Messerotti Benvenuti, S., G. Buodo, et al. (2011). "Neurofeedback training for tourette syndrome: an uncontrolled single case study." Appl Psychophysiol Biofeedback 36(4): 281-288.

 

Gilles de la Tourette syndrome (TS) is characterized by motor and vocal tic manifestations, often accompanied by behavioral, cognitive and affective dysfunctions. Electroencephalography of patients with TS has revealed reduced Sensorimotor Rhythm (SMR) and excessive fronto-central Theta activity, that presumably underlie motor and cognitive disturbances in TS. Some evidence exists that neurofeedback (NFB) training aimed at enhancing SMR amplitude is effective for reducing tics. The present report is an uncontrolled single case study where a NFB training protocol, involving combined SMR uptraining/Theta downtraining was delivered to a 17-year-old male with TS. After sixteen SMR-Theta sessions, six additional sessions were administered with SMR uptraining alone. SMR increase was better obtained when SMR uptraining was administered alone, whereas Theta decrease was observed after both trainings. The patient showed a reduction of tics and affective symptoms, and improvement of cognitive performance after both trainings. Overall, these findings suggest that Theta decrease might account for some clinical effects seen in conjunction with SMR uptraining. Future studies should clarify the feasibility of NFB protocols for patients with TS beyond SMR uptraining alone.

Mihara, M., I. Miyai, et al. (2012). "Neurofeedback using real-time near-infrared spectroscopy enhances motor imagery related cortical activation." PLoS One7(3): e32234.

 

Accumulating evidence indicates that motor imagery and motor execution share common neural networks. Accordingly, mental practices in the form of motor imagery have been implemented in rehabilitation regimes of stroke patients with favorable results. Because direct monitoring of motor imagery is difficult, feedback of cortical activities related to motor imagery (neurofeedback) could help to enhance efficacy of mental practice with motor imagery. To determine the feasibility and efficacy of a real-time neurofeedback system mediated by near-infrared spectroscopy (NIRS), two separate experiments were performed. Experiment 1 was used in five subjects to evaluate whether real-time cortical oxygenated hemoglobin signal feedback during a motor execution task correlated with reference hemoglobin signals computed off-line. Results demonstrated that the NIRS-mediated neurofeedback system reliably detected oxygenated hemoglobin signal changes in real-time. In Experiment 2, 21 subjects performed motor imagery of finger movements with feedback from relevant cortical signals and irrelevant sham signals. Real neurofeedback induced significantly greater activation of the contralateral premotor cortex and greater self-assessment scores for kinesthetic motor imagery compared with sham feedback. These findings suggested the feasibility and potential effectiveness of a NIRS-mediated real-time neurofeedback system on performance of kinesthetic motor imagery. However, these results warrant further clinical trials to determine whether this system could enhance the effects of mental practice in stroke patients.

 

Samani, A., A. Holtermann, et al. (2010). "Active biofeedback changes the spatial distribution of upper trapezius muscle activity during computer work." Eur J Appl Physiol 110(2): 415-423.

 

The aim of this study was to investigate the spatio-temporal effects of advanced biofeedback by inducing active and passive pauses on the trapezius activity pattern using high-density surface electromyography (HD-EMG). Thirteen healthy male subjects performed computer work with superimposed feedback either eliciting passive (rest) or active (approximately 30% MVC) pauses based on fuzzy logic design and a control session with no feedback. HD-EMG signals of upper trapezius were recorded using a 5 x 13 multichannel electrode grid. From the HD-EMG recordings, two-dimensional maps of root mean square (RMS), relative rest time (RRT) and permuted sample entropy (PeSaEn) were obtained. The centre of gravity (CoG) and entropy of maps were used to quantify changes in the spatial distribution of muscle activity. PeSaEn as a measure of temporal heterogeneity for each channel, decreased over the whole map in response to active pause (P < 0.05) underlining a more homogenous activation pattern. Concomitantly, the CoG of RRT maps moved in caudal direction and the entropy of RMS maps as a measure of spatial heterogeneity over the whole recording grid, increased in response to active pause session compared with control session (no feedback) (P < 0.05). Active pause compared with control resulted in more heterogeneous coordination of trapezius compared with no feedback implying a more uneven spatial distribution of the biomechanical load. The study introduced new aspects in relation to the potential benefit of superimposed muscle contraction in relation to the spatial organization of muscle activity during computer work.

 

Shindo, K., K. Kawashima, et al. (2011). "Effects of neurofeedback training with an electroencephalogram-based brain-computer interface for hand paralysis in patients with chronic stroke: a preliminary case series study." J Rehabil Med 43(10): 951-957.

 

OBJECTIVE: To explore the effectiveness of neurorehabilitative training using an electroencephalogram-based brain- computer interface for hand paralysis following stroke. DESIGN: A case series study. SUBJECTS: Eight outpatients with chronic stroke demonstrating moderate to severe hemiparesis. METHODS: Based on analysis of volitionally decreased amplitudes of sensory motor rhythm during motor imagery involving extending the affected fingers, real-time visual feedback was provided. After successful motor imagery, a mechanical orthosis partially extended the fingers. Brain-computer interface interventions were carried out once or twice a week for a period of 4-7 months, and clinical and neurophysiological examinations pre- and post-intervention were compared. RESULTS: New voluntary electromyographic activity was measured in the affected finger extensors in 4 cases who had little or no muscle activity before the training, and the other participants exhibited improvement in finger function. Significantly greater suppression of the sensory motor rhythm over both hemispheres was observed during motor imagery. Transcranial magnetic stimulation showed increased cortical excitability in the damaged hemisphere. Success rates of brain-computer interface training tended to increase as the session progressed in 4 cases. CONCLUSION: Brain-computer interface training appears to have yielded some improvement in motor function and brain plasticity. Further controlled research is needed to clarify the role of the brain-computer interface system.

 

Subramanian, L., J. V. Hindle, et al. (2011). "Real-time functional magnetic resonance imaging neurofeedback for treatment of Parkinson's disease." J Neurosci31(45): 16309-16317.

 

Self-regulation of brain activity in humans based on real-time feedback of functional magnetic resonance imaging (fMRI) signal is emerging as a potentially powerful, new technique. Here, we assessed whether patients with Parkinson's disease (PD) are able to alter local brain activity to improve motor function. Five patients learned to increase activity in the supplementary motor complex over two fMRI sessions using motor imagery. They attained as much activation in this target brain region as during a localizer procedure with overt movements. Concomitantly, they showed an improvement in motor speed (finger tapping) and clinical ratings of motor symptoms (37% improvement of the motor scale of the Unified Parkinson's Disease Rating Scale). Activation during neurofeedback was also observed in other cortical motor areas and the basal ganglia, including the subthalamic nucleus and globus pallidus, which are connected to the supplementary motor area (SMA) and crucial nodes in the pathophysiology of PD. A PD control group of five patients, matched for clinical severity and medication, underwent the same procedure but did not receive feedback about their SMA activity. This group attained no control of SMA activation and showed no motor improvement. These findings demonstrate that self-modulation of cortico-subcortical motor circuits can be achieved by PD patients through neurofeedback and may result in clinical benefits that are not attainable by motor imagery alone.

 

Tornoe, B. and L. Skov (2012). "Computer animated relaxation therapy in children between 7 and 13 years with tension-type headache: a pilot study." Appl Psychophysiol Biofeedback 37(1): 35-44.

 

This pilot study evaluated the effect of computer animated relaxation therapy in children between 7 and 13 years with tension-type headache and the children's experiences with the therapy. The therapy consisted of an uncontrolled nine-session course in modified progressive relaxation therapy assisted by computer animated surface EMG provided from the trapezius muscles and with the physiotherapist as a participant observer. Outcome measures were (a) headache frequency and intensity, (b) pericranial tenderness, (c) tension patterns, and (d) evaluations assessed at baseline and at 3 months follow up. Nine children, mean age 10.9 (SD 1.7) years, diagnosed with frequent episodic or chronic tension-type headache completed the course. The results showed a mean improvement of 45% for headache frequency at 3 months follow up versus baseline and a significant reduction in headache frequency for all participants and in Total Tenderness Score for children with frequent episodic tension-type headache. The children expressed a growing understanding of body reactions and an acquired ability to deactivate and regulate these reactions. Computer animated SEMG seems an applicable learning strategy for young headache sufferers. This study suggests that children below the age of 13 need both the dialog and guidance from a participant observer in order to achieve body awareness.

 

van de Vijver, I., K. R. Ridderinkhof, et al. (2011). "Frontal oscillatory dynamics predict feedback learning and action adjustment." J Cogn Neurosci 23(12): 4106-4121.

 

Frontal oscillatory dynamics in the theta (4-8 Hz) and beta (20-30 Hz) frequency bands have been implicated in cognitive control processes. Here we investigated the changes in coordinated activity within and between frontal brain areas during feedback-based response learning. In a time estimation task, participants learned to press a button after specific, randomly selected time intervals (300-2000 msec) using the feedback after each button press (correct, too fast, too slow). Consistent with previous findings, theta-band activity over medial frontal scalp sites (presumably reflecting medial frontal cortex activity) was stronger after negative feedback, whereas beta-band activity was stronger after positive feedback. Theta-band power predicted learning only after negative feedback, and beta-band power predicted learning after positive and negative feedback. Furthermore, negative feedback increased theta-band intersite phase synchrony (a millisecond resolution measure of functional connectivity) among right lateral prefrontal, medial frontal, and sensorimotor sites. These results demonstrate the importance of frontal theta- and beta-band oscillations and intersite communication in the realization of reinforcement learning.

 

Watanabe, A., K. Kanemura, et al. (2011). "Effect of electromyogram biofeedback on daytime clenching behavior in subjects with masticatory muscle pain." J Prosthodont Res 55(2): 75-81.

 

PURPOSE: Although daytime clenching is believed to be one of the oral parafunctions leading to dental problems, a treatment strategy has not yet been devised. Electromyogram (EMG) biofeedback training was performed to ascertain its effect on the regulation of daytime clenching behavior. MATERIALS AND METHODS: Twenty subjects (mean age, 30.9+/-5.6 years) who had mild to moderate masticatory muscle pain with daytime clenching behavior were randomly divided into either a biofeedback group (BF) or control group (CO). Subjects were fitted with a hearing-aid-shaped EMG recording and biofeedback apparatus which was used to record EMG data under natural conditions from the temporal muscle, continuously for five hours on four consecutive days. EMG data on Days 1 and 4 were recorded without biofeedback as pre-test and post-test, respectively, and on Days 2 and 3, subjects in the BF group noticed their clenching behaviors via an alert sound from the EMG biofeedback apparatus. No alert sound was given for the CO group throughout the recording sessions. RESULTS: There was no significant difference in the number of clenching events for five hours between the BF group (4.6+/-2.5) and CO group (4.6+/-0.9) on Day 1, however a significant decrease was found in the BF group between Day 1 (4.6+/-2.5) and Day 4 (2.4+/-1.7; P<0.05). CONCLUSION: Daytime clenching was reduced in the short-term with the help of an EMG biofeedback system under natural circumstances. Further research is needed to confirm a long-lasting effect.

 

Prosthetic Training

 

Corbett, E. A., E. J. Perreault, et al. (2011). "Comparison of electromyography and force as interfaces for prosthetic control." J Rehabil Res Dev 48(6): 629-641.

 

The ease with which persons with upper-limb amputations can control their powered prostheses is largely determined by the efficacy of the user command interface. One needs to understand the abilities of the human operator regarding the different available options. Electromyography (EMG) is widely used to control powered upper-limb prostheses. It is an indirect estimator of muscle force and may be expected to limit the control capabilities of the prosthesis user. This study compared EMG control with force control, an interface that is used in everyday interactions with the environment. We used both methods to perform a position-tracking task. Direct-position control of the wrist provided an upper bound for human-operator capabilities. The results demonstrated that an EMG control interface is as effective as force control for the position-tracking task. We also examined the effects of gain and tracking frequency on EMG control to explore the limits of this control interface. We found that information transmission rates for myoelectric control were best at higher tracking frequencies than at the frequencies previously reported for position control. The results may be useful for the design of prostheses and prosthetic controllers.

 

Damian, D. D., A. H. Arita, et al. (2012). "Slip speed feedback for grip force control." IEEE Trans Biomed Eng 59(8): 2200-2210.

 

Grasp stability in the human hand has been resolved by means of an intricate network of mechanoreceptors integrating numerous cues about mechanical events, through an ontogenetic grasp practice. An engineered prosthetic interface introduces considerable perturbation risks in grasping, calling for feedback modalities that address the underlying slip phenomenon. In this study, we propose an enhanced slip feedback modality, with potential for myoelectric-based prosthetic applications, that relays information regarding slip events, particularly slip occurrence and slip speed. The proposed feedback modality, implemented using electrotactile stimulation, was evaluated in psychophysical studies of slip control in a simplified setup. The obtained results were compared with vision and a binary slip feedback that transmits on-off information about slip detection. The slip control efficiency of the slip speed display is comparable to that obtained with vision feedback, and it clearly outperforms the efficiency of the on-off slip modality in such tasks. These results suggest that the proposed tactile feedback is a promising sensory method for the restoration of stable grasp in prosthetic applications.

 

Lipschutz, R. D., B. Lock, et al. (2011). "Use of two-axis joystick for control of externally powered shoulder disarticulation prostheses." J Rehabil Res Dev 48(6): 661-667.

 

We explored a new method for simple and accurate control of shoulder movement for externally powered shoulder disarticulation prostheses with a two-axis joystick. We tested 10 subjects with intact shoulders and arms to determine the average amount of shoulder motion and force available to control an electronic input device. We then applied this information to two different input strategies to examine their effectiveness: (1) a traditional rocker potentiometer and a pair of force-sensing resistors and (2) a two-axis joystick. Three nondisabled subjects and two subjects with shoulder disarticulation amputations attempted to control an experimental externally powered shoulder using both control strategies. Two powered arms were tested, one with powered flexion/extension and humeral rotation and one with powered flexion/extension and adduction/abduction. Overwhelmingly, the subjects preferred the joystick control, because it was more intuitively linked with their shoulder movement. Additionally, two motions (one in each axis) could be controlled simultaneously. This pilot study provides valuable insight into an effective means of controlling high-level, externally powered prostheses with a two-axis joystick

Nataraj, R., M. L. Audu, et al. (2012). "Trunk acceleration for neuroprosthetic control of standing: a pilot study." J Appl Biomech 28(1): 85-92.

This pilot study investigated the potential of using trunk acceleration feedback control of center of pressure (COP) against postural disturbances with a standing neuroprosthesis following paralysis. Artificial neural networks (ANNs) were trained to use three-dimensional trunk acceleration as input to predict changes in COP for able-bodied subjects undergoing perturbations during bipedal stance. Correlation coefficients between ANN predictions and actual COP ranged from 0.67 to 0.77. An ANN trained across all subject-normalized data was used to drive feedback control of ankle muscle excitation levels for a computer model representing a standing neuroprosthesis user. Feedback control reduced average upper-body loading during perturbation onset and recovery by 42% and peak loading by 29% compared with optimal, constant excitation.

Peerdeman, B., D. Boere, et al. (2011). "Myoelectric forearm prostheses: state of the art from a user-centered perspective." J Rehabil Res Dev 48(6): 719-737.

User acceptance of myoelectric forearm prostheses is currently low. Awkward control, lack of feedback, and difficult training are cited as primary reasons. Recently, researchers have focused on exploiting the new possibilities offered by advancements in prosthetic technology. Alternatively, researchers could focus on prosthesis acceptance by developing functional requirements based on activities users are likely to perform. In this article, we describe the process of determining such requirements and then the application of these requirements to evaluating the state of the art in myoelectric forearm prosthesis research. As part of a needs assessment, a workshop was organized involving clinicians (representing end users), academics, and engineers. The resulting needs included an increased number of functions, lower reaction and execution times, and intuitiveness of both control and feedback systems. Reviewing the state of the art of research in the main prosthetic subsystems (electromyographic [EMG] sensing, control, and feedback) showed that modern research prototypes only partly fulfill the requirements. We found that focus should be on validating EMG-sensing results with patients, improving simultaneous control of wrist movements and grasps, deriving optimal parameters for force and position feedback, and taking into account the psychophysical aspects of feedback, such as intensity perception and spatial acuity.

 

Pulliam, C. L., J. M. Lambrecht, et al. (2011). "Electromyogram-based neural network control of transhumeral prostheses." J Rehabil Res Dev 48(6): 739-754.

 

Upper-limb amputation can cause a great deal of functional impairment for patients, particularly for those with amputation at or above the elbow. Our long-term objective is to improve functional outcomes for patients with amputation by integrating a fully implanted electromyographic (EMG) recording system with a wireless telemetry system that communicates with the patient's prosthesis. We believe that this should generate a scheme that will allow patients to robustly control multiple degrees of freedom simultaneously. The goal of this study is to evaluate the feasibility of predicting dynamic arm movements (both flexion/extension and pronation/supination) based on EMG signals from a set of muscles that would likely be intact in patients with transhumeral amputation. We recorded movement kinematics and EMG signals from seven muscles during a variety of movements with different complexities. Time-delayed artificial neural networks were then trained offline to predict the measured arm trajectories based on features extracted from the measured EMG signals. We evaluated the relative effectiveness of various muscle subsets. Predicted movement trajectories had average root-mean-square errors of approximately 15.7 degrees and 24.9 degrees and average R(2) values of approximately 0.81 and 0.46 for elbow flexion/extension and forearm pronation/supination, respectively.

 

Rossini, L. and P. M. Rossini (2010). "Combining ENG and EEG integrated analysis for better sensitivity and specificity of neuroprosthesis operations." Conf Proc IEEE Eng Med Biol Soc 2010: 134-137.

 

Combining non-invasive monitoring of action-related brain signals with the invasive recordings of the nerve motor output could provide robust natural and bidirectional multimodal Brain-Machine interfaces. One 26 years old, right-handed male who had suffered traumatic trans-radial amputation of the left arm was connected in a bidirectional way with a robotic hand prostheses. Cortical signals related with movement programming, execution, and feed-back were recorded by non-invasive scalp electrodes to detect high-level information (i.e. onset of movement intention), while the efferent neural activity containing the low-level commands towards the missing limb was recorded from the amputated nerves by multipolar intra-neural electrodes. The aim of this article is to report advanced experiences aiming to investigate whether information on "hand-related" activities can be decoded by the combined analysis of motor-related signals simultaneously gathered via intraneural electrodes implanted into the peripheral nervous system and scalp recorded electroencephalography signals to govern a dexterous hand prosthesis using the natural neural "pathway".

 

Scheme, E. and K. Englehart (2011). "Electromyogram pattern recognition for control of powered upper-limb prostheses: state of the art and challenges for clinical use." J Rehabil Res Dev 48(6): 643-659.

 

Using electromyogram (EMG) signals to control upper-limb prostheses is an important clinical option, offering a person with amputation autonomy of control by contracting residual muscles. The dexterity with which one may control a prosthesis has progressed very little, especially when controlling multiple degrees of freedom. Using pattern recognition to discriminate multiple degrees of freedom has shown great promise in the research literature, but it has yet to transition to a clinically viable option. This article describes the pertinent issues and best practices in EMG pattern recognition, identifies the major challenges in deploying robust control, and advocates research directions that may have an effect in the near future.

Schultz, A. E. and T. A. Kuiken (2011). "Neural interfaces for control of upper limb prostheses: the state of the art and future possibilities." PM R 3(1): 55-67.

Current treatment of upper limb amputation restores some degree of functional ability, but this ability falls far below the standard set by the natural arm. Although acceptance rates can be high when patients are highly motivated and receive proper training and care, current prostheses often fail to meet the daily needs of amputees and frequently are abandoned. Recent advancements in science and technology have led to promising methods of accessing neural information for communication or control. Researchers have explored invasive and noninvasive methods of connecting with muscles, nerves, or the brain to provide increased functionality for patients experiencing disease or injury, including amputation. These techniques offer hope of more natural and intuitive prosthesis control, and therefore increased quality of life for amputees. In this review, we discuss the current state of the art of neural interfaces, particularly those that may find application within the prosthetics field.

 

Simon, A. M., L. J. Hargrove, et al. (2011). "Target Achievement Control Test: evaluating real-time myoelectric pattern-recognition control of multifunctional upper-limb prostheses." J Rehabil Res Dev 48(6): 619-627.

 

Despite high classification accuracies (~95%) of myoelectric control systems based on pattern recognition, how well offline measures translate to real-time closed-loop control is unclear. Recently, a real-time virtual test analyzed how well subjects completed arm motions using a multiple-degree of freedom (DOF) classifier. Although this test provided real-time performance metrics, the required task was oversimplified: motion speeds were normalized and unintended movements were ignored. We included these considerations in a new, more challenging virtual test called the Target Achievement Control Test (TAC Test). Five subjects with transradial amputation attempted to move a virtual arm into a target posture using myoelectric pattern recognition, performing the test with various classifier (1- vs 3-DOF) and task complexities (one vs three required motions per posture). We found no significant difference in classification accuracy between the 1- and 3-DOF classifiers (97.2% +/- 2.0% and 94.1% +/- 3.1%, respectively; p=0.14). Subjects completed 31% fewer trials in significantly more time using the 3-DOF classifier and took 3.6 +/- 0.8 times longer to reach a three-motion posture compared with a one-motion posture. These results highlight the need for closed-loop performance measures and demonstrate that the TAC Test is a useful and more challenging tool to test real-time pattern-recognition performance.

 

Cognitive Disorders

 

Becerra, J., T. Fernandez, et al. (2012). "Neurofeedback in healthy elderly human subjects with electroencephalographic risk for cognitive disorder." J Alzheimers Dis 28(2): 357-367.

 

In normal elderly subjects, the best electroencephalogram (EEG)-based predictor of cognitive impairment is theta EEG activity abnormally high for their age. The goal of this work was to explore the effectiveness of a neurofeedback (NFB) protocol in reducing theta EEG activity in normal elderly subjects who present abnormally high theta absolute power (AP). Fourteen subjects were randomly assigned to either the experimental group or the control group; the experimental group received a reward (tone of 1000 Hz) when the theta AP was reduced, and the control group received a placebo treatment, a random administration of the same tone. The results show that the experimental group exhibits greater improvement in EEG and behavioral measures. However, subjects of the control group also show improved EEG values and in memory, which may be attributed to a placebo effect. However, the effect of the NFB treatment was clear in the EG, although a placebo effect may also have been present.

 

Dias, A. M., A. M. Van Deusen, et al. (2012). "Clinical efficacy of a new automated hemoencephalographic neurofeedback protocol." Span J Psychol 15(3): 930-941.

 

Among the ongoing attempts to enhance cognitive performance, an emergent and yet underrepresented venue is brought by hemoencefalographic neurofeedback (HEG). This paper presents three related advances in HEG neurofeedback for cognitive enhancement: a) a new HEG protocol for cognitive enhancement, as well as b) the results of independent measures of biological efficacy (EEG brain maps) extracted in three phases, during a one year follow up case study; c) the results of the first controlled clinical trial of HEG, designed to assess the efficacy of the technique for cognitive enhancement of an adult and neurologically intact population. The new protocol was developed in the environment of a software that organizes digital signal algorithms in a flowchart format. Brain maps were produced through 10 brain recordings. The clinical trial used a working memory test as its independent measure of achievement. The main conclusion of this study is that the technique appears to be clinically promising. Approaches to cognitive performance from a metabolic viewpoint should be explored further. However, it is particularly important to note that, to our knowledge, this is the world's first controlled clinical study on the matter and it is still early for an ultimate evaluation of the technique.

 

Seizure Disorders

 

Fritz, N. E., J. Fell, et al. (2011). "Do surface DC-shifts affect epileptic hippocampal EEG activity?" Epilepsy Res 95(1-2): 136-143.

 

 

Despite considerable research on EEG-feedback of slow cortical potentials (SCPs) for seizure control in epilepsy, the underlying mechanisms and the direct effects on intracerebral pathological activity within the focal area remain unclear. Intrahippocampal EEG recordings from four patients with temporal lobe epilepsy and implanted electrodes were analyzed with regard to spike activity and power in 10 frequency bands (0.5-148Hz) during SCP feedback based on surface recordings (position Cz). Trials with positive, negative and indifferent SCPs were contrasted. Three of the four patients showed changes in spike activity during SCPs, but these were inconsistent between patients, and resulted in increased and decreased activity in both positive and negative SCPs. Spectral analysis revealed that in all patients, positive surface shifts showed a bi-hemispheric higher power in the high-frequency activity above 40Hz. Two patients showed a higher power also during negative shifts, both in high-frequency activity and one in most other frequency bands. Feedback-related power effects did not differ between focal and non-focal side. The inconsistent change in spiking activity and the lack of decrease of power in pathology associated frequency bands during SCPs show that these SCPs do not decrease pathological activity within the epileptic focus. A possible relation of higher power in high-frequency activity during positive SCPs to cognitive processes, such as memory functions, is discussed.

 

Legarda, S. B., D. McMahon, et al. (2011). "Clinical neurofeedback: case studies, proposed mechanism, and implications for pediatric neurology practice." J Child Neurol 26(8): 1045-1051.

 

Trends in alternative medicine use by American health care consumers are rising substantially. Extensive literature exists reporting on the effectiveness of neurofeedback in the treatment of autism, closed head injury, insomnia, migraine, depression, attention deficit hyperactivity disorder, epilepsy, and posttraumatic stress disorder. We speculated that neurofeedback might serve as a therapeutic modality for patients with medically refractory neurological disorders and have begun referring patients to train with clinical neurofeedback practitioners. The modality is not always covered by insurance. Confident their child's medical and neurological needs would continue to be met, the parents of 3 children with epilepsy spectrum disorder decided to have their child train in the modality. The children's individual progress following neurofeedback are each presented here. A proposed mechanism and practice implications are discussed.

 

Lopour, B. A. and A. J. Szeri (2010). "A model of feedback control for the charge-balanced suppression of epileptic seizures." J Comput Neurosci 28(3): 375-387.

 

Here we present several refinements to a model of feedback control for the suppression of epileptic seizures. We utilize a stochastic partial differential equation (SPDE) model of the human cortex. First, we verify the strong convergence of numerical solutions to this model, paying special attention to the sharp spatial changes that occur at electrode edges. This allows us to choose appropriate step sizes for our simulations; because the spatial step size must be small relative to the size of an electrode in order to resolve its electrical behavior, we are able to include a more detailed electrode profile in the simulation. Then, based on evidence that the mean soma potential is not the variable most closely related to the measurement of a cortical surface electrode, we develop a new model for this. The model is based on the currents flowing in the cortex and is used for a simulation of feedback control. The simulation utilizes a new control algorithm incorporating the total integral of the applied electrical potential. Not only does this succeed in suppressing the seizure-like oscillations, but it guarantees that the applied signal will be charge-balanced and therefore unlikely to cause cortical damage.

 

Autism Spectrum Disorders

 

Holtmann, M., S. Steiner, et al. (2011). "Neurofeedback in autism spectrum disorders." Dev Med Child Neurol 53(11): 986-993.

AIM: To review current studies on the effectiveness of neurofeedback as a method of treatment of the core symptoms of autism spectrum disorders (ASD). METHOD: Studies were selected based on searches in PubMed, Ovid MEDLINE, EMBASE, ERIC, and CINAHL using combinations of the following keywords: 'Neurofeedback' OR 'EEG Biofeedback' OR 'Neurotherapy' OR 'Mu-Rhythm' OR 'SMR' AND 'Autism' OR 'Autism Spectrum Disorder' OR 'Pervasive Developmental Disorder'. RESULTS: The existing evidence does not support the use of neurofeedback in the treatment of ASD. Studies with outcomes in favour of neurofeedback might be showing an improvement in comorbid attention-deficit-hyperactivity disorder symptoms rather than a true improvement in core ASD symptoms. INTERPRETATION: Limitations of this review are those inherent in the studies available, including small sample size, short duration, variable diagnostic criteria, and insufficient control interventions, all causing a lack of generalizability.

 

Weber, E., A. Koberl, et al. (2011). "Predicting successful learning of SMR neurofeedback in healthy participants: methodological considerations." Appl Psychophysiol Biofeedback 36(1): 37-45.

 

Neurofeedback (NF) is a tool that has proven helpful in the treatment of various disorders such as epilepsy or attention deficit disorder (ADHD). Depending on the respective application, a high number of training sessions might be necessary before participants can voluntarily modulate the electroencephalographic (EEG) rhythms as instructed. In addition, many individuals never learn to do so despite numerous training sessions. Thus, we are interested in determining whether or not performance during the early training sessions can be used to predict if a participant will learn to regulate the EEG rhythms. Here, we propose an easy to use, but accurate method for predicting the performance of individual participants. We used a sample set of sensorimotor rhythm (SMR 12-15 Hz) NF training sessions (experiment 1) to predict the performance of the participants of another study (experiment 2). We then used the data obtained in experiment 2 to predict the performance of participants in experiment 1. We correctly predicted the performance of 12 out of 13 participants in the first group and all 14 participants in the second group; however, we were not able to make these predictions before the end of the eleventh training session.

 

Weiskopf, N. (2012). "Real-time fMRI and its application to neurofeedback." Neuroimage 62(2): 682-692.

 

Real-time fMRI (rtfMRI) allows immediate access to experimental results by analyzing data as fast as they are acquired. It was devised soon after the inception of fMRI and has undergone a rapid development since then. The availability of results during the ongoing experiment facilitates a variety of applications such as quality assurance or fast functional localization. RtfMRI can also be used as a brain-computer interface (BCI) with high spatial resolution and whole-brain coverage, overcoming limitations of EEG based BCIs. This review will focus on the application of rtfMRI BCIs to neurofeedback, i.e., the online feedback of the blood oxygen level dependent (BOLD) response. I will motivate its development and place its beginnings into the contemporary scientific context by providing an account of our early work at the University of Tubingen, followed by a review of the accomplishments and the current state of rtfMRI neurofeedback. RtfMRI neurofeedback has been used to train self-regulation of the local BOLD response in various different brain areas and to study consequential behavioral effects. Behavioral effects such as modulation of pain, reaction time, linguistic or emotional processing have been shown in healthy and/or patient populations. RtfMRI neurofeedback presents a new paradigm for studying the relation between brain behavior and physiology, because the latter can be regarded as the independent variable (unlike in conventional neuroimaging studies where behavior is the independent variable). The initial results in patient populations improving pain, tinnitus, depression or modulating perception in schizophrenia are encouraging and merit further controlled clinical studies.

 

Zhang, X., T. J. Ross, et al. (2011). "Single subject task-related BOLD signal artifact in a real-time fMRI feedback paradigm." Hum Brain Mapp 32(4): 592-600.

 

Real-time functional magnetic resonance imaging (rtfMRI) has been proposed as a method of providing feedback to develop a participant's ability to control his or her own neuronal activity. However, this BOLD signal is vulnerable to contamination from nonneuronal sources that can also be shaped by the feedback provided. Here we illustrate an artifact found while training participants to control signal from an ROI in the insula. As the artifact was directly behind the eye and the experiment used an echo-planar imaging (EPI) sequence with phase encoding direction that included the orbits and the insula in the same line, we hypothesized that the artifact was due to eye motion. We demonstrate a reduced training effect when eyeball signal is regressed out of the data and reproduce the artifact with block design voluntary eye movement. Further, using independent components analysis on historical data, we find the artifact is common in BOLD data, but typically not task-correlated, even in tasks where one might expect differing amounts of eye movement in the active task blocks. The artifact, thus, does not significantly impact group results in typical fMRI experiments. Finally, we demonstrate this particular artifact can be avoided in rtfMRI experiments by ensuring that the phase encoding direction does not project any eye movement related artifact onto the ROI being used for feedback training. Our findings underscore the importance of taking great care in designing rtfMRI feedback procedures to avoid contamination with nonneuronal sources of BOLD signal alteration.

 

Zoefel, B., R. J. Huster, et al. (2011). "Neurofeedback training of the upper alpha frequency band in EEG improves cognitive performance." Neuroimage 54(2): 1427-1431.

 

In this study, the individually determined upper alpha frequency band in EEG (electroencephalogram) was investigated as a neurofeedback parameter. Fourteen subjects were trained on five sessions within 1 week by means of feedback dependent on the current upper alpha amplitude. On the first and fifth session, cognitive ability was tested by a mental rotation test. As a result, eleven of the fourteen subjects showed significant training success. Individually determined upper alpha was increased independently of other frequency bands. The enhancement of cognitive performance was significantly larger for the neurofeedback group than for a control group who did not receive feedback. Thus, enhanced cognitive control went along with an increased upper alpha amplitude that was found in the neurofeedback group only.

 

Zotev, V., F. Krueger, et al. (2011). "Self-regulation of amygdala activation using real-time FMRI neurofeedback." PLoS One 6(9): e24522.

Real-time functional magnetic resonance imaging (rtfMRI) with neurofeedback allows investigation of human brain neuroplastic changes that arise as subjects learn to modulate neurophysiological function using real-time feedback regarding their own hemodynamic responses to stimuli. We investigated the feasibility of training healthy humans to self-regulate the hemodynamic activity of the amygdala, which plays major roles in emotional processing. Participants in the experimental group were provided with ongoing information about the blood oxygen level dependent (BOLD) activity in the left amygdala (LA) and were instructed to raise the BOLD rtfMRI signal by contemplating positive autobiographical memories. A control group was assigned the same task but was instead provided with sham feedback from the left horizontal segment of the intraparietal sulcus (HIPS) region. In the LA, we found a significant BOLD signal increase due to rtfMRI neurofeedback training in the experimental group versus the control group. This effect persisted during the Transfer run without neurofeedback. For the individual subjects in the experimental group the training effect on the LA BOLD activity correlated inversely with scores on the Difficulty Identifying Feelings subscale of the Toronto Alexithymia Scale. The whole brain data analysis revealed significant differences for Happy Memories versus Rest condition between the experimental and control groups. Functional connectivity analysis of the amygdala network revealed significant widespread correlations in a fronto-temporo-limbic network. Additionally, we identified six regions--right medial frontal polar cortex, bilateral dorsomedial prefrontal cortex, left anterior cingulate cortex, and bilateral superior frontal gyrus--where the functional connectivity with the LA increased significantly across the rtfMRI neurofeedback runs and the Transfer run. The findings demonstrate that healthy subjects can learn to regulate their amygdala activation using rtfMRI neurofeedback, suggesting possible applications of rtfMRI neurofeedback training in the treatment of patients with neuropsychiatric disorders.

 

Miscellaneous

 

Crocetti, A., S. Forti, et al. (2011). "Neurofeedback for subjective tinnitus patients." Auris Nasus Larynx 38(6): 735-738.

 

OBJECTIVE: Previous studies report that enhanced power in the delta range (1.5-4Hz) and reduced power in the alpha frequency band (8-12Hz) were most pronounced in the temporal regions. These studies referred to the 8-12Hz activity as tau activity, and they created a new neurofeedback protocol to treat tinnitus using a temporally generated tau rhythm (8-12Hz) and slow waves in the delta range (3-4Hz) for feedback. This study aims to repeat this protocol and to evaluate its effect on tinnitus. METHODS: Fifteen normal-hearing patients with tinnitus were treated with the neurofeedback protocol. The Tinnitus Handicap Inventory and Visual Analogue Scales were administered before and after treatment and at 1, 3 and 6 months post-treatment. RESULTS: After therapy, all questionnaires scores were significant improved, and the improvements persisted throughout the followup period. Moreover, an increasing trend in the tau/delta ratio was observed; specifically, the trend was more stable respect of the pre-recording measure. However, only in some subjects may the signal alone be enough to develop the correct behaviors. CONCLUSION: Further studies are necessary to characterize the tinnitus subjects who recovered from and adapted to this psychophysical condition and, therefore, responded to neurofeedback therapy.

 

Hammer, B. U., A. P. Colbert, et al. (2011). "Neurofeedback for insomnia: a pilot study of Z-score SMR and individualized protocols." Appl Psychophysiol Biofeedback 36(4): 251-264.

Insomnia is an epidemic in the US. Neurofeedback (NFB) is a little used, psychophysiological treatment with demonstrated usefulness for treating insomnia. Our objective was to assess whether two distinct Z-Score NFB protocols, a modified sensorimotor (SMR) protocol and a sequential, quantitative EEG (sQEEG)-guided, individually designed (IND) protocol, would alleviate sleep and associated daytime dysfunctions of participants with insomnia. Both protocols used instantaneous Z scores to determine reward condition administered when awake. Twelve adults with insomnia, free of other mental and uncontrolled physical illnesses, were randomly assigned to the SMR or IND group. Eight completed this randomized, parallel group, single-blind study. Both groups received fifteen 20-min sessions of Z-Score NFB. Pre-post assessments included sQEEG, mental health, quality of life, and insomnia status. ANOVA yielded significant post-treatment improvement for the combined group on all primary insomnia scores: Insomnia Severity Index (ISI p<.005), Pittsburgh Sleep Quality Inventory (PSQI p<.0001), PSQI Sleep Efficiency (p<.007), and Quality of Life Inventory (p<.02). Binomial tests of baseline EEGs indicated a significant proportion of excessively high levels of Delta and Beta power (p<.001) which were lowered post-treatment (paired z-tests p<.001). Baseline EEGs showed excessive sleepiness and hyperarousal, which improved post-treatment. Both Z-Score NFB groups improved in sleep and daytime functioning. Post-treatment, all participants were normal sleepers. Because there were no significant differences in the findings between the two groups, our future large scale studies will utilize the less burdensome to administer Z-Score SMR protocol.

Moravec, C. S. and M. G. McKee (2011). "Biofeedback in the treatment of heart disease." Cleve Clin J Med 78 Suppl 1: S20-23.

Biofeedback is a method of training subjects to regulate their own physiology using feedback from physiologic sensors connected to an output display. Biofeedback-assisted stress management (BFSM) incorporates the physiologic signals with instructions on stress management. The goal of BFSM training is to give subjects the tools to control their own mental and physiologic reactions, leading to improved health and wellness. In cardiovascular disease, overactivation of the sympathetic component of the autonomic nervous system and psychologic stress together negatively affect quality of life and clinical status. BFSM targets both areas. We hypothesize that this intervention can be used in cardiovascular disease to improve clinical status and quality of life, as well as interfere with disease progression. We are conducting trials of BFSM in heart failure and stable coronary artery disease. Preliminary data suggest that use of BFSM by heart failure patients may actually cause cellular and molecular remodeling of the failing heart in the direction of normal. We are comparing the effects of BFSM with usual care in patients with stable coronary artery disease, testing the hypothesis that the intervention will decrease both sympathetic hyperarousal and activation of the inflammatory cascade. Since heart rate variability is abnormal in both cardiovascular disease and depression, and since BFSM has been successfully used to change heart rate variability, we also expect this intervention to have a positive impact on the depression that often accompanies cardiovascular disease.

Surmeli, T., A. Ertem, et al. (2012). "Schizophrenia and the efficacy of qEEG-guided neurofeedback treatment: a clinical case series." Clin EEG Neurosci 43(2): 133-144.

Schizophrenia is sometimes considered one of the most devastating of mental illnesses because its onset is early in a patient's life and its symptoms can be destructive to the patient, the family, and friends. Schizophrenia affects 1 in 100 people at some point during their lives, and while there is no cure, it is treatable with antipsychotic medications. According to the Clinical Antipsychotic Trials for Interventions Effectiveness (CATIE), about 74% of the patients who have discontinued the first medication prescribed within a year will have a relapse afterward. This shows an enormous need for developing better treatment methods and better ways to manage the disease, since current therapies do not have sufficient impact on negative symptoms, cognitive dysfunction, and compliance to treatment. In this clinical case series, we investigate the efficacy of quantitative electroencephalography (qEEG)-guided neurofeedback (NF) treatment in this population, and whether this method has an effect on concurrent medical treatment and on the patients. Fifty-one participants (25 males and 26 females) ranging from 17 to 54 years of age (mean: 28.82 years and SD: 7.94 years) were included. Signed consent was received from all patients. Most of the participants were previously diagnosed with chronic schizophrenia, and their symptoms did not improve with medication. All 51 patients were evaluated using qEEG, which was recorded at baseline and following treatment. Before recording the qEEG, participants were washed out for up to 7 half-lives of the medication. After Food and Drug Administration (FDA)-approved Nx-Link Neurometric analysis, qEEGs suggested a diagnosis of chronic schizophrenia for all participants. This was consistent with the clinical judgment of the authors. The participants' symptoms were assessed by means of the Positive and Negative Syndrome Scale (PANSS). Besides the PANSS, 33 out of 51 participants were also evaluated by the Minnesota Multiphasic Personality Inventory (MMPI) and the Test of Variables of Attention (TOVA), both at baseline and following treatment. Each participant was prescribed an NF treatment protocol based on the results of their qEEG neurometric analysis. Each session was 60 minutes in duration, with 1 to 2 sessions per day. When 2 sessions were administered during a single day, a 30-minute rest was given between the sessions. Changes in the PANSS, MMPI, and TOVA were analyzed to evaluate the effectiveness of NF treatment. The mean number of sessions completed by the participants was 58.5 sessions within 24 to 91 days. Three dropped out of treatment between 30 and 40 sessions of NF, and one did not show any response. Of the remaining 48 participants 47 showed clinical improvement after NF treatment, based on changes in their PANSS scores. The participants who were able to take the MMPI and the TOVA showed significant improvements in these measures as well. Forty were followed up for more than 22 months, 2 for 1 year, 1 for 9 months, and 3 for between 1 and 3 months after completion of NF. Overall NF was shown to be effective. This study provides the first evidence for positive effects of NF in schizophrenia.

 

Virginia. Special Advisory Commission on Mandated Health Insurance Benefits. (2001). Mandated coverage for training and education in the use of EEG biofeedback equipment and techniques : report of the Special Advisory Commission on Mandated Health Insurance Benefits to the Governor and the General Assembly of Virginia. Richmond (P.O. Box 36147, Richmond 23235), Commonwealth of Virginia.

 

 

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