the absence of high-voltage slow-wave activity between 4 and 7 Hz. Anticipated treatment effects were indexed by systematic behavioral assessments of undirected motor activity and short attention span in the classroom. EEG and behavioral indices were monitored in four hyperkinetic children under the following six conditions: (1) No Drug, (2) Drug Only, (3) Drug and SMR Training I, (4) Drug and SMR Reversal Training, (5) Drug and SMR Training II, (6) No Drug and SMR Training. All hyperkinetic subjects were maintained on a constant drug regimen throughout the phases employing chemotherapy. Contingent increases and decreases in SMR occurred in three of four training subjects and were associated with similar changes in classroom assessments of motor inactivity. Combining medication and SMR training resulted in substantial improvements that exceeded the effects of drugs alone and were sustained with SMR training after medication was withdrawn. In contrast, these physiological and behavioral changes were absent in one highly distractible subject who failed to acquire the SMR task. Finally, pretraining levels of SMR accurately reflected both the seve-ity of original motor deficits and the susceptibility of hyperkinetic subjects to both treatments. Although the procedure clearly reduced hyperkinetic behavior, a salient, specific therapeutic factor could not be identified due to the dual EEG contingency imposed combined with associated changes in EMG. Despite these and other qualifying factors, the findings suggested the prognostic and diagnostic value of the SMR in the disorder when overactivity rather than distractibility is the predominant behavioral deficit.     

A P300-based Brain-Computer Interface with Stimuli on Moving Objects: Four-Session Single-Trial and Triple-Trial Tests with a Game-Like Task Design

Brain-computer interfaces (BCIs) are tools for controlling computers and other devices without using muscular activity, employing user-controlled variations in signals recorded from the user’s brain. One of the most efficient noninvasive BCIs is based on the P300 wave of the brain’s response to stimuli and is therefore referred to as the P300 BCI. Many modifications of this BCI have been proposed to further improve the BCI’s characteristics or to better adapt the BCI to various applications. However, in the original P300 BCI and in all of its modifications, the spatial positions of stimuli were fixed relative to each other, which can impose constraints on designing applications controlled by this BCI. We designed and tested a P300 BCI with stimuli presented on objects that were freely moving on a screen at a speed of 5.4°/s. Healthy participants practiced a game-like task with this BCI in either single-trial or triple-trial mode within four sessions. At each step, the participants were required to select one of nine moving objects. The mean online accuracy of BCI-based selection was 81% in the triple-trial mode and 65% in the single-trial mode. A relatively high P300 amplitude was observed in response to targets in most participants. Self-rated interest in the task was high and stable over the four sessions (the medians in the 1st/4th sessions were 79/84% and 76/71% in the groups practicing in the single-trial and triple-trial modes, respectively). We conclude that the movement of stimulus positions relative to each other may not prevent the efficient use of the P300 BCI by people controlling their gaze, e.g., in robotic devices and in video games.     

Operant conditioning of EEG rhythms and ritalin in the treatment of hyperkinesis

Enhanced voluntary motor inhibition regularly accompanies conditioned increases in the sensorimotor rhythm (SMR), a 12–14-Hz Rolandic EEG rhythm in cats. A similar rhythm, presumably SMR, has also been identified in the human EEG. The clinical effectiveness of SMR operant conditioning has been claimed for epilepsy, insomnia, and hyperkinesis concurrent with seizure disorders. The present report attempts to follow up and replicate preliminary findings that suggested the technique's successful application to hyperkinesis uncomplicated by a history of epilepsy. SMR was defined as 12–14-Hz EEG activity in the absence of high-voltage slow-wave activity between 4 and 7 Hz. Anticipated treatment effects were indexed by systematic behavioral assessments of undirected motor activity and short attention span in the classroom. EEG and behavioral indices were monitored in four hyperkinetic children under the following six conditions: (1) No Drug, (2) Drug Only, (3) Drug and SMR Training I, (4) Drug and SMR Reversal Training, (5) Drug and SMR Training II, (6) No Drug and SMR Training. All hyperkinetic subjects were maintained on a constant drug regimen throughout the phases employing chemotherapy. Contingent increases and decreases in SMR occurred in three of four training subjects and were associated with similar changes in classroom assessments of motor inactivity. Combining medication and SMR training resulted in substantial improvements that exceeded the effects of drugs alone and were sustained with SMR training after medication was withdrawn. In contrast, these physiological and behavioral changes were absent in one highly distractible subject who failed to acquire the SMR task. Finally, pretraining levels of SMR accurately reflected both the severity of original motor deficits and the susceptibility of hyperkinetic subjects to both treatments. Although the procedure clearly reduced hyperkinetic behavior, a salient, specific therapeutic factor could not be identified due to the dual EEG contingency imposed combined with associated changes in EMG. Despite these and other qualifying factors, the findings suggested the prognostic and diagnostic value of the SMR in the disorder when overactivity rather than distractibility is the predominant behavioral deficit.     

Control of different electromyogram levels of M. abductor pollicis brevis by means of visual feedback in healthy subjects

We studied voluntary control of integrated electromyogram (IEMG) in the range of 20 +/- 5% and 40 +/- 5% of the IEMG of m. abductor pollicis brevis during its maximum voluntary contraction with and without visual feedback. Healthy subjects performed IEMG control with visual feedback in 5 trials; IEMG control with visual feedback in 5 trials for 5 days, and the reproduction of memorized IEMG value without visual feedback after 5 trials of IEMG under the visual control. The accuracy of IEMG control was estimated by the following parameters: time of IEMG being out of the required 10% range (ERROR); IEMG variability (VARIABILITY), and the bias of IEMG mean level (BIAS) during 30-sec trials. The IEMG control in the range of 20 +/- 5% with visual feedback improved in all subjects over the course of 5 trials. Within 5-day training, ERROR and VARIABILITY reduced on the first day only; during the last 4 days there was no accuracy increase. ERROR increased more than twice when the 20% IEMG level was reproduced without vision. The IEMG control in the range of 40 +/- 5% improved neither during 5 trials, nor during 5 days of training with visual feedback. ERROR increased for about 1.5 times when the 40% IEMG level was reproduced without vision. It was concluded that the motor system, particularly the motor cortex, could control the given level of muscle activity using the visual feedback.     

An instance of viewpoint consistency in pigeon object recognition

Pigeons were trained on a visual discrimination, a task using a TV monitor. Two different types of stimuli appeared as pictures on the TV screen, one was a feeder used in their home cages and the other a coffee mug. One group of the pigeons was trained to peck the screen when the feeder appeared on it, while the other group was trained to peck the screen when the mug appeared. The feeder was considered to be a `familiar object' but the mug an `unfamiliar object' for the subjects. After training, to peck the familiar object, the subjects showed generalization to unusual view pictures of the object, but they did not show such generalization after training to peck the unfamiliar object. These results suggest that view point consistency is limited to familiar objects in pigeons.     

基于节律性脑电信号的脑-机接口

脑-机接口系统是一个不依靠外周神经和肌肉组织等而实现大脑和外界装置之间直接的交流和控制的通道。它为那些运动障碍的残疾人表达自己的意愿和实现对外部设备的控制提供了一种新的强大的技术支持。基于脑电的脑-机接口作为一种非侵入型的技术引起了该领域很多人的关注。基于脑电的脑-机接口采用了很多种类型的脑电信号。其中,振荡性的脑电图由于有较高的幅值和对噪声不敏感等特性而体现出极大的优势。也是由于这些原因,振荡性的脑电图变成了脑-机接口的应用中非常成功的设计之一。本文要介绍主要的基于脑电的脑-机接口中的两种,分别是稳态视觉诱发电位和基于运动本体感觉节律的脑-机接口。作者将详细的叙述该研究的生理背景、脑-机接口的参数,以及该系统的构造及信号处理的方法,并且会演示一些具有潜在应用价值的科研成果。     

Principles of neurorehabilitation based on the brain-computer interface and biologically adequate control of the exoskeleton

The neurophysiological prerequisites for the development and operation of the brain-computer interfaces (BCI) that allow cerebral electrical signals alone to control external technical devices are considered. A BCI based on the discrimination of the EEG patterns related to imagery of extremity movements is described. The possibility of the rehabilitation of patients with motor disorders by means of the BCI based on motor imagery and the exoskeleton controlled by it is discussed.     

Effects of Neurofeedback Training on Performing Bimanual Coordination In-phase and Anti-phase Patterns in Children with ADHD

It is generally accepted that children with attention-deficit/hyperactivity disorder (ADHD) have poor motor control, especially in bimanual coordination tasks. Such children characteristically have impaired fine motor ability, problems with force control, and poor motor coordination. They are at particular risk of loss of motor control and reduced bimanual coordination. We tested whether, compared to a control condition, neurofeedback training (NFT) could improve bimanual coordination among children with ADHD. 20 Children with ADHD (mean age 7.9 years; SD 2.11) were randomly assigned either to NFT or to a control condition. All participants completed a bimanual coordination test at the following time points: baseline, assessment 1, assessment 2, assessment 3, and again 12 session later at posttest. NFT consisted of Sensory Motor Rhythm (SMR) training to achieve increased SMR in C3 and C4, while participants in the control condition were under mock NFT conditions. Bimanual coordination accuracy and consistency improved from baseline to completion of the intervention (significant Time effect), but in the NFT condition (significant time?×?group interaction). Compared to the control condition, the NFT group had fewer errors in both patterns of bimanual coordination (significant Group effect). Among children with ADHD, SMR neurofeedback training (NFT) led to significant improvements in a bimanual coordination task. The SMR NFT thus appears to have the potential to improve and enhance the motor control of ADHD patients.     

Large-Scale Assessment of a Fully Automatic Co-Adaptive Motor Imagery-Based Brain Computer Interface

In the last years Brain Computer Interface (BCI) technology has benefited from the development of sophisticated machine leaning methods that let the user operate the BCI after a few trials of calibration. One remarkable example is the recent development of co-adaptive techniques that proved to extend the use of BCIs also to people not able to achieve successful control with the standard BCI procedure. Especially for BCIs based on the modulation of the Sensorimotor Rhythm (SMR) these improvements are essential, since a not negligible percentage of users is unable to operate SMR-BCIs efficiently. In this study we evaluated for the first time a fully automatic co-adaptive BCI system on a large scale. A pool of 168 participants naive to BCIs operated the co-adaptive SMR-BCI in one single session. Different psychological interventions were performed prior the BCI session in order to investigate how motor coordination training and relaxation could influence BCI performance. A neurophysiological indicator based on the Power Spectral Density (PSD) was extracted by the recording of few minutes of resting state brain activity and tested as predictor of BCI performances. Results show that high accuracies in operating the BCI could be reached by the majority of the participants before the end of the session. BCI performances could be significantly predicted by the neurophysiological indicator, consolidating the validity of the model previously developed. Anyway, we still found about 22% of users with performance significantly lower than the threshold of efficient BCI control at the end of the session. Being the inter-subject variability still the major problem of BCI technology, we pointed out crucial issues for those who did not achieve sufficient control. Finally, we propose valid developments to move a step forward to the applicability of the promising co-adaptive methods.     

Conscious Brain-to-Brain Communication in Humans Using Non-Invasive Technologies

Human sensory and motor systems provide the natural means for the exchange of information between individuals, and, hence, the basis for human civilization. The recent development of brain-computer interfaces (BCI) has provided an important element for the creation of brain-to-brain communication systems, and precise brain stimulation techniques are now available for the realization of non-invasive computer-brain interfaces (CBI). These technologies, BCI and CBI, can be combined to realize the vision of non-invasive, computer-mediated brain-to-brain (B2B) communication between subjects (hyperinteraction). Here we demonstrate the conscious transmission of information between human brains through the intact scalp and without intervention of motor or peripheral sensory systems. Pseudo-random binary streams encoding words were transmitted between the minds of emitter and receiver subjects separated by great distances, representing the realization of the first human brain-to-brain interface. In a series of experiments, we established internet-mediated B2B communication by combining a BCI based on voluntary motor imagery-controlled electroencephalographic (EEG) changes with a CBI inducing the conscious perception of phosphenes (light flashes) through neuronavigated, robotized transcranial magnetic stimulation (TMS), with special care taken to block sensory (tactile, visual or auditory) cues. Our results provide a critical proof-of-principle demonstration for the development of conscious B2B communication technologies. More fully developed, related implementations will open new research venues in cognitive, social and clinical neuroscience and the scientific study of consciousness. We envision that hyperinteraction technologies will eventually have a profound impact on the social structure of our civilization and raise important ethical issues.     

A New Auditory Multi-Class Brain-Computer Interface Paradigm: Spatial Hearing as an Informative Cue

Most P300-based brain-computer interface (BCI) approaches use the visual modality for stimulation. For use with patients suffering from amyotrophic lateral sclerosis (ALS) this might not be the preferable choice because of sight deterioration. Moreover, using a modality different from the visual one minimizes interference with possible visual feedback. Therefore, a multi-class BCI paradigm is proposed that uses spatially distributed, auditory cues. Ten healthy subjects participated in an offline oddball task with the spatial location of the stimuli being a discriminating cue. Experiments were done in free field, with an individual speaker for each location. Different inter-stimulus intervals of 1000 ms, 300 ms and 175 ms were tested. With averaging over multiple repetitions, selection scores went over 90% for most conditions, i.e., in over 90% of the trials the correct location was selected. One subject reached a 100% correct score. Corresponding information transfer rates were high, up to an average score of 17.39 bits/minute for the 175 ms condition (best subject 25.20 bits/minute). When presenting the stimuli through a single speaker, thus effectively canceling the spatial properties of the cue, selection scores went down below 70% for most subjects. We conclude that the proposed spatial auditory paradigm is successful for healthy subjects and shows promising results that may lead to a fast BCI that solely relies on the auditory sense.     

Prediction of Auditory and Visual P300 Brain-Computer Interface Aptitude

Objective

Brain-computer interfaces (BCIs) provide a non-muscular communication channel for patients with late-stage motoneuron disease (e.g., amyotrophic lateral sclerosis (ALS)) or otherwise motor impaired people and are also used for motor rehabilitation in chronic stroke. Differences in the ability to use a BCI vary from person to person and from session to session. A reliable predictor of aptitude would allow for the selection of suitable BCI paradigms. For this reason, we investigated whether P300 BCI aptitude could be predicted from a short experiment with a standard auditory oddball.

Methods

Forty healthy participants performed an electroencephalography (EEG) based visual and auditory P300-BCI spelling task in a single session. In addition, prior to each session an auditory oddball was presented. Features extracted from the auditory oddball were analyzed with respect to predictive power for BCI aptitude.

Results

Correlation between auditory oddball response and P300 BCI accuracy revealed a strong relationship between accuracy and N2 amplitude and the amplitude of a late ERP component between 400 and 600 ms. Interestingly, the P3 amplitude of the auditory oddball response was not correlated with accuracy.

Conclusions

Event-related potentials recorded during a standard auditory oddball session moderately predict aptitude in an audiory and highly in a visual P300 BCI. The predictor will allow for faster paradigm selection.

Significance

Our method will reduce strain on patients because unsuccessful training may be avoided, provided the results can be generalized to the patient population.     

Behavioral management of epileptic seizures following EEG biofeedback training of the sensorimotor rhythm

Eight severely epileptic patients, four males and four females, ranging in age from 10 to 29 years, were trained to increase 12–14 Hz EEG activity from the regions overlying the Rolandic area. This activity, the sensorimotor rhythm(SMR), has been hypothesized to be related to motor inhibitory processes(Sterman, 1974). The patients represented a crosssection of several different types of epilepsy, including grand mal, myoclonic, akinetic, focal, and psychomotor types. Three of them had varying degrees of mental retardation. SMR was detected by a combination of an analog filtering system and digital processing. Feedback, both auditory and/or visual, was provided whenever one-half second of 12–14-Hz activity was detected in the EEG. Patients were provided with additional feedback keyed by the output of a 4–7-Hz filter which indicated the presence of epileptiform spike activity, slow waves, or movement. Feedback for SMR was inhibited whenever slow-wave activity spikes or movement was also present. During the treatment period most of the patients showed varying degrees of improvement. Two of the patients who had been severely epileptic, having multiple seizures per week, have been seizure free for periods of up to 1 month. Other patients have developed the ability to block many of their seizures. Seizure intensity and duration have also decreased. Furthermore, the successful patients demonstrated an increase in the amount of SMR and an increase in amplitude of SMR during the training period. Spectral analyses for the EEGs were performed periodically. The effectiveness of SMR conditioning for the control of epileptic seizures is evaluated in terms of patient characteristics and type of seizures.     

Retention of ventilatory pattern learning in normal subjects

Two procedures for training normal subjects to increase inspiratory duration (TI) were compared. In the first procedure (feedback), a visual signal informed subjects of their TI value just after the end of each inspiration; subjects were instructed to maintain TI for a set interval previously established by the experimenter. The second procedure (pacing) consisted of delivering a periodic signal to subjects and instructing them to adjust their respiratory frequency to this signal. All subjects participated in two identical sessions, 24 h apart. Comparison of performances between the two sessions provides evidence for a retention effect in feedback subjects only, suggesting the superiority of this method. Voluntary increase of TI during training induced a spontaneous increase of tidal volume, independent of any instruction. This increase in breathing amplitude cannot be explained in terms of chemical control of breathing.