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Predicting Successful Learning of SMR Neurofeedback in Healthy Participants: Methodological Considerations
Abstract
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.
... One potential source of drawback is the general ability of an individual to modify their cortical activity, which is referred to as the inefficacy problem (The inefficacy problem is apparent in both EEG-and fMRI-based NFB; yet rooted in diverse technical approaches and difficulties. Gevensleben et al., 2009;Weber et al., 2011;Huster et al., 2014;Rogala et al., 2016;Alkoby et al., 2018). This failure to control has been described in numerous NFB trials and other brain-computer interface (BCI) applications (for a review, see Alkoby et al., 2018). ...
... Further factors in the design of the training protocol (e.g., duration of each training and training schedule), and the NFB learning strategy Witte et al., 2013) may contribute to overall NFB success. Indeed, the evaluation of early training sessions can be used to predict future training progress (Weber et al., 2011;Enriquez-Geppert et al., 2013). In addition to those already mentioned, Weber et al. (2020) have provided an extensive summary of predictors of NFB training outcome in their systematic review. ...
... Our findings are also in line with NFB research that has indicated large intra-individual differences in EEG patterns Riha et al., 2020) and training trajectories (Riha et al., 2021). Lastly, we found that a certain number of individuals were successful in modifying their EEG activity (Responders), a finding consistent with current literature (Weber et al., 2011;Kouijzer et al., 2013;Enriquez-Geppert et al., 2014;Alkoby et al., 2018). ...
The widespread understanding that chronic tinnitus is a heterogeneous phenomenon with various neural oscillatory profiles has spurred investigations into individualized approaches in its treatment. Neurofeedback, as a non-invasive tool for altering neural activity, has become increasingly popular in the personalized treatment of a wide range of neuropsychological disorders. Despite the success of neurofeedback on the group level, the variability in the treatment efficacy on the individual level is high, and evidence from recent studies shows that only a small number of people can effectively modulate the desired aspects of neural activity. To reveal who may be more suitable, and hence benefit most from neurofeedback treatment, we classified individuals into unobserved subgroups with similar oscillatory trajectories during the treatment and investigated how subgroup membership was predicted by a series of characteristics. Growth mixture modeling was used to identify distinct latent subgroups with similar oscillatory trajectories among 50 individuals suffering from chronic subjective tinnitus (38 male, 12 female, mean age = 47.1 ± 12.84) across 15 neurofeedback training sessions. Further, the impact of characteristics and how they predicted the affiliation in the identified subgroups was evaluated by including measures of demographics, tinnitus-specific (Tinnitus Handicap Inventory) and depression variables, as well as subjective quality of life subscales (World Health Organization—Quality of Life Questionnaire), and health-related quality of life subscales (Short Form-36) in a logistic regression analysis. A latent class model could be fitted to the longitudinal data with a high probability of correctly classifying distinct oscillatory patterns into 3 different groups: non-responder (80%), responder (16%), and decliner (4%). Further, our results show that the health-related wellbeing subscale of the Short Form-36 questionnaire was differentially associated with the groups. However, due to the small sample size in the Responder group, we are not able to provide sufficient evidence for a distinct responder profile. Nevertheless, the identification of oscillatory change-rate differences across distinct groups of individuals provides the groundwork from which to tease apart the complex and heterogeneous oscillatory processes underlying tinnitus and the attempts to modify these through neurofeedback. While more research is needed, our results and the analytical approach presented may bring clarity to contradictory past findings in the field of tinnitus research, and eventually influence clinical practice.
... For instance, a neurofeedback training protocol that aimed to improve WM ability by increasing upper alpha power indicated that three of nine participants failed to control their alpha power after several training sessions (Escolano et al., 2011). Moreover, during neurofeedback training to modulate sensorimotor rhythm, approximately half of the participants did not learn to regulate their own brain activities even after numerous training sessions (Weber et al., 2011). ...
... For instance, alpha powers in the eyes-closed and eyes-open resting state before neurofeedback training were significantly correlated with successful EEG learning (Wan et al., 2014). Another study found that an individual's ability to modulate sensorimotor rhythm in early neurofeedback training sessions predicted later neurofeedback training efficacy (Weber et al., 2011). Thus, even if the psychological state is similar among trainees, different functional brain characteristics might affect the efficacy of neurofeedback training. ...
... In other words, the sensory modality dominance is a more crucial factor than the individual learning ability, as the individual brain characteristics determine the neurofeedback training efficacy. When not only neurophysiological factors such as alpha power or sensorimotor rhythm (Weber et al., 2011;Wan et al., 2014) but also modality dominance are used to characterize the cognitive traits of an individual, it is possible to predict neurofeedback training efficacy more accurately. Note that we confirmed that 75% of participants in the Real group showed the same sensory modality dominance between Pre-and Post-WM tasks (i.e., tactile or visual dominance was maintained), and the other few participants showed different dominance (tactile changed to visual in one participant and visual changed to tactile in four participants). ...
Neurofeedback is a neuromodulation technique used to improve brain function by self-regulating brain activity. However, the efficacy of neurofeedback training varies widely between individuals, and some participants fail to self-regulate brain activity. To overcome intersubject variation in neurofeedback training efficacy, it is critical to identify the factors that influence this type of neuromodulation. In this study, we considered that individual differences in cognitive ability may influence neurofeedback training efficacy and aimed to clarify the effect of individual working memory (WM) abilities, as characterized by sensory modality dominance, on neurofeedback training efficacy in healthy young adults. In particular, we focused on the abilities of individuals to retain internal (tactile or somatosensory) or external (visual) body information in their WM. Forty participants performed functional near-infrared spectroscopy-based neurofeedback training aimed at producing efficient and lower-level activity in the bilateral dorsolateral prefrontal cortex and frontopolar cortex. We carried out a randomized, sham-controlled, double-blind study that compared WM ability before and after neurofeedback training. Individual WM ability was quantified using a target searching task that required the participants to retain spatial information presented as vibrotactile or visual stimuli. Participants who received feedback information based on their own prefrontal activity showed gradually decreasing activity in the right prefrontal area during the neurofeedback training and demonstrated superior WM ability during the target searching task with vibrotactile stimuli compared with the participants who performed dummy neurofeedback training. In comparison, left prefrontal activity was not influenced by the neurofeedback training. Furthermore, the efficacy of neurofeedback training (i.e., lower right prefrontal activity and better searching task performance) was higher in participants who exhibited tactile dominance rather than visual dominance in their WM. These findings indicate that sensory modality dominance in WM may be an influential neurophysiological factor in determining the efficacy of neurofeedback training. These results may be useful in the development of neurofeedback training protocols tailored to individual needs.
... Gaining considerable long-lasting control on brain activity through neurofeedback requires a high number of training sessions, leading to high temporal, financial, and staff costs. Besides, previous studies re-vealed that a non-negligible proportion of participants (estimated 10%-50%) fail to gain significant control over their brain function through neurofeedback, even after several training sessions (Blankertz et al., 2010;Drechsler et al., 2007;Hammer et al., 2012;Hanslmayr, Sauseng, Doppelmayr, Schabus, & Klimesch, 2005;Lubar, Swartwood, Swartwood, & O'Donnell, 1995;Neumann & Birbaumer, 2003;Weber, Köberl, Frank, & Doppelmayr, 2011). This phenomenon, first seen in Brain-Computer Interface (BCI) research, is called BCI-illiteracy (Blankertz et al., 2010;Kober et al., 2013; or BCI-inefficiency (Hammer et al., 2012;Kübler, Blankertz, Müller, & Neuper, 2011) in the literature, and has been demonstrated for both healthy and unhealthy participants, as for all EEG training features. ...
... 1. Psychological/neuropsychological traits (Burde & Blankertz, 2006;Daum et al., 1993;Drechsler et al., 2007;Hammer et al., 2012;Nijboer, Birbaumer, & Kübler, 2010;Witte et al., 2013). riquez-Geppert et al., 2013;Halder et al., 2013;Ninaus et al., 2015); 3. Brain neurophysiological parameters in the form of brain activity (Blankertz et al., 2010;Nan, Wan, Vai, & Da Rosa, 2015;Wan, Nan, Vai, & Rosa, 2014); 4. Neurofeedback early training performance (Kübler, Neumann, Wilhelm, Hinterberger, & Birbaumer, 2004;Neumann & Birbaumer, 2003;Weber et al., 2011). ...
... To solve the BCI-illiteracy problem in neurofeedback applications, previous studies proposed some psychological/ neuropsychological (Burde & Blankertz, 2006;Daum et al., 1993;Hammer et al., 2012;Nijboer et al., 2010;Witte et al., 2013), neuroanatomical (Enriquez-Geppert et al., 2013Halder et al., 2013), and neurophysiological (Blankertz et al., 2010) factors besides neurofeedback initial performance (Kübler et al., 2004;Neumann & Birbaumer, 2003;Weber et al., 2011) as the predictor of individuals' neurofeedback trainability. The mental strategy used by an individual during a neurofeedback session is another factor that influences on gaining brain self-control (Angelakis et al., 2007;Birbaumer et al., 2013;Kober et al., 2013;Nan et al., 2012;Neumann & Birbaumer, 2003;Rubik, 2011;Witte et al., 2013). ...
Introduction: Regarding the neurofeedback training process, previous studies indicate that 10%-50% of subjects cannot gain control over their brain activity even after repeated training sessions. This study is conducted to overcome this problem by investigating inter-individual differences in neurofeedback learning to propose some predictors for the trainability of subjects.
Methods: Eight healthy female students took part in 8 (electroencephalography) EEG neurofeedback training sessions for enhancing EEG gamma power at the Oz channel. We studied participants’ preexisting fluid intelligence and EEG frequency sub-bands’ power during 2-min eyes-closed rest and a cognitive task as psychological and neurophysiological factors, concerning neurofeedback learning performance. We also assessed the self-reports of participants about mental strategies used by them during neurofeedback to identify the most effective successful strategies.
Results: The results revealed that a significant percentage of individuals (25% in this study) cannot learn how to control their brain gamma activity using neurofeedback. Our findings suggest that fluid intelligence, gamma power during a cognitive task, and alpha power at rest can predict gamma-enhancing neurofeedback performance of individuals. Based on our study, neurofeedback learning is a form of implicit learning. We also found that learning without a user’s mental efforts to find out successful mental strategies, in other words, unconscious learning, lead to more success in gamma-enhancing neurofeedback.
Conclusion: Our results may improve gamma neurofeedback efficacy for further clinical usage and studies by giving insight about both non-trainable individuals and effective mental strategies.
... The validity of NF training protocol was performed based on three criteria: trainability, independence and interpretability. The evaluation of learning ability with more than one criteria has also been assessed in other studies [52][53][54]. ...
... Although NF training has shown potential benefit in different applications, learning ability is varied among individuals. Existing studies [19,44,46,53,63,64] show that not all participants managed to successfully modulate training parameters. The number of participants classified as non-learners in these studies [19,44,46,53,63,64] are in the range of twenty percent to fifty percent. ...
... Existing studies [19,44,46,53,63,64] show that not all participants managed to successfully modulate training parameters. The number of participants classified as non-learners in these studies [19,44,46,53,63,64] are in the range of twenty percent to fifty percent. Therefore, the learning indices of NF training are discussed for each patient separately in the presented study. ...
Neurofeedback (NF) training has been used for the treatment of neuropathic pain. This paper presents the results of assessment of the learning ability of five patients having neuropathic pain. The following two types of baselines were adopted: Baseline 1 refers to power on Day 1 in PreNF state; and Baseline 2 refers to power recorded on each training day in PreNF state. The result of the study demonstrated that not only the baseline its selection is also important to demonstrate the validity of training protocol. It was also found that Baseline 2 can be used to define cut-off time for training (when training should be stopped). All five patients can be classified as learner and alpha band was found to be most relevant for NF training.
... performance (Nijboer et al., 2008(Nijboer et al., , 2010, while frustration and overconfidence can impair it (Guger et On the neurophysiological side, several biomarkers have been proposed to predict BCI aptitude. Resting-state EEG markers-particularly higher alpha power-are consistently associated with better MI control, whereas BCI-illiterate individuals often show increased theta and decreased alpha activity (Blankertz et 17 showed that early slow cortical potentials (SCP) modulation correlated with later performance in severely paralyzed patients, and Weber et al. (2011) 19 found that sensory motor rhythms (SMR) modulation success in early sessions predicted long-term outcomes, although reliable prediction required at least eleven sessions. ...
... Although not shown here, we also tested additional frequency bands, including the alpha band [8-12 Hz], beta band [12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28][29][30], low gamma band , and theta band [3][4][5][6][7][8]. In both the alpha and beta bands, the results retained the key characteristics observed in the broad band, although the broad frequency range provided a more comprehensive and integrative view across the various analyses performed. ...
Brain-Computer Interfaces (BCIs) based on motor imagery (MI) hold promise for restoring control in individuals with motor impairments. However, up to 30% of users remain unable to effectively use BCIs: a phenomenon termed BCI inefficiency. This study addresses a major limitation in current BCI training protocols: the use of fixed-length training paradigms that ignore individual learning variability. We propose a novel approach that leverages neuronal avalanches, spatiotemporal cascades of brain activity, as biomarkers to characterize and predict user-specific learning mechanism. Using electroencephalography (EEG) data collected across four MI-BCI training sessions in 20 healthy participants, we extracted two features: avalanche length and activations. These features revealed significant training and task-condition effects, particularly in later sessions. Crucially, changes in these features across sessions (avalanche length and activations) correlated significantly with BCI performance and enabled prediction of future BCI success via longitudinal Support Vector Regression and Classification models. Predictive accuracy reached up to 91%, with notable improvements after spatial filtering based on selected regions of interest. These findings demonstrate the utility of neuronal avalanche dynamics as robust biomarkers for BCI training, supporting the development of personalized protocols aimed at mitigating BCI illiteracy.
... ADHD affects the limbic area, marking it as one of the regions impacted in the brain. Additionally, research on brain electrical activity has shown reduced activity in the frontal lobe to specific visual stimuli among individuals with this disorder [6][7][8][9][10][11]. Several studies have consistently identified several key anatomical differences in the brains of individuals with ADHD compared with those in healthy people. ...
... Among the regions impacted by these abnormalities is the brain's temporal surface, which plays a role in language functions and is typically more developed in the left hemisphere in individuals without these defects. However, individuals with this disorder frequently display symmetrical sizes in both hemispheres [7]. Furthermore, electroencephalogram (EEG) activity patterns in children with this disorder are unconventional, marked by an increased occurrence of short amplitude brain signals in the frontal brain regions, indicating delayed development in the brain structures vital for attention and information organization. ...
Background
Neurofeedback is a non-invasive brain training technique used to enhance and treat hyperactivity disorder by altering the patterns of brain activity. Nonetheless, the extent of enhancement by neurofeedback varies among individuals/patients and many of them are irresponsive to this treatment technique. Therefore, several studies have been conducted to predict the effectiveness of neurofeedback training including the theta/beta protocol with a specific emphasize on slow cortical potential (SCP) before initiating treatment, as well as examining SCP criteria according to age and sex criteria in diverse populations. While some of these studies failed to make accurate predictions, others have demonstrated low success rates. This study explores functional connections within various brain lobes across different frequency bands of electroencephalogram (EEG) signals and the value of phase locking is used to predict the potential effectiveness of neurofeedback treatment before its initiation.
Methods
This study utilized EEG data from the Mendelian database. In this database, EEG signals were recorded during neurofeedback sessions involving 60 hyperactive students aged 7–14 years, irrespective of sex. These students were categorized into treatable and non-treatable. The proposed method includes a five-step algorithm. Initially, the data underwent preprocessing to reduce noise using a multi-stage filtering process. The second step involved extracting alpha and beta frequency bands from the preprocessed EEG signals, with a particular emphasis on the EEG recorded from sessions 10 to 20 of neurofeedback therapy. In the third step, the method assessed the disparity in brain signals between the two groups by evaluating functional relationships in different brain lobes using the phase lock value, a crucial data characteristic. The fourth step focused on reducing the feature space and identifying the most effective and optimal electrodes for neurofeedback treatment. Two methods, the probability index (p-value) via a t-test and the genetic algorithm, were employed. These methods showed that the optimal electrodes were in the frontal lobe and central cerebral cortex, notably channels C3, FZ, F4, CZ, C4, and F3, as they exhibited significant differences between the two groups. Finally, in the fifth step, machine learning classifiers were applied, and the results were combined to generate treatable and non-treatable labels for each dataset.
Results
Among the classifiers, the support vector machine and the boosting method demonstrated the highest accuracy when combined. Consequently, the proposed algorithm successfully predicted the treatability of individuals with hyperactivity in a short time and with limited data, achieving an accuracy of 90.6% in the neurofeedback method. Additionally, it effectively identified key electrodes in neurofeedback treatment, reducing their number from 32 to 6.
Conclusions
This study introduces an algorithm with a 90.6% accuracy for predicting neurofeedback treatment outcomes in hyperactivity disorder, significantly enhancing treatment efficiency by identifying optimal electrodes and reducing their number from 32 to 6. The proposed method enables the prediction of patient responsiveness to neurofeedback therapy without the need for numerous sessions, thus conserving time and financial resources.
... The results of NF training, however, are not always consistent. There is, in fact, a significant part of the population subjected to this treatment who does not seem to benefit from its effects and who does not achieve the required voluntary control of the frequency bands covered by the training, the so-called non-responders (or non-performers or non -regulators; Weber et al., 2010;Alkoby et al., 2018). In this regard, two categories of predictive factors of the ineffectiveness of NF training have been identified: psychological predictors and neurophysiological predictors. ...
... As regard neurophysiological predictors, Wan et al. (2014) showed that alpha wave amplitude in resting condition before NF training significantly correlated with success in EEG learning. Also confirmed by other studies (e.g., Kotchoubey et al., 1999;Neumann and Birbaumer, 2003;Weber et al., 2010), this observation has led to considering individual differences in the amplitude of the different frequency bands as a factor not to be underestimated within NF training. What we therefore asked ourselves is whether a personalization of NF procedures, in which the characteristics of the training are adapted to the individual, can transform non-responders into responders. ...
In recent years, the scientific community has begun tо explore the efficacy оf an integrated neurofeedback + biofeedback approach іn various conditions, both pathological and non-pathological. Although several studies have contributed valuable insights into its potential benefits, this review aims tо further investigate its effectiveness by synthesizing current findings and identifying areas for future research. Our goal іs tо provide a comprehensive overview that may highlight gaps іn the existing literature and propose directions for subsequent studies. The search for articles was conducted on the digital databases PubMed, Scopus, and Web of Science. Studies to have used the integrated neurofeedback + biofeedback approach published between 2014 and 2023 and reviews to have analyzed the efficacy of neurofeedback and biofeedback, separately, related to the same time interval and topics were selected. The search identified five studies compatible with the objectives of the review, related to several conditions: nicotine addiction, sports performance, Autism Spectrum Disorder (ASD), and Attention Deficit Hyperactivity Disorder (ADHD). The integrated neurofeedback + biofeedback approach has been shown to be effective in improving several aspects of these conditions, such as a reduction in the presence of psychiatric symptoms, anxiety, depression, and withdrawal symptoms and an increase in self-esteem in smokers; improvements in communication, imitation, social/cognitive awareness, and social behavior in ASD subjects; improvements in attention, alertness, and reaction time in sports champions; and improvements in attention and inhibitory control in ADHD subjects. Further research, characterized by greater methodological rigor, is therefore needed to determine the effectiveness of this method and the superiority, if any, of this type of training over the single administration of either. This review іs intended tо serve as a catalyst for future research, signaling promising directions for the advancement оf biofeedback and neurofeedback methodologies.
... In short, brain waves are patterns of electrical activity that can be recognized by their amplitudes (the power of the waves measured in microvolts) and frequencies (how fast the waves oscillate measured by the number of waves per second). Based on their frequency, brain waves are categorized into delta (less than 4 Hz), which are observed in the EEG signal when a person is asleep; theta (4-8 Hz), observed when the person is sleepy; alpha (8-13 Hz), usually seen when the person is awake but relaxed; beta (13)(14)(15)(16)(17)(18)(19)(20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30), present when individuals are alert; and gamma (30-100 Hz), typically observed when a person is trying to solve a problem. Moreover, these frequency components have subsets, such as the sensorimotor rhythm (SMR) frequency bands (12)(13)(14)(15), which are categorized by low beta waves, observed when the person is alert but physically relaxed [23]. ...
... The most commonly used training is the frequency training, which aims to change the power ratio of the EEG frequency bands [24]. Among the most well-studied and used frequency training protocols, are the EEG alpha/theta ratio training and the enhancement of the SMR frequency (12)(13)(14)(15) [25]. Secondly, there is the coherence training, which focuses on the coherence or the degree of correlation between two or more brain regions. ...
Purpose of Review
Biofeedback is a promising technique that has been used as a treatment tool for different psychological disorders. In this regard, central (neurofeedback) and peripheral psychophysiological signals are presented as comprehensible stimuli with the aim of training specific processes. This review summarizes recent evidence about its use for the treatment of impulsivity-related processes in addictive disorders.
Recent Findings
Neurofeedback (NFB) protocols, based on electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), have focused on substance use disorders. Biofeedback protocols using peripheral measures have been mainly based on heart rate variability and focused on behavioral addictions. EEG-NFB reported good results in the reduction of hyperarousal, impulsivity and risk taking in alcohol use disorder, and decreased rates of smoking and less craving in nicotine addiction. In fMRI-NFB, effective NFB performance has been related with better clinical outcomes in substance use disorders; however, its implication for treatment is still unclear. Heart rate variability biofeedback results are scarce, but some interventions have been recently designed aimed at treating behavioral addictions.
Summary
In addictive disorders, biofeedback interventions for impulsivity-related processes have shown promising results, although the literature is still scarce. Further research should aim at proving the effectiveness of biofeedback protocols as a treatment option for impulsivity in addictive disorders.
... The choice of how a sensory stimulus is presented to a user must consider the clinical condition and the best way to represent the physiological information being trained, that is, feedback must be contingent (Sitaram et al. 2017). A stimulus can be presented isolated, independently, or integrated with other stimuli, such as in a video game, for instance (Giggins et al. 2013, Caria et al. 2007Donovan et al. 2016;Shokur et al. 2016;Weber et al. 2011). ...
... In general, for visual stimulation, it is presented to the user as a specific visual target, as a point or line, that must be reached using a cursor represented by another point or line (Wolpaw et al. 1991;Zapała et al. 2017). It is common to use bars to represent the effort of the user (Caria et al. 2007;Weber et al. 2011), for instance, more concentrated or contracted muscles will increase the size of the bar. The hot-cold color intensity of an image is also often used to represent the modulation of brain activity training in a neurofeedback protocol (Hwang et al. 2009). ...
For a better rescuing of people with disabilities, it is crucial the development of new assistive technologies and therapeutic methods to rehabilitate people with some disabilities to integrate them to a complete social life. A very promising tool is the physiological self-regulation protocols based on biofeedback training. Biofeedback protocols are based on the premise that it is possible to learn how to self-modulate specific aspects of the body’s physiological activity. A biofeedback system is composed of input physiological information and output sensorial stimuli information in a real-time closed-loop process that allows patients to modulate a target physiological (dys)function. The application of biofeedback protocols has been widely studied and used in different clinical practices such as orthopedic, neurological, physiological, and cognitive conditions. This review focuses on the main aspects concerning the system arrangement and protocols of stimulation in biofeedback approaches, from its basic principles of operation to its clinical application in different contexts, with emphasis on sensorimotor and cognitive deficits.KeywordsSelf-regulationBiofeedbackNeurofeedbackBrain machine interfaceBrain computer interfaceRehabilitation
... While NFB works on the principle of self-regulation of endogenous EEG activity (Enriquez-Geppert et al., 2017;Ros et al., 2020), tACS is based on delivering external electric fields capable of interacting with an ongoing EEG activity (Liu et al., 2018;Vöröslakos et al., 2018). Despite the vast differences in mechanisms of action of tACS and NFB, according to the thorough research, both methods can successfully modulate various EEG bands (Lubar, 1997;Weber et al., 2011;Staufenbiel et al., 2014;Witkowski et al., 2016;Violante et al., 2017;Wischnewski and Schutter, 2017;Pimenta et al., 2018;Tseng et al., 2018;Abellaneda-Pérez et al., 2020). Both neuromodulatory methods have been also investigated in their ability to improve various brain functions such as motor performance (Joundi et al., 2012;Ros et al., 2014b;Scharnowski et al., 2015;Moisa et al., 2016;Guerra et al., 2018Guerra et al., , 2019Bologna et al., 2019), memory processes (Alexeeva et al., 2012;Polanía et al., 2012;Violante et al., 2017;Dobrakowski and Łebecka, 2020), attention (Escolano et al., 2014;Hopfinger et al., 2017;Berger and Davelaar, 2018;Deiber et al., 2020), creativity (Gruzelier, 2009;Agnoli et al., 2018;Di Bernardi Luft et al., 2018), emotional regulation (Johnston et al., 2010;Bramson et al., 2020), etc. (Hohn et al., 2019;Prim et al., 2019). ...
... In the realm of EEG biofeedback studies, a unidirectional and bidirectional training protocol is used (Dempster and Vernon, 2009;Friedrich et al., 2015). The unidirectional protocol refers to the NFB protocol aimed at modulating a single-frequency bandwidth (Dempster and Vernon, 2009;Weber et al., 2011). Unidirectional protocols can be single frequency (e.g., uptraining of alpha amplitude) or multifrequency (e.g., downregulation of beta and gamma amplitude) (Vanneste et al., 2016). ...
Transcranial alternating current stimulation (tACS) and neurofeedback (NFB) are two different types of non-invasive neuromodulation techniques, which can modulate brain activity and improve brain functioning. In this review, we compared the current state of knowledge related to the mechanisms of tACS and NFB and their effects on electroencephalogram (EEG) activity (online period/stimulation period) and on aftereffects (offline period/post/stimulation period), including the duration of their persistence and potential behavioral benefits. Since alpha bandwidth has been broadly studied in NFB and in tACS research, the studies of NFB and tACS in modulating alpha bandwidth were selected for comparing the online and offline effects of these two neuromodulation techniques. The factors responsible for variability in the responsiveness of the modulated EEG activity by tACS and NFB were analyzed and compared too. Based on the current literature related to tACS and NFB, it can be concluded that tACS and NFB differ a lot in the mechanisms responsible for their effects on an online EEG activity but they possibly share the common universal mechanisms responsible for the induction of aftereffects in the targeted stimulated EEG band, namely Hebbian and homeostatic plasticity. Many studies of both neuromodulation techniques report the aftereffects connected to the behavioral benefits. The duration of persistence of aftereffects for NFB and tACS is comparable. In relation to the factors influencing responsiveness to tACS and NFB, significantly more types of factors were analyzed in the NFB studies compared to the tACS studies. Several common factors for both tACS and NFB have been already investigated. Based on these outcomes, we propose several new research directions regarding tACS and NFB.
... Neurofeedback (NF) is an electroencephalographic technique that uses operant conditioning to train, in a nonvoluntary manner, the subject's brain activity in terms of EEG metrics (power, amplitude, coherence, and phase) to modulate it towards the normative data in the QEEG database, while the subject receives different visual and/or auditory stimuli (video games and movies) [11,15,23,24]. Real-time NF techniques have shown promise in improving the cognitive performance of patients with LDs, ADHD, and ASD [24][25][26][27][28][29][30]. However, the brain activity metrics in some of these patients (nonresponders) do not seem to improve, even after having several sessions [24][25][26][27][28][29][30] or applying advanced, novel self-regulation training techniques, such as Live Z-Score Training Neurofeedback (LZT-NF). ...
... Real-time NF techniques have shown promise in improving the cognitive performance of patients with LDs, ADHD, and ASD [24][25][26][27][28][29][30]. However, the brain activity metrics in some of these patients (nonresponders) do not seem to improve, even after having several sessions [24][25][26][27][28][29][30] or applying advanced, novel self-regulation training techniques, such as Live Z-Score Training Neurofeedback (LZT-NF). LZT-NF performs real-time QEEG in the form of generating Z-scores as an essential component of the feedback control mechanism. ...
Learning disabilities (LDs) have an estimated prevalence between 5% and 9% in the pediatric population and are associated with difficulties in reading, arithmetic, and writing. Previous electroencephalography (EEG) research has reported a lag in alpha-band development in specific LD phenotypes, which seems to offer a possible explanation for differences in EEG maturation. In this study, 40 adolescents aged 10–15 years with LDs underwent 10 sessions of Live Z-Score Training Neurofeedback (LZT-NF) Training to improve their cognition and behavior. Based on the individual alpha peak frequency (i-APF) values from the spectrogram, a group with normal i-APF (ni-APF) and a group with low i-APF (li-APF) were compared in a pre-and-post-LZT-NF intervention. There were no statistical differences in age, gender, or the distribution of LDs between the groups. The li-APF group showed a higher theta absolute power in P4 (p = 0.016) at baseline and higher Hi-Beta absolute power in F3 (p = 0.007) post-treatment compared with the ni-APF group. In both groups, extreme waves (absolute Z-score of ≥1.5) were more likely to move toward the normative values, with better results in the ni-APF group. Conversely, the waves within the normal range at baseline were more likely to move out of the range after treatment in the li-APF group. Our results provide evidence of a viable biomarker for identifying optimal responders for the LZT-NF technique based on the i-APF metric reflecting the patient’s neurophysiological individuality.
... To advance the use of fMRI-NF as a potential individualised treatment for ADHD, it will be crucial to understand how many of those with ADHD will respond to the treatment, who the responders are, and what distinguishes them from non-responders. Large heterogeneity of NF response has been observed with EEG-NF in both healthy (Dekker, Sitskoorn, Denissen, & van Boxtel, 2014;Enriquez-Geppert et al., 2013;Weber, Koberl, Frank, & Doppelmayr, 2011) and clinical populations, including ADHD patients (Doehnert, Brandeis, Straub, Steinhausen, & Drechsler, 2008;Drechsler et al., 2007;Kotchoubey et al., 1999;Kouijzer, van Schie, Gerrits, Buitelaar, & de Moor, 2013;Liechti et al., 2012;Lubar, Swartwood, Swartwood, & O'Donnell, 1995). A review of 20 EEG-NF studies, which included healthy participants and children with ADHD or Autism Spectrum Disorder (ASD), showed that between 40 -84% of participants were successful NF-regulators (Alkoby, Abu-Rmileh, Shriki, & Todder, 2018). ...
... The aim of the current study was therefore to investigate the relationship between the ability to self-regulate brain activity through fMRI-NF and baseline clinical, cognitive, and neurofunctional measures, based on data from our previously published fMRI-NF study in adolescents with ADHD (Alegria et al., 2017). Evidence from EEG-NF studies has demonstrated that brain function measures predict NF learning both in healthy controls (Nan et al., 2018;Reichert, Kober, Neuper, & Wood, 2015;Wan, Nan, Vai, & Rosa, 2014;Weber et al., 2011) and in ADHD patients (Gevensleben et al., 2009;Okumura et al., 2017;Wangler et al., 2011). We therefore hypothesised that stronger baseline activation of fronto-striatal cognitive control regions in the fMRI stop task would be correlated with better fMRI-NF learning. ...
Functional Magnetic Resonance Imaging Neurofeedback (fMRI-NF) targeting brain areas/networks shown to be dysfunctional by previous fMRI research is a promising novel neurotherapy for ADHD. Our pioneering study in 31 adolescents with ADHD showed that fMRI-NF of the right inferior frontal cortex (rIFC) and of the left parahippocampal gyrus (lPHG) was associated with clinical improvements. Previous studies using electro-encephalography-NF have shown, however, that not all ADHD patients learn to self-regulate, and the predictors of NF self-regulation learning are not presently known. The aim of the current study was therefore to elucidate the potential predictors of fMRI-NF learning by investigating the relationship between fMRI-NF learning and baseline inhibitory brain function during an fMRI stop task, along with clinical and cognitive measures. fMRI-NF learning capacity was calculated for each participant by correlating the number of completed fMRI-NF runs with brain activation in their respective target regions from each run (rIFC or lPHG); higher correlation values were taken as a marker of better (linear) fMRI-NF learning. Linear correlations were then conducted between baseline measures and the participants’ capacity for fMRI-NF learning. Better fMRI-NF learning was related to increased activation in left inferior fronto-striatal regions during the fMRI stop task. Poorer self-regulation during fMRI-NF training was associated with enhanced activation in posterior temporo-occipital and cerebellar regions. Cognitive and clinical measures were not associated with general fMRI-NF learning across all participants. A categorical analysis showed that 48% of adolescents with ADHD successfully learned fMRI-NF and this was also not associated with any baseline clinical or cognitive measures except that faster processing speed during inhibition and attention tasks predicted learning. Taken together, the findings suggest that imaging data are more predictive of fMRI-NF self-regulation skills in ADHD than behavioural data. Stronger baseline activation in fronto-striatal cognitive control regions predicts better fMRI-NF learning in ADHD.
... Those who do not achieve this goal in at least one of the first 3 sessions (first week) will be considered as ''non-performers'' and excluded from the study. Indeed, it has been found that the ability of the subjects to perform well during the first NFB training sessions was predictive of their subsequent performance [128]. The excluded patients will be replaced by other patients and they will not impute the randomization list. ...
... On the other hand, the changes in resting-state EEG will be considered only as a satellite measure in the present study. The association with the clinical analgesic response will be studied, as well as the possibility that the ability of the subjects to modulate their brain activity during the first training sessions might predict the subsequent performance at NFB sessions [128]. ...
Background:
Chronic neuropathic pain associated with peripheral neuropathies cannot be attributed solely to lesions of peripheral sensory axons and likely involves alteration in the processing of nociceptive information in the central nervous system in most patients. Few data are available regarding EEG correlates of chronic neuropathic pain. The fact is that effective cortical neuromodulation strategies to treat neuropathic pain target the precentral cortical region, i.e. a cortical area corresponding to the motor cortex. It is not known how these strategies might modulate brain rhythms in the central cortical region, but it can be speculated that sensorimotor rhythms (SMRs) are modified. Another potent way of modulating cortical rhythms is to use EEG-based neurofeedback (NFB). Rare studies previously aimed at relieving neuropathic pain using EEG-NFB training.
Methods/design:
The objective of this single-centre, single-blinded, randomized controlled pilot study is to assess the value of an EEG-NFB procedure to relieve chronic neuropathic pain in patients with painful peripheral neuropathy. A series of 32 patients will be randomly assigned to one of the two following EEG-NFB protocols, aimed at increasing either the low-β(SMR)/high-β ratio (n=16) or the α(μ)/θ ratio (n=16) at central (rolandic) cortical level. Various clinical outcome measures will be collected before and one week after 12 EEG-NFB sessions performed over 4weeks. Resting-state EEG will also be recorded immediately before and after each NFB session. The primary endpoint will be the change in the impact of pain on patient's daily functioning, as assessed on the Interference Scale of the short form of the Brief Pain Inventory.
Discussion:
The value of EEG-NFB procedures to relieve neuropathic pain has been rarely studied. This pilot study will attempt to show the value of endogenous modulation of brain rhythms in the central (rolandic) region in the frequency band corresponding to the frequency of stimulation currently used by therapeutic motor cortex stimulation. In the case of significant clinical benefit produced by the low-β(SMR)/high-β ratio increasing strategy, this work could pave the way for using EEG-NFB training within the armamentarium of neuropathic pain therapy.
... The smaller bars on the left and right side of the screen showed the power values in the theta and beta frequency range. These two frequency bands were used to assure that patients were not manipulating the SMR amplitude by producing artefacts, e.g., blinking, which would have increased theta power, or tensing their muscles, which would have increased beta power and consequently, also SMR power Weber et al., 2011). One NF training session comprised one baseline run (3 min) and six feedback runs (3 min each) (Fig. 1C). ...
... The theta and beta frequencies, which were used as control frequencies during NF training to prevent patients from producing artifacts by blinking, eye movements, or muscle artifacts Kober et al., 2015b;Weber et al., 2011), did not change in the same linear fashion than SMR power across feedback runs in the responder group (Fig. 2). This indicates that the responder group did not systematically increase artifact activity across the feedback runs to modulate SMR. ...
Objective:
To investigate the effects of EEG-based neurofeedback training, in which one can learn to self-regulate one's own brain activity, on cognitive function in patients with multiple sclerosis (pwMS).
Methods:
Fourteen pwMS performed ten neurofeedback training sessions within 3-4 weeks at home using a tele-rehabilitation system. The aim of the neurofeedback training was to increase voluntarily the sensorimotor rhythm (SMR, 12-15 Hz) in the EEG over central brain areas by receiving visual real-time feedback thereof. Cognitive function was assessed before and after all neurofeedback training sessions using a comprehensive standardized neuropsychological test battery.
Results:
Half of the pwMS (N = 7) showed cognitive improvements in long-term memory and executive functions after neurofeedback training. These patients successfully learned to self-regulate their own brain activity by means of neurofeedback training. The other half of pwMS (N = 7) did neither show any cognitive changes when comparing the pre- and post-assessment nor were they able to modulate their own brain activity in the desired direction during neurofeedback training.
Conclusions:
Data from this interventional study provide first preliminary evidence that successful self-regulation of one's own brain activity may be associated with cognitive improvements in pwMS.
Significance:
These promising results should stimulate further studies. Neurofeedback might be a promising and alternative tool for future cognitive rehabilitation.
... For instance, following upper alpha NFT, two single chronic stroke patients with memory deficits showed memory improvement meanwhile cortical "normalization" was found in a stroke patient with pathological brain activation patterns (3). Compared to traditional rehabilitation, thirty sessions of sensorimotor rhythm (SMR, [12][13][14][15] or mid-beta (15)(16)(17)(18) NFT was more effective to improve concentration and visual perception for the patient with hemi-paralysis from stroke within the previous 3 months to 1 year (4). In summary, previous studies have shown the potential of NFT for cognition rehabilitation in stroke survivors. ...
... The inter-individual differences in neurofeedback learning have also been found in previous work, regardless of the NFT protocol and subject population (16)(17)(18)(19)(20)(21)(22)(23). With regard to stroke patients, Kober et al. (24) which investigated the NFT effects on cognitive functions also found that not all patients could learn to enhance alpha amplitude within and across NFT sessions. ...
Stroke is a debilitating neurological condition which usually results in the abnormal electrical brain activity and the impairment of sensation, motor, or cognition functions. In this context, neurofeedback training, i.e., a non-invasive and relatively low cost technique that contributes to neuroplasticity and behavioral performance, might be promising for stroke rehabilitation. We intended to explore neurofeedback training on a 63-year-old male patient and a 77-year-old female patient with chronic stroke. Both of them had suffered from an ischemic stroke for rather long period (more than 3 years) and could not gain further improvement by traditional therapy. The neurofeedback training was designed to enhance alpha activity by 15 sessions distributed over 2 months, for the purpose of overall cognitive improvement and hopefully also motor function improvement for the female patient. We found that the two patients showed alpha enhancement during NFT compared to eyes open baseline within most sessions. Furthermore, both patients reduced their anxiety and depression level. The male patient showed an evolution in speech pattern in terms of naming, sentences completion and verbal fluency, while the female patient improved functionality of the march. These results suggested that alpha neurofeedback training could provide a spectrum of improvements, providing new hope for chronic stroke patients who could not gain further improvements through traditional therapies.
... Common neurofeedback protocols range from 12 to 30 sessions (see, for review, Fielenbach et al., 2018); hence, a decrease in mean magnitude of the targeted frequency band might take more than eight sessions to manifest. However, previous research has shown that performance in early neurofeedback training sessions predicts performance in later training sessions (Weber, Köberl, Frank, & Doppelmayr, 2011). Hence, more training sessions may not necessarily result in more clinically relevant results. ...
... Some studies have suggested that a pattern of EEG-learning should be observable over every session of neurofeedback training (Weber et al., 2011). In our study, only Patient 1 showed a significant change in EEG magnitude, but this change was not observable over every session, as the change in SMR magnitude correlated only by trend highest with SMA Model 2, indicating a stable number of first sessions and an increase later in the intervention. ...
Electroencephalographic (EEG) neurofeedback could be a promising treatment for
forensic psychiatric patients. Increasing evidence shows some patients are unable to
regulate cortical activity. Before neurofeedback can be applied successfully, research
is needed to investigate the interpersonal mechanisms responsible for patients’
ability to respond to neurofeedback. A single-case experimental design allows
for close monitoring of individual patients, providing valuable information about
patients’ response to the intervention and the time frame in which changes in clinical
symptoms can be observed. Four patients with Diagnostic and Statistical Manual of
Mental Disorders (4th ed., text rev.; DSM-IV-TR) substance use disorder and various
comorbidities participated in a sham-controlled clinical case study. Self-report level of
impulsivity and craving were assessed. Results indicate that one patient showed more
improvements on behavioral measures after the neurofeedback training than did the
others. This patient reported less impulsivity and reduced levels of self-reported
craving. However, these findings could not be attributed to the neurofeedback
intervention. The findings suggest that there is insufficient evidence for the beneficial
effects of a theta/sensorimotor rhythm (SMR) neurofeedback intervention on measures of impulsivity and craving, and that there may be great interindividual
differences in patients’ ability to regulate cortical activity.
... Common neurofeedback protocols range from 12 to 30 sessions (see, for review, Fielenbach et al., 2018); hence, a decrease in mean magnitude of the targeted frequency band might take more than eight sessions to manifest. However, previous research has shown that performance in early neurofeedback training sessions predicts performance in later training sessions (Weber, Köberl, Frank, & Doppelmayr, 2011). Hence, more training sessions may not necessarily result in more clinically relevant results. ...
... Some studies have suggested that a pattern of EEG-learning should be observable over every session of neurofeedback training (Weber et al., 2011). In our study, only Patient 1 showed a significant change in EEG magnitude, but this change was not observable over every session, as the change in SMR magnitude correlated only by trend highest with SMA Model 2, indicating a stable number of first sessions and an increase later in the intervention. ...
Electroencephalographic (EEG) neurofeedback could be a promising treatment for forensic psychiatric patients. Increasing evidence shows some patients are unable to regulate cortical activity. Before neurofeedback can be applied successfully, research is needed to investigate the interpersonal mechanisms responsible for patients’ ability to respond to neurofeedback. A single-case experimental design allows for close monitoring of individual patients, providing valuable information about patients’ response to the intervention and the time frame in which changes in clinical symptoms can be observed. Four patients with Diagnostic and Statistical Manual of Mental Disorders (4th ed., text rev.; DSM-IV-TR) substance use disorder and various comorbidities participated in a sham-controlled clinical case study. Self-report level of impulsivity and craving were assessed. Results indicate that one patient showed more improvements on behavioral measures after the neurofeedback training than did the others. This patient reported less impulsivity and reduced levels of self-reported craving. However, these findings could not be attributed to the neurofeedback intervention. The findings suggest that there is insufficient evidence for the beneficial effects of a theta/sensorimotor rhythm (SMR) neurofeedback intervention on measures of impulsivity and craving, and that there may be great interindividual differences in patients’ ability to regulate cortical activity.
... The success rate after 3 sessions of NF is in line with the literature [60][61][62][63][64], with 63% of participants enhancing IA and 79% -suppressing it. Nonetheless, only 50% of upregulation participants specifically enhanced mu rhythm, as found from CSD-EEG analysis. ...
Objective: The study objective was to characterise indices of learning and patterns of connectivity in two neurofeedback (NF) paradigms that modulate mu oscillations in opposite directions, and the relationship with change in excitability of the corticospinal tract (CST).
Approach: Forty-three healthy volunteers participated in 3 NF sessions for upregulation (N=24) or downregulation (N=19) of individual alpha (IA) power at central location Cz. Brain signatures from multichannel electroencephalogram (EEG) were analysed, including oscillatory (power, spindles), non-oscillatory components (Hurst exponent), and effective connectivity (Directed Transfer Function) of participants who were successful at enhancing or suppressing IA power at Cz. CST excitability was studied through leg motor-evoked potential before and after the last NF session. We assessed whether participants modulated widespread alpha or central mu rhythm through the use of current source density derivation (CSD), and related the change in power in mu and upper half of mu band, to CST excitability change.
Main results: In the last session, IA/mu power suppression was achieved by 79% of participants, while 63% enhanced IA. CSD-EEG revealed that mu power was upregulated through an increase in the incidence rate of bursts of alpha band activity, while downregulation involved changes in oscillation amplitude and temporal patterns. Neuromodulation also influenced frequencies adjacent to the targeted band, indicating the use of common mental strategies within groups. Directed transfer function analysis showed, for both groups, significant connectivity between structures associated with motor imagery tasks, known to modulate the excitability of the motor cortex, although most connections did not remain significant after correcting for multiple comparisons. CST excitability modulation was related to the absolute amplitude of upper mu modulation, rather than the modulation direction.
Significance: The upregulation and downregulation of IA/mu power during NF, with respect to baseline were achieved via distinct mechanisms involving oscillatory and non-oscillatory EEG features. Mu enhancement and suppression post-NF and during the last NF block with respect to the baseline, respectively corresponded to opposite trends in motor-evoked potential changes post-NF. The ability of NF to modulate CST excitability could be a valuable rehabilitation tool for central nervous system disorders (stroke, spinal cord injury), where increased excitability and neural plasticity are desired. This work may inform future neuromodulation protocols and may improve NF training effectiveness by rewarding certain EEG signatures.
... Let us take SMR as an example. For example, some individuals with excessively low resting SMR activity have been found to be unresponsive to the SMR NFB protocol (Weber et al., 2011). In such cases, modulation through other EEG frequencies that have symmetric bidirectional coupling relationships with SMR may enhance SMR amplitudes. ...
In recent years, the dynamics and function of cross-frequency coupling (CFC) in electroencephalography (EEG) have emerged as a prevalent area of investigation within the research community. One possible approach in studying CFC is to utilize non-invasive neuromodulation methods such as transcranial alternating current stimulation (tACS) and neurofeedback (NFB). In this study, we address (1) the potential applicability of single and multifrequency tACS and NFB protocols in CFC research; (2) the prevalence of CFC types, such as phase–amplitude or amplitude–amplitude CFC, in tACS and NFB studies; and (3) factors that contribute to inter- and intraindividual variability in CFC and ways to address them potentially. Here we analyzed research studies on CFC, tACS, and neurofeedback. Based on current knowledge, CFC types have been reported in tACS and NFB studies. We hypothesize that direct and indirect effects of tACS and neurofeedback can induce CFC. Several variability factors such as health status, age, fatigue, personality traits, and eyes-closed (EC) vs. eyes-open (EO)condition may influence the CFC types. Modifying the duration of the tACS and neurofeedback intervention and selecting a specific demographic experimental group could reduce these sources of CFC variability. Neurofeedback and tACS appear to be promising tools for studying CFC.
... Weber et al. 52 showed that more than ten sessions were required to attain good modulation of sensorimotor rhythms and subsequently obtain good predictions of participant performance. ...
Real-time brain-computer interfaces (BCIs) that decode electroencephalograms (EEG) during motor imagery (MI) are a powerful adjunct to rehabilitation therapy after neurotrauma. Immersive virtual reality (VR) could complement BCIs by delivering multisensory feedback congruent to the user’s MI, enabling therapies that engage users in task-oriented scenarios. Yet, therapeutic outcomes rely on the user’s proficiency in evoking MI to attain volitional BCI-commanded VR interaction. While previous studies suggested that users could improve BCI-evoked MI within a single session, the effects of multiple training sessions on sensorimotor neuromodulation remain unknown. Here, we present a longitudinal study assessing the impact of VR-mediated BCI training on lower-limb sensorimotor neuromodulation, wherein an EEG-based BCI was coupled with congruent real-time multisensory feedback in immersive VR. We show that unimpaired individuals could learn to modulate their sensorimotor activations during MI virtual walking over multiple training sessions, also resulting in increased BCI control accuracy. Additionally, when extending the system to immersive VR cycling, four individuals with chronic complete spinal cord injury (SCI) showed similar improvements. This is the first study demonstrating that individuals could learn modulating sensorimotor activity associated with MI using BCI integrated with immersive VR over multiple training sessions, even after SCI-induced motor and sensory decline. These results suggest that VR-BCI training may facilitate neuroplasticity, potentially strengthening sensorimotor pathways and functional connectivity relevant to motor control and recovery.
... Several decades of feedback research with electroencephalogram (EEG) signals have shown that participants can be trained to influence the amplitude or topography of specific components of scalp electric activity [3]. However, it has been very difficult to influence specific mental states or treat psychiatric disorders with EEG-based neurofeedback, probably because of its low spatial specificity and difficulties associated with the poor signal-to-noise ratio provided by single trial-based EEG [4][5][6][7][8][9][10][11]. This phenomenon, which was initially seen in Brain-Computer Interface (BCI) research, has been shown for both healthy and unwell participants. ...
Objective
In this pilot study a binaural pulse modulator was tested to see if it leads to a change in self-reported measures of distress. This binaural pulse modulator produces two frequencies that combine to create a binaural pulse to stimulate the nervous system through a differential auditory tone presentation and the response of the user can be adjusted to the appropriate target tone for effective treatment use. Each individual calibrated the binaural pulse to increase the level of emotion experienced while imagining an experience with a similar emotional valence or while engaged in a cognitive function while also listening to the sound. “Treatment” is based on the client’s control of the binaural pulses to achieve the desired state. Training focuses on specific aspects of their psychological difficulties while listening to an auditory tone, turning a knob until the sound becomes uncomfortable. Finally, another knob is turned to cancel out the uncomfortable noise which appears to be associated with a reduction in distress.
Case presentations
Four adult Hispanic participants (three females and one male) were studied with self-reported measures of distress (generalized anxiety disorder 7, Coronavirus Disease Stress Scale, posttraumatic stress disorder checklist for Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, and Beck depression scale II) were completed at screening, before treatment, after treatment, 4-weeks post-treatment, and 12-weeks post-treatment. Quantitative electroencephalogram and functional magnetic resonance imaging were also performed before and after treatment.
Results
Preliminary findings indicated that at the end of treatment with binaural pulse modulator there were reported reductions in self-reported levels of distress. Quantitative electroencephalogram as well as functional magnetic resonance imaging changes in brain state were also noted when comparing pre- to post-treatment. Conclusions: binaural pulse modulator use appears to result in temporary changes in self-reported levels of distress during treatment. Limitations of the study are reviewed and directions for further research are offered.
... Depending on the aim of the NF training, changes in a specific EEG frequency can be fed back to the NF user in real time, e.g., through visual or auditory feedback. Most NF systems use visual feedback, e.g., in the form of two-dimensional objects that change size or move in response to changes in EEG parameters (e.g., Weber et al., 2011). However, changes in brain activation can also be transferred to changes in a VR scenario. ...
The rapid progress of commercial virtual reality (VR) technology, open access to VR development software as well as open-source instructions for creating brain-VR interfaces have increased the number of VR-based neurofeedback (NF) training studies. Controlling a VR environment with brain signals has potential advantages for NF applications. More entertaining, multimodal and adaptive virtual feedback modalities might positively affect subjective user experience and could consequently enhance NF training performance and outcome. Nevertheless, there are certain pitfalls and contraindications that make VR-based NF not suitable for everyone. In the present review, we summarize applications of VR-based NF and discuss positive effects of VR-based NF training as well as contraindications such as cybersickness in VR or age- and sex-related differences. The existing literature implies that VR-based feedback is a promising tool for the improvement of NF training performance. Users generally rate VR-based feedback more positively than traditional 2D feedback, albeit to draw meaningful conclusions and to rule out adverse effects of VR, more research on this topic is necessary. The pace in the development of brain-VR synchronization furthermore necessitates ethical considerations on these technologies.
... 11.0° wide and it changed vertically in size whenever SMR or Gamma power increased or decreased, respectively. To the left and right of the central bar two additional bars were presented depicting EOG artefacts (4-7 Hz, control frequency I) and muscle artefacts (50-100 Hz, control frequency II), respectively Weber et al., 2011). They were both ca. ...
EEG-based neurofeedback is a prominent method to modulate one’s own brain activity in a desired direction. However, the EEG signal can be disturbed by artifacts, e.g., eye movements, which can consequently confound the neurofeedback performance. Involuntary miniature eye movements can be hardly detected by conventional EEG correction methods such as recording the electro-oculogram (EOG) and subtracting EOG activity from the EEG signal. However, such miniature eye movements can influence EEG activity, especially in the Gamma frequency range, enormously. In the present study, we investigated whether power in different EEG frequencies can be effectively modulated by self-control of brain signals during neurofeedback training and/or whether changes in EEG power are provoked by miniature eye movements during the training. To this end, 24 participants performed one session of SMR and one session of Gamma neurofeedback training. Additionally, in each training session sham feedback was performed. An eye tracker was used to detect miniature eye movements (< 1°) during neurofeedback training. About two thirds of the participants were able to increase their SMR power over the course of NF training, while one third was able to increase Gamma power. Generally, miniature eye movements induced a strong Gamma power increase. The number of eye movements also increased numerically over the course of the NF training. However, we did not find a significant relationship with the NF training performance. This is a first indication that miniature saccades do not affect NF training performance, but should not be neglected during NF training. Our results have to be confirmed in future studies.
... Doehnert et al. evaluated the outcome of slow cortical potentials (SCPs) NFT on children with ADHD [18], and they found out that half of the subjects were not able to respond to the training. Weber et al. have used the individuals' EEG signals of 11 training sessions and complex methods to classify people into two groups; successful and unsuccessful learners [19]. Subjects with ADHD did not learn to control their brain signals and failed in showing a reduction in other symptoms in a study performed by Drechsler et al. [20]. ...
... Indeed, the amplitude of the signal measured during the resting state EEG or the first session seems to be a reliable predictor of an individual's ability to modulate this signal, in that the higher the level of baseline activity, the greater the modulation. This has been observed for the alpha (Su et al., 2021;Wan et al., 2014), sensorimotor rhythm (SMR, Blankertz et al., 2010;Li et al., 2021;Reichert et al., 2015;Weber et al., 2011) and low beta bands (12-15 Hz, Nan et al., 2015;Sho'ouri, 2021). Interestingly, although most of the cited studies aimed to increase the amplitude of the target signal during the resting state, one study (Nan et al., 2018) showed that a lower amplitude of the trained alpha frequency also predicted the ability to decrease it during NFB training. ...
Neurofeedback (NFB) is a brain-computer interface which allows individuals to modulate their brain activity. Despite the self-regulatory nature of NFB, the effectiveness of strategies used during NFB training has been little investigated. In a single session of NFB training (6*3min training blocks) with healthy young participants, we experimentally tested if providing a list of mental strategies (list group, N = 46), compared with a group receiving no strategies (no list group, N = 39), affected participants' neuromodulation ability of high alpha (10-12Hz) amplitude. We additionally asked participants to verbally report the mental strategies used to enhance high alpha amplitude. The verbatim was then classified in pre-established categories in order to examine the effect of type of mental strategy on high alpha amplitude. First, we found that giving a list to the participants did not promote the ability to neuromodulate high alpha activity. However, our analysis of the specific strategies reported by learners during training blocks revealed that cognitive effort and recalling memories were associated with higher high alpha amplitude. Furthermore, the resting amplitude of trained high alpha frequency predicted an amplitude increase during training, a factor that may optimize inclusion in NFB protocols. The present results also corroborate the interrelation with other frequency bands during NFB training. Although these findings are based on a single NFB session, our study represents a further step towards developing effective protocols for high alpha neuromodulation by NFB.
... These artifacts can lead to an increase in SMR activity. To prevent participants from falsely increasing their SMR activity using eye and muscle movements (e.g., excessive blinking or conscious muscle tensing), Theta activity (4-7 Hz) was presented in the left bar, and Beta activity (21-35 Hz) was displayed in the right bar in both groups Weber et al., 2011). ...
Electroencephalogram (EEG)-based neurofeedback (NF) is mainly used in clinical settings as a therapeutic intervention or to optimize performance in healthy individuals. Home-based NF systems are available and might facilitate general access to NF training, especially when repeated training sessions are necessary. However, it remains an open question whether NF training at home is possible without remote monitoring. In the present study, we assessed the capacity of healthy individuals to modulate their own EEG activity when using a home-based NF training system in a comparable manner as if participants had purchased a commercially available NF system. Participants’ face-to-face contact with experimenters was reduced to a minimum, and instructions were provided only in the form of written information or videos. Initially, 38 participants performed 9 sessions of sensorimotor rhythm (SMR) (12–15 Hz) based NF training (three generalization sessions, six training sessions). An active control group (n = 19) received feedback on random EEG frequencies. Because of technical problems, bad EEG data quality, or non-compliance, 21 participants had to be excluded from the final data analysis, providing first evidence for the difficulties of non-supervised home-based NF training. In this study, participants were not able to modulate their own brain activity in a desired direction during NF training. Our results indicate that personal interaction with a NF expert might be of relevance and that remote supervision of the training data and more direct communication with the NF users are necessary to enable successful NF training performance. We provide suggestions for the development and implementation of home-based NF systems.
... Notwithstanding its promise, NFT faces several challenges, including the failure of some individuals to achieve self-regulation, even after repeated training. Indeed, a substantial proportion -up to 30% -of participants in neurofeedback studies fail to self-regulate specific brain activity Weber, Köberl, Frank, & Doppelmayr, 2011). By considering the time and energy that need to be spent on training, it is useful and worthwhile to predict whether a participant will learn to regulate the EEG rhythms in advance. ...
This dissertation, after a critical review of the extant neurofeedback training (NFT) literature in sport, has identified some evidence for NFT as an approach that should enhance sporting performance in some circumstances; however, this evidence is on shaky grounds. A subsequent study tested the effectiveness of NFT on attention and reaction time of athletes, but found a smaller effect than what was found in the literature. This dissertation also highlights the debates on NFT and its effectiveness, and offers a solution by developing an allostasis four-stage model of NFT.
... Another possible explanation for our null result is the low success rate of our participants in reaching the neurofeedback goal, where one-third failed in all sessions, and only three succeeded in more than half of the sessions. This proportion of non-respondent is in line with www.nature.com/scientificreports/ the literature [50][51][52] , indicating that a considerable part of participants (around 50%) are non-respondents (or non-learners) to neurofeedback, having no success in modulating their brain activity through this technique. Future studies must assess the neuroenhancement effectiveness of neurofeedback, focusing on participants who are respondents to the neurofeedback. ...
Neurofeedback and transcranial Direct Current Stimulation (tDCS) are promising techniques for neuroenhancement of attentional performance. As far as we know no study compared both techniques on attentional performance in healthy participants. We compared tDCS and neurofeedback in a randomized, single-blind, controlled experiment assessing both behavioral (accuracy and time reaction) and electrophysiological (N1, P1, and P3 components) data of participants responding to the Attention Network Task (ANT). Eighty volunteers volunteered for this study. We adopted standard protocols for both techniques, i.e., a Sensorimotor Rhythm (SMR) protocol for neurofeedback and the right DLPFC anodal stimulation for tDCS, applied over nine sessions (two weeks). We did not find significant differences between treatment groups on ANT, neither at the behavioral nor at the electrophysiological levels. However, we found that participants from both neuromodulation groups, irrespective of if active or sham, reported attentional improvements in response to the treatment on a subjective scale. Our study adds another null result to the neuromodulation literature, showing that neurofeedback and tDCS effects are more complex than previously suggested and associated with placebo effect. More studies in neuroenhancement literature are necessary to fully comprehend neuromodulation mechanisms.
... This bar increased its size whenever SMR power increased. Two additional smaller bars on the left and on the right side of the screen depicted EOG artefacts (theta: 4-8 Hz) and muscle artefacts (beta: 21-35 Hz), respectively Weber et al., 2011). A baseline run at the beginning of the training session was used to determine individual thresholds for each bar. ...
Regular exercise improves cognitive control abilities and successful self-regulation of physical activity. However, it is not clear whether exercising also improves the ability to self-regulate one’s own brain activity. We investigated this in 26 triathletes and 25 control participants who did not exercise regularly. Within each group half of the participants performed one session of sensorimotor rhythm (SMR, 12-15 Hz) upregulation neurofeedback training, the other half received a sham neurofeedback training. The neurofeedback training session took about 45 minutes. In a separate session, participants underwent structural magnetic resonance imaging (MRI) to investigate possible differences in brain structure between triathletes and controls. Triathletes and controls were able to voluntarily upregulate their SMR activity during neurofeedback when receiving real feedback. Triathletes showed a stronger increase in SMR activity in the second half of the training compared to controls, suggesting that triathletes are able to self-regulate their own brain activity over a longer period of time. Further, triathletes and controls showed differences in brain structure as reflected by larger gray and white matter volumes in the inferior frontal gyrus and insula compared to controls. These brain areas are generally involved in cognitive control mechanisms. Our results provide new evidence regarding self-regulation abilities of people who exercise regularly and might impact the practical application of neurofeedback.
... In general, for visual stimulation, it is presented to the user as a specific visual target, as a point or line, that must be reached using a cursor represented by another point or line (Wolpaw et al. 1991;Zapała et al. 2017). It is common to use bars to represent the effort of the user (Caria et al. 2007;Weber et al. 2011), for instance, more concentrated or contracted muscles will increase the size of the bar. The hot-cold color intensity of an image is also often used to represent the modulation of brain activity training in a neurofeedback protocol (Hwang et al. 2009). ...
Collection of selected papers submitted and presented at the III Latin American Workshop on Computational Neuroscience (LAWCN'21), held in the city of São Luís do Maranhão, Brazil, from 8 to 10th December 2021. Papers have been peer-reviewed and selected for their superior quality and impact. Topics covered are within the areas of Computational Neuroscience, Artificial Intelligence, and Neuroengineering.
... In general, for visual stimulation, it is presented to the user as a specific visual target, as a point or line, that must be reached using a cursor represented by another point or line (Wolpaw et al. 1991;Zapała et al. 2017). It is common to use bars to represent the effort of the user (Caria et al. 2007;Weber et al. 2011), for instance, more concentrated or contracted muscles will increase the size of the bar. The hot-cold color intensity of an image is also often used to represent the modulation of brain activity training in a neurofeedback protocol (Hwang et al. 2009). ...
The neuron motor system has the ability to update the control strategy according to the environment. Intercepting a moving object is a task that can provide and study this ability. The aim of this study is to determine the performance and the control strategy on visual occlusion perturbation to intercepting moving targets. Sixteen subjects (24.4 ± 5.32 years old; 12 males and 4 females) were recruited. The experiment was carried out with a familiarization and an experimental phase where the participants managed a Physical Effector Machine (PEM) synchronized with a Virtual Interception Task (VIT). During the familiarization phase, participants learned the movement time (200 to 250 ms). In the experimental phase participants performed under two different conditions: Perturbation condition (PC), which corresponds to the target occlusion for 75 ms and 300 ms before expected movement onset and Control condition (CC) where there was no occlusion. In both conditions, the target moved at a constant velocity (145 cm.s−1). The results were analysed from the kinematics Movement time (MT), Relative time to peak velocity (%tPV), Correction Numbers (CN) and Spatial absolute-error (AE). The statistics were run by non-parametric Mann Whitney test to verify differences between CC and PC. The results showed a higher AE for PC than CC condition [U(159) = 16.738; p = .01; r = .43]. For the TM, %tPV and NC there were no differences between conditions. Our findings allowed us to conclude that the occlusion affected the performance accuracy but the control strategy to intercepting seemed to be similar in both conditions.KeywordMotor controlFeedback mechanismInterceptive task
... In general, for visual stimulation, it is presented to the user as a specific visual target, as a point or line, that must be reached using a cursor represented by another point or line ( Wolpaw et al. 1991;Zapała et al. 2018). It is common to use bars to represent the effort of the user (Caria et al. 2007; Weber et al. 2011), for instance, more concentrated or contracted muscles will increase the size of the bar. The hot-cold color intensity of an image is also often used to represent the modulation of brain activity training in a neurofeedback protocol (Hwang et al. 2009). ...
For a better rescuing of people with disabilities, it is crucial the development of new assistive technologies and therapeutic methods to rehabilitate people with some disabilities to integrate them to a complete social life. A very promising tool is the physiological self-regulation protocols based on biofeedback training. Biofeedback protocols are based on the premise that it is possible to learn how to self-modulate specific aspects of the body's physiological activity. A biofeedback system is composed of input physiological information and output sensorial stimuli information in a real-time closed-loop process that allows patients to modulate a target physiological (dys)function. The application of biofeedback protocols has been widely studied and used in different clinical practices such as orthopedic, neurological, physiological, and cognitive conditions. This review focuses on the main aspects concerning the system arrangement and protocols of stimulation in biofeedback approaches, from its basic principles of operation to its clinical application in different contexts , with emphasis on sensorimotor and cognitive deficits.
... Neurofeedback training (NFT) enables users to learn self-regulation of their cortical oscillations by receiving moment-to-moment feedback from their electroencephalogram (EEG) 1,2 . NFT is a safe, inexpensive, and accessible technology that is a valuable intervention. ...
Neurofeedback training (NFT) enables users to learn self-control of EEG activity of interest and then to create many benefits on cognitive function. A considerable number of nonresponders who fail to achieve successful NFT have often been reported in the within-session prediction. This study aimed to investigate successful EEG NFT of upregulation alpha activity in terms of trainability, independence, and between-session predictability validation. Forty-six participants completed 12 training sessions. Spectrotemporal analysis revealed the upregulation success on brain activity of 8–12 Hz exclusively to demonstrate trainability and independence of alpha NFT. Three learning indices of between-session changes exhibited significant correlations with eyes-closed resting state (ECRS) alpha amplitude before the training exclusively. Through a stepwise linear discriminant analysis, the prediction model of ECRS’s alpha frequency band amplitude exhibited the best accuracy (89.1%) validation regarding the learning index of increased alpha amplitude on average. This study performed a systematic analysis on NFT success, the performance of the 3 between-session learning indices, and the validation of ECRS alpha activity for responder prediction. The findings would assist researchers in obtaining insight into the training efficacy of individuals and then attempting to adapt an efficient strategy in NFT success.
... Operant learning can be regarded as part of the dual process theory, which includes automatically process and controlled process (Enriquez-Geppert et al., 2017). Normally, approximately 15-30% of subjects do not respond to neurofeedback/BCI (Weber et al., 2011). Strategies are extremely important for neurofeedback. ...
Compared with the traditional neurofeedback paradigm, the cognition-guided neurofeedback brain–computer interface (BCI) is a novel paradigm with significant effect on nicotine addiction. However, the cognition-guided neurofeedback BCI dataset is extremely lacking at present. This paper provides a BCI dataset based on a novel cognition-guided neurofeedback on nicotine addiction. Twenty-eight participants are recruited and involved in two visits of neurofeedback training. This cognition-guided neurofeedback includes two phases: an offline classifier construction and a real-time neurofeedback training. The original electroencephalogram (EEG) raw data of two phases are provided and evaluated in this paper. The event-related potential (ERP) amplitude and channel waveform suggest that our BCI dataset is of good quality and consistency. During neurofeedback training, the participants’ smoking cue reactivity patterns have a significant reduction. The mean accuracy of the multivariate pattern analysis (MVPA) classifier can reach approximately 70%. This novel cognition-guided neurofeedback BCI dataset can be used to develop comparisons with other neurofeedback systems and provide a reference for the development of other BCI algorithms and neurofeedback paradigms on addiction.
... In this context, there is an increasing interest for physiological or psychological predictors describing who would benefit from neurofeedback training (Alkoby et al., 2018). For example, several studies report functional neural networks (Weber et al., 2011;Scheinost et al., 2014;Wan et al., 2014;Trambaiolli et al., 2018a) and neuroanatomical differences (Halder et al., 2013) are related to the neurofeedback literacy in both healthy and clinical populations. Also, psychological aspects as control belief, frustration, concentration, among others, play an essential role during the training performance (Alkoby et al., 2018;Kadosh and Staunton, 2019). ...
Affective neurofeedback training allows for the self-regulation of the putative circuits of emotion regulation. This approach has recently been studied as a possible additional treatment for psychiatric disorders, presenting positive effects in symptoms and behaviors. After neurofeedback training, a critical aspect is the transference of the learned self-regulation strategies to outside the laboratory and how to continue reinforcing these strategies in non-controlled environments. In this mini-review, we discuss the current achievements of affective neurofeedback under naturalistic setups. For this, we first provide a brief overview of the state-of-the-art for affective neurofeedback protocols. We then discuss virtual reality as a transitional step toward the final goal of “in-the-wild” protocols and current advances using mobile neurotechnology. Finally, we provide a discussion of open challenges for affective neurofeedback protocols in-the-wild, including topics such as convenience and reliability, environmental effects in attention and workload, among others.
... Positive reinforcement seems to be more important than the feedback's operating component [56]. Although some studies have found good results while using the same reinforcement for all participants [28,57,58], other studies have found limited effect or no effect at all [29]. Our results suggest that one cause for these discrepancies may reside in the use of the same or low-preference reinforcements for all participants, an issue that had not been monitored for so far. ...
The brain activity that is measured by electroencephalography (EEG) can be modified through operant conditioning, specifically using neurofeedback (NF). NF has been applied to several disorders claiming that a change in the erratic brain activity would be accompanied by a reduction of the symptoms. However, the expected results are not always achieved. Some authors have suggested that the lack of an adequate response may be due to an incorrect application of the operant conditioning principles. A key factor in operant conditioning is the use of reinforcers and their value in modifying behavior, something that is not always sufficiently taken into account. This work aims to clarify the relevance of the motivational value versus the purely informational value of the reinforcer. In this study, 113 subjects were randomly assigned two different reinforcer conditions: a selected reinforcer—the subjects subjectively selected the reinforcers—or an imposed reinforcer—the reinforcers were assigned by the experimenter—and both groups undertook NF sessions to enhance the sensorimotor rhythm (SMR). In addition, the selected reinforcer group was divided into two subgroups: one receiving real NF and the other one sham NF. There were no significant differences between the groups at baseline in terms of SMR amplitude. After the intervention, only those subjects belonging to the selected reinforcer group and receiving real NF increased their SMR. Our results provide evidence for the importance of the motivational value of the reinforcer in Neurofeedback success.
... The most commonly used is the frequency training, in which the goal is changing the power ratio of the EEG frequency bands. It is mostly used in attention deficit hyperactivity disorder (ADHD) and autism spectrum disorders treatment [60,61]. Slow cortical potential (SCP) is a second kind of popular neurofeedback protocol, based on modulating specific (slow) event-related potentials (negative or positive); it is also mainly used in ADHD. ...
Background:
The aim of this article is to present a short review of noninvasive, nonpharmacological treatment methods used in somatic illnesses that fall under the umbrella of approach called behavioral medicine.
Methods:
The narrative review method was applied in the study. Science paper databases, including PubMed, had been used to retrieve papers on therapeutic methods used in clinical setting that meet the broad criteria of behavioral medicine definition as stated in the Charter of International Behavioral Medicine Society.
Results:
Main groups of methods, disorders in which they are being employed and their effectiveness, have been identified.
Conclusions:
Behavioral medicine is grouping treatment methods and interventions that hold large potential for clinical setting. Two groups of methods can be distinguished by the scrutiny and level of evidence gathered in their effectiveness assessment; for biofeedback, guided imagery, and hypnosis techniques, comprehensive evidence reports in the framework of U.S. Evidence Synthesis Program exist. Meditation techniques, disclosure therapies, and relaxation methods are less well assessed. Broader employment of behavioral medicine therapies in clinical setting is possible after addressing two major problems in the field, which are deficiencies in quality evidence of effectiveness for many of the methods and their insufficiencies in underlying therapeutic mechanism knowledge.
... In the present study, behavioral transfer to both posttests and theta changes from pre-to both posttraining sessions were predicted by individual NFT theta changes, demonstrating the importance of taking individual differences into account for determining the efficiency of NFT. Even if individually estimated frequency bands are trained, some participants have shown to be non-responsive to NFT ( Enriquez-Geppert et al., 2014b ; Hanslmayr et al., 2005 ;Weber et al., 2011 ) and it has been argued that small MCC volumes contribute to the non-responsiveness to NFT ( Enriquez-Geppert et al., 2013 ;Ninaus et al., 2015 ). Interestingly, older participants show small FM theta amplitudes that are not related to small MCC volumes but are associated with cognitive decline instead ( Kardos et al., 2014 ). ...
Cognitive and neurofeedback training (NFT) studies have demonstrated that training-induced alterations of frontal-midline (FM) theta activity (4-8 Hz) transfer to cognitive control processes. Given that FM theta oscillations are assumed to provide top-down control for episodic memory retrieval, especially for source retrieval, that is, accurate recollection of contextual details of prior episodes, the present study investigated whether FM theta NFT transfers to memory control processes. It was assessed (1) whether FM theta NFT improves source retrieval and modulates its underlying EEG characteristics and (2) whether this transfer extends over two posttests. Over seven NFT sessions, the training group who trained individual FM theta activity showed greater FM theta increase than an active control group who trained randomly chosen frequency bands. The training group showed better source retrieval in a posttraining session performed 13 days after NFT and their performance increases from pre- to both posttraining sessions were predicted by NFT theta increases. Thus, training-induced enhancement of memory control processes seems to protect newly formed memories from proactive interference of previously learned information. EEG analyses revealed that during pretest both groups showed source memory specific theta activity at frontal and parietal sites. Surprisingly, training-induced improvements in source retrieval tended to be accompanied by less prestimulus FM theta activity, which was predicted by NFT theta change for the training but not the control group, suggesting a more efficient use of memory control processes after training. The present findings provide unique evidence for the enhancement of memory control processes by FM theta NFT.
... Six out of 14 reported self-perceived improvements due to the NF-SCP training. This is in line with studies reporting on so-called "performers and non-performers" [86], which to some degree is reflected in the patterns of the manipulation of the slow cortical potentials, at least on a group level. ...
Neurofeedback (NF) as a treatment for children and adolescents with attention deficit hyperactivity disorder (ADHD) has gained growing interest in recent years. Most research has been quantitative, focusing on treatment outcomes, while qualitative approaches exploring the treatment process and participants’ experiences are scarce. The objective of this study was to examine NF participants’ use of cognitive and other strategies for approaching and solving NF tasks, their development over the course of the training and the influence of participants’ compliance.
Method
We collected 130 short semi-structured interviews following treatment sessions from 30 participants with ADHD receiving NF using slow cortical potential training (SCP). The interviews were transcribed verbatim and analyzed using thematic analysis. Themes where evaluated for changes over-time and between participants with high/low treatment compliance. Interviews from 14 participants who had undergone at least five completed interviews were examined in more depths, aiming to establish typical strategy/training profiles.
Results
We identified 16 strategies covering four domains: cognitive, physiological, emotional and unspecified. Typical of most strategies were that they served as a vehicle to regulate mental arousal. Overall, no clear patterns of changes over time were found. Highly compliant participants reported to use the strategies from the emotional domain and the strategy focus more frequently than neutral compliant participants did, while neutral compliant participants reported the use of the strategies muscular activity and passivity more often than participants did with high compliance. Across participants, three strategy profiles were derived, those who handled the task by manipulating their state of mind in relation to the NF task, those who were mainly manifest and concrete towards the task, and those who were mostly unaware of what they were doing. These profiles differed in self-regulatory performance, and only participants showing the state of mind profile experienced a decrease of ADHD symptoms accompanied by objectively measured improvements in self-regulation. In addition, compliance affected both how and what strategies were used.
Conclusion/discussion
A heterogeneous array of cognitive and other strategies is used at varying levels of training compliance by participants with ADHD during SCP that could be condensed to three prototypical profiles. Future research should take compliance and strategy/training profiles into account when evaluating NF. The latter may help to clarify which and how brain activity regulating mechanisms drive training, individual response to NF, and how they are influenced by motivational factors. Our findings might also help to facilitate more effective instructions in how to approach SCP in clinical practice.
... Unfortunately, a rigorous examination of the method is further complicated by the fact that a relatively large proportion of participants fail to acquire regulation capability of their brain activity (e.g., Enriquez-Geppert et al., 2013;Gevensleben et al., 2009;Kotchoubey et al., 1999;Weber et al., 2011). In these cases, the essential purpose of the NF method could not be achieved. ...
Neurofeedback (NF), a training tool aimed at enhancing neural self-regulation, has been suggested as a complementary treatment option for neuropsychiatric disorders. Despite its potential as a neurobiological intervention directly targeting neural alterations underlying clinical symptoms, the efficacy of NF for the treatment of mental disorders has been questioned recently by negative findings obtained in randomized controlled trials (e.g., Cortese et al., 2016). A possible reason for insufficient group effects of NF trainings vs. placebo could be related to the high rate of participants who fail to self-regulate brain activity by NF (“non-learners”). Another reason could be the application of standardized NF protocols not adjusted to individual differences in pathophysiology. Against this background, we have summarized information on factors determining training and treatment success to provide a basis for the development of individualized training protocols and/or clinical indications.
The present systematic review included 25 reports investigating predictors for the outcome of NF trainings in healthy individuals as well as patients affected by mental disorders or epilepsy. We selected these studies based on searches in EBSCOhost using combinations of the keywords ”neurofeedback“ and ”predictor/predictors“. As “NF training” we defined all NF applications with at least two sessions.
The best available evidence exists for neurophysiological baseline parameters. Among them, the target parameters of the respective training seem to be of particular importance. However, particularities of the different experimental designs and outcome criteria restrict the interpretability of some of the information we extracted. Therefore, further research is needed to gain more profound knowledge about predictors of NF outcome.
... Emerging evidence suggests that early neurophysiological characteristics could be particularly useful in predicting neurofeedback effects, including patients' initial ability to regulate the neural activity (e.g. the average performance in first 30 trials) (Weber et al., 2011) and the ease of generating neural activity patterns (e.g. the classification accuracy of neural activity patterns) (Sadtler et al., 2014). Therefore, we additionally examine whether these short-term and long-term behavioural effects could be predicted by the classification accuracy of neural activity patterns at preneurofeedback and deactivated performance during the first cycle of neurofeedback, respectively. ...
With approximately 75% of smokers resuming cigarette smoking after using the Gold Standard Programme for smoking cessation, investigation into novel therapeutic approaches is warranted. Typically, smoking cue reactivity is crucial for smoking behaviour. Here we developed a novel closed-loop, smoking cue reactivity patterns EEG-based neurofeedback protocol and evaluated its therapeutic efficacy on nicotine addiction. During an evoked smoking cue reactivity task participants' brain activity patterns corresponding to smoking cues were obtained with multivariate pattern analysis of all EEG channels data, then during neurofeedback the EEG activity patterns of smoking cue reactivity were continuously deactivated with adaptive closed-loop training. In a double-blind, placebo-controlled, randomized clinical trial, 60 nicotine-dependent participants were assigned to receive two neurofeedback training sessions (∼1 h/session) either from their own brain (n = 30, real-feedback group) or from the brain activity pattern of a matched participant (n = 30, yoked-feedback group). Cigarette craving and craving-related P300 were assessed at pre-neurofeedback and post-neurofeedback. The number of cigarettes smoked per day was assessed at baseline, 1 week, 1 month, and 4 months following the final neurofeedback visit. In the real-feedback group, participants successfully deactivated EEG activity patterns of smoking cue reactivity. The real-feedback group showed significant decrease in cigarette craving and craving-related P300 amplitudes compared with the yoked-feedback group. The rates of cigarettes smoked per day at 1 week, 1 month and 4 months follow-up decreased 30.6%, 38.2%, and 27.4% relative to baseline in the real-feedback group, compared to decreases of 14.0%, 13.7%, and 5.9% in the yoked-feedback group. The neurofeedback effects on craving change and smoking amount at the 4-month follow-up were further predicted by neural markers at pre-neurofeedback. This novel neurofeedback training approach produced significant short-term and long-term effects on cigarette craving and smoking behaviour, suggesting the neurofeedback protocol described herein is a promising brain-based tool for treating addiction.
Objective: In this pilot study a binaural pulse modulator (BPM) was tested to see if it indeed leads to a change in self-reported measures of distress. This BPM produces two frequencies which combine to create a binaural pulse to stimulate the nervous system through a differential auditory tone presentation and through the response of the user can be adjusted to the appropriate target tone for effective treatment use. The binaural pulse is calibrated by each individual in order to increase the level of emotion experienced while imagining an experience with a similar emotional valence or while engaged in a cognitive function while also listening to the sound. “Treatment” is based on the client's control of the binaural pulses to achieve the desired state. Training focuses on specific aspects of their psychological difficulties while listening to an auditory tone, turning a knob until the sound becomes uncomfortable. Finally, another knob is turned to cancel out the uncomfortable noise which appears to be associated with reduction in distress.
Case presentations: Four adult Hispanic participants (three female aged 38, 59,and 45 years and one male aged 19) were studied with self report measures of distress (generalized anxiety disorder 7, Covid-stress-scale, PTSD checklist for DSM-5, Beck depression scale -II) were completed at screening, prior to treatment, at the completion of treatment, four weeks post treatment, and 12 weeks post treatment. qEEG and fMRI was also performed prior to and after treatment. Results: Preliminary findings indicated that at the end of treatment with BPM reported reductions in self reported levels of distress. qEEG as well as fMRI changes in brain state were also noted when comparing pre to post treatment.
Conclusions: BPM use appears to result in temporary change in self-reported levels of distress during the course of treatment. Limitations of the study are reviewed and directions for further research are offered.
In dieser Übersicht stellen wir an erster Stelle Frequenzbandtrainingsprotokolle vor, die wissenschaftlich bezüglich ihrer Effektivität sehr gut untersucht sind und in der Praxis seit mehreren Jahrzenten erfolgreich eingesetzt werden. Diese „Standard-Neurofeedback-Protokolle“ sind das monopolare SMR-up-Training, das SMR-upTheta-down-Protokoll und das Theta/Beta Protokoll. Wir besprechen eingehend die Datenlage und die positive Wirkung dieser Standard-Protokolle, gehen aber auch auf ihre Unzulänglichkeiten näher ein. Auch weniger gut untersuchte Protokolle, die künftig richtungsweisend sein können, wie das Alpha-Asymmetrieprotokoll werden vorgestellt.
Susceptibility of brain activity to the inhalation of different aromas established the idea of inhaling an aroma as an auxiliary factor in neurofeedback training. The present study has focused on investigating the effect of musk incense stick aroma inhalation on various features of EEG signals (power of different frequency bands along with Katz fractal dimension (Katz’s FD), approximate entropy (ApEn) and scaling exponent) and working memory for use in neurofeedback training. To raise this aim, the EEG signals were recorded under eyes-open (EO) and eyes-closed (EC) conditions for 22 healthy subjects before and during the musk incense stick aroma inhalation, followed by performing Wechsler Memory Scale (WMS). The results showed that musk incense stick aroma inhalation under EO condition increased the relative power of delta, theta, sensorimotor rhythm (SMR) and low beta frequency bands along with ApEn and Katz’s FD in most channels, whereas decreased the relative power of alpha, high beta and gamma bands. A decrease was found in the relative power of delta, theta, SMR, low beta, high beta and gamma frequency bands in some channels under EC conditions. ApEn and Katz’s FD values also increased in most channels under EC conditions following musk incense stick aroma inhalation. The scaling exponent also decreased under the same conditions in most channels. However, these changes were not significant in all channels. The WMS score also increased after inhaling aroma, but not significantly. The findings of this research suggest the use of musk incense stick aroma inhalation during neurofeedback training to increase training efficiency.
In dieser Dissertation untersuchten wir die neuronalen Korrelate des Training-Effektes einer auditorischen P300 Gehirn-Computer Schnittstelle mittels fMRI Analyse in einem prä-post Design mit zehn gesunden Testpersonen. Wir wiesen in drei Trainings-sitzungen einen Trainingseffekt in der EEG-Analyse der P300 Welle nach und fanden entsprechende Kontraste in einer prä-post Analyse von fMRI Daten, wobei in allen fünf Sitzungen das gleiche Paradigma verwendet wurde. In der fMRI Analyse fanden wir fol-gende Ergebnisse: in einem Target-/ Nichttarget Kontrast zeigte sich verstärkte Aktivie-rung in Generatorregionen der P300 Welle (temporale und inferiore frontale Regionen) und interessanterweise auch in motorassoziierten Arealen, was höhere kognitiver Pro-zesse wie Aufmerksamkeitslenkung und Arbeitsspeicher widerspiegeln könnte. Der Kon-trast des Trainingseffektes zeigte nach dem Training einen stärkeren Rebound Effekt im Sinne einer verstärkten Aktivierung in Generatorregionen der P300 Welle, was eine ver-besserte Erkennung und Prozessierung von Target-Stimuli reflektieren könnte. Eine Ab-nahme von Aktivierung in frontalen Arealen in diesem Kontrast könnte durch effizientere Abläufe kognitiver Prozesse und des Arbeitsgedächtnis erklärt werden.
Epilepsy is a chronic brain disorder characterized by recurrent seizures due to abnormally synchronized electrical discharges. Neurofeedback (NFB) is an operative conditioning technique used to reinforce or inhibit specific frequencies of electroencephalogram (EEG) activity. Augmentation of the sensorimotor rhythm (SMR) is a common neurofeedback protocol for epilepsy patients. In the present work, we aim to evaluate the espectral outcomes of a neurofeedback protocol based on SMR augmentation in refractory epilepsy patients. The participants underwent five sessions of NFB while having their EEG recorded with a 22-electrode system. The sensorimotor rhythm (SMR) before and after the NFB training differed significantly in the frontal, central electrodes, and in the channel used for training. Our results demonstrate that NFB training can improve regulation of SMR in these patients.KeywordsEpilepsyNeurofeedbackSensorimotor rhythm
Featured Application
A mental and emotional state priming BCI to assist Neurofeedback self-regulation serious games.
Abstract
Neurofeedback training (NFT) is a technique often proposed to train brain activity SR with promising results. However, some criticism has been raised due to the lack of evaluation, reliability, and validation of its learning effects. The current work evaluates the hypothesis that SR learning may be improved by priming the subject before NFT with guided mindfulness meditation (MM). The proposed framework was tested in a two-way parallel-group randomized controlled intervention with a single session alpha NFT, in a simplistic serious game design. Sixty-two healthy naïve subjects, aged between 18 and 43 years, were divided into MM priming and no-priming groups. Although both the EG and CG successfully attained the up-regulation of alpha rhythms (F(1,59) = 20.67, p < 0.001, ηp² = 0.26), the EG showed a significantly enhanced ability (t(29) = 4.38, p < 0.001) to control brain activity, compared to the CG (t(29) = 1.18, p > 0.1). Furthermore, EG superior performance on NFT seems to be explained by the subject’s lack of awareness at pre-intervention, less vigour at post-intervention, increased task engagement, and a relaxed non-judgemental attitude towards the NFT tasks. This study is a preliminary validation of the proposed assisted priming framework, advancing some implicit and explicit metrics about its efficacy on NFT performance, and a promising tool for improving naïve “users” self-regulation ability.
Despite the considerable success of neurofeedback techniques in the treatment of various neurological disorders and the improvement of cognitive performance of healthy individuals, some people fail to learn how to control their brain activities using neurofeedback. Given the time-consuming and costly nature of neurofeedback, the prediction of people’s success rate in training by neurofeedback is of paramount importance. Therefore, the present study aimed to determine the factors affecting the success rate of 7 healthy women over 10 sessions (30 trials) in terms of enhancement of low beta band activities (βL). The relative power of different frequency bands (delta, theta, alpha and beta) of EEG signals obtained in the first training session was considered as the predictor variable along with the participants’ IQ test score. Afterwards, we assessed the predictor variables’ impact on the mean low beta power (15–18 Hz) values of the participants’ EEG signals in the last session (βL(last sess)). According to the results, the mean low beta power in the first session (βL(sess1)) had the most effect on βL(last sess) (R² = 73.9 %). In the next stage, we designed three systems using the RBF network, which predicted the βL(last sess), mean score of each participant in the last training session and the slope of βL changes of each subject during the training sessions using βL(sess1) (prediction error < 10⁻¹¹). The designed prediction system may be able to increase training efficiency with neurofeedback and save time and financial resources.
Objectives
According to some studies, a putatively calming effect of EEG neurofeedback training could be useful as a therapeutic tool in psychiatric practice. With the aim of elucidating this possibility, we tested the efficacy of a single session of ↑sensorimotor (SMR)/↓theta neurofeedback training for mood improvement in 32 healthy men, taking into account trainability, independence and interpretability of the results.
Methods
A pre-post design, with the following dependent variables, was applied: (i) psychometric measures of mood with regards to anxiety, depression, and anger (Profile of Mood State, POMS, and State Trait Anxiety Inventory, STAI); (ii) biological measures (salivary levels of cortisol); (iii) neurophysiological measures (EEG frequency band power analysis). In accordance with general recommendations for research in neurofeedback, a control group receiving sham neurofeedback was included.
Results
Anxiety levels decreased after the real neurofeedback and increased after the sham neurofeedback (P < 0.01, size effect 0.9 for comparison between groups). Cortisol decreased after the experiment in both groups, though with significantly more pronounced effects in the desired direction after the real neurofeedback (P < 0.04; size effect 0.7). The group receiving real neurofeedback significantly enhanced their SMR band (P < 0.004; size effect 0.88), without changes in the theta band. The group receiving sham neurofeedback did not show any EEG changes.
Conclusions
The improvement observed in anxiety was greater in the experimental group than in the sham group, confirmed by both subjective (psychometric) measures and objective (biological) measures. This was demonstrated to be associated with the real neurofeedback, though a nonspecific (placebo) effect likely also contributed.
Introduction: Alpha/Theta neurofeedback treatment (A/T NFT) has been administered to adults with anxiety disorders since the late 1960s, yet the efficacy of this treatment remains unclear. The present, single-blind study, for the first time, uses an active placebo NFT control group to test the A/T NFT protocol for trait anxiety on prodromal and clinical adult female participants. The effects this treatment has on activation and arousal states, self-perceived anxiety levels, neural oscillations, and other parameters were assessed.
Methods: Twenty-seven women ranging in age from 19 through 69 who had scored higher than the 66th percentile in the STAI trait anxiety sub-scale (75% of whom had previously been diagnosed with an anxiety disorder) were randomly assigned to either the experimental (EG) or the control group (CG). The EG (n = 14) received ten sessions of A/T NFT in which alpha and theta EEG amplitudes were uptrained at Pz. The CG (n = 13) received ten sessions of active placebo NFT at Pz. During successive sessions beta- (15–19 Hz) and high beta amplitudes (20- 24 Hz) were uptrained or downtrained. Growth curve modeling (GCM) and traditional 2x5 repeated measures ANOVA were performed on the NFT sessions data to model individual and average group learning curves. Cognitive variables, such as treatment outcome expectancy, personal attribution styles, use, types, and efficacy of cognitive strategies in NFT, and correlations between NFT learning performance, time of day the NFT sessions were held, and a participant’s best or worst time to learn, were also investigated.
Results: The analysis of individual learning curves, GCM, and ANOVA all confirmed that the majority of participants of the EG up-regulated absolute and relative A+T amplitudes within a NFT session, but so did the participants of the CG. However, a non-significant trend for the EG to have steeper learning curves was observed. Participants of both the EG and the CG felt significantly more deactivated by the end of a NFT session and reduced their self-perceived anxiety on all anxiety measures (STAI, BAI, GAD-7) by the end of the NFT trial. Although a trend could be observed that the EG reduced anxiety scores more than the CG, these differences did not rise to statistical significance. Lastly, no significant changes in the pre-post trial QEEG were found, although a trend of higher combined relative A+T power at the end of the trial was observed in the EG. In the EG the use of mental strategies was correlated with lower T/A ratio difference scores between the beginning and the end of the NFT trial but not with increased relative and absolute T+A amplitudes. The Time-of-day participants prefer or avoid learning did not correlate significantly with alpha or theta NFT amplitudes, i.e., NFT sessions being held during sub-optimal times of day were not associated with poorer learning performance.
Conclusions: For both EG and CG absolute and relative T+A amplitudes increased within sessions and absolute and relative alpha increased across sessions although the CG protocol had not included an uptraining of alpha or theta amplitudes, nor low beta amplitudes (below 15 Hz) which may have represented upper alpha peak frequency in some of the younger participants. Thus, upregulation of beta and upper beta in NFT may be associated with alpha frequency uptraining due to functional coupling of alpha and beta EEG frequencies or it may be due to placebo and other non-specific effects such as EEG frequency drifts, alpha’s idling mode and inhibitory role during task performance, or perhaps simply that some frequency bands (alpha) are more susceptible to change and easier to train. Especially the inhibition of flanking bands in the NFT protocol, i.e., beta bands in A+T training, to prevent frequency drifts, will be necessary along with detailed GCM modeling of all frequency bands to see if and how the bands change over time and how those processes relate to NFT learning curves.
Keywords: neurofeedback, EEG biofeedback, quantitative EEG, trait / state anxiety, anxiety disorders, active placebo control, alpha/theta protocol, growth curve modeling.
Biofeedback-assisted modulation of electrocortical activity has been established to have intrinsic clinical benefits and has been shown to improve cognitive performance in healthy humans. In order to further investigate the pedagogic relevance of electroencephalograph (EEG) biofeedback (neurofeedback) for enhancing normal function, a series of investigations assessed the training's impact on an ecologically valid real-life behavioural performance measure: music performance under stressful conditions in conservatoire students. In a pilot study, single-blind expert ratings documented improvements in musical performance in a student group that received training on attention and relaxation related neurofeedback protocols, and improvements were highly correlated with learning to progressively raise theta (5–8 Hz) over alpha (8–11 Hz) band amplitudes. These findings were replicated in a second experiment where an alpha/theta training group displayed significant performance enhancement not found with other neurofeedback training protocols or in alternative interventions, including the widely applied Alexander technique.
One of the dramatic sequelae of strokes is the impairment of cognitive functions. Standard rehabilitation programs do not always lead to an improvement. Based on theoretical considerations, the authors used alpha or theta neurofeedback training (NFT) in two different studies and assessed changes in the cognitive performance of the stroke patients. However, these two studies yielded incongruent results. Although in Study 1, alpha NFT was superior to a control treatment, this result could not be replicated in the second study. In Study 2, neither alpha nor theta NFT was superior to a control treatment. Given these conflicting results, the authors suggest that there is a serious need to perform future studies with comparison to a database and individual training protocols at selected electrode positions.
Seven autistic children diagnosed with autism spectrum disorders (ASD) received a neurofeedback treatment that aimed to improve their level of executive control. Neurofeedback successfully reduced children's heightened theta/beta ratio by inhibiting theta activation and enhancing beta activation over sessions. Following treatment, children's executive capacities were found to have improved greatly relative to pre-treatment assessment on a range of executive function tasks. Additional improvements were found in children's social, communicative and typical behavior, relative to a waiting list control group. These findings suggest a basic executive function impairment in ASD that can be alleviated through specific neurofeedback treatment. Possible neural mechanisms that may underlie neurofeedback mediated improvement in executive functioning in autistic children are discussed.
Since the first reports of neurofeedback treatment in Attention Deficit Hyperactivity Disorder (ADHD) in 1976, many studies have investigated the effects of neurofeedback on different symptoms of ADHD such as inattention, impulsivity and hyperactivity. This technique is also used by many practitioners, but the question as to the evidence-based level of this treatment is still unclear. In this study selected research on neurofeedback treatment for ADHD was collected and a meta-analysis was performed.
Both prospective controlled studies and studies employing a pre-and post-design found large effect sizes (ES) for neurofeedback on impulsivity and inattention and a medium ES for hyperactivity. Randomized studies demonstrated a lower ES for hyperactivity suggesting that hyperactivity is probably most sensitive to nonspecific treatment factors.
Due to the inclusion of some very recent and sound methodological studies in this meta-analysis, potential confounding factors such as small studies, lack of randomization in previous studies and a lack of adequate control groups have been addressed, and the clinical effects of neurofeedback in the treatment of ADHD can be regarded as clinically meaningful. Three randomized studies have employed a semi-active control group which can be regarded as a credible sham control providing an equal level of cognitive training and client-therapist interaction. Therefore, in line with the AAPB and ISNR guidelines for rating clinical efficacy, we conclude that neurofeedback treatment for ADHD can be considered “Efficacious and Specific” (Level 5) with a large ES for inattention and impulsivity and a medium ES for hyperactivity.
About one third of patients with epilepsy do not benefit from medical treatment. For these patients electroencephalographic (EEG) biofeedback is a viable alternative. EEG biofeedback, or neurofeedback, normalizes or enhances EEG activity by means of operant conditioning. While dozens of scientific reports have been published on neurofeedback for seizure disorder, most have been case series with too few subjects to establish efficacy. The purpose of this paper is to meta-analyze existing research on neurofeedback and epilepsy.
We analyzed every EEG biofeedback study indexed in MedLine, PsychInfo, and PsychLit databases between 1970 and 2005 on epilepsy that provided seizure frequency change in response to feedback. Sixty-three studies have been published, 10 of which provided enough outcome information to be included in a meta-analysis. All studies consisted of patients whose seizures were not controlled by medical therapies, which is a very important factor to keep in mind when interpreting the results. Nine of 10 studies reinforced sensorimotor rhythms (SMR) while 1 study trained slow cortical potentials (SCP). All studies reported an overall mean decreased seizure incidence following treatment and 64 out of 87 patients (74%) reported fewer weekly seizures in response to EEG biofeedback. Treatment effect was mean log (post/pre) where pre and post represent number of seizures per week prior to treatment and at final evaluation, respectively. Due to prevalence of small groups, Hedges's g was computed for effect size. As sample heterogeneity was possible (Q test, p=.18), random effects were assumed and the effect of intervention was −0.233, SE= 0.057, z [Formula: see text] −4.11, p<.001.
Based on this meta-analysis, EEG operant conditioning was found to produce a significant reduction on seizure frequency. This finding is especially noteworthy given the patient group, individuals who had been unable to control their seizures with medical treatment.
Alpha/theta (a/t) neurofeedback training has in the past successfully been used as a complementary therapeutic relaxation technique in the treatment of alcoholism. In spite of positive clinical outcomes, doubts have been cast on the protocol's specificity when compared to alternative relaxation regimes. This study investigated the basic tenet underlying the a/t training rationale, that accurate a/t feedback representation facilitates the generation of these frequency components. Two groups of healthy volunteers were randomly assigned to either (a) real contingent a/t feedback training or (b) a noncontingent mock feedback control condition. The groups were compared on measures of theta/alpha (t/a) ratios within and across training sessions, as well as activational self-report scales after each session. The contingent a/t feedback group displayed significant within-session t/a ratio increments not evident in the mock control group, as well as higher overall t/a ratios in some but not all of the training sessions. No differences were found between the groups in terms of subjective activational phenomenology, in that both groups reported significantly lower levels of activation after training sessions. The data demonstrate that irrespective of considerations of clinical relevance, accurate a/t neurofeedback effectively facilitates production of higher within-session t/a ratios than do noncontingent feedback relaxation.
Alpha-theta neurofeedback has been shown to produce professionally significant performance improvements in music students. The present study aimed to extend this work to a different performing art and compare alpha-theta neurofeedback with another form of biofeedback: heart rate variability (HRV) biofeedback. Twenty-four ballroom and Latin dancers were randomly allocated to three groups, one receiving neurofeedback, one HRV biofeedback and one no intervention. Dance was assessed before and after training. Performance improvements were found in the biofeedback groups but not in the control group. Neurofeedback and HRV biofeedback benefited performance in different ways. A replication with larger sample sizes is required.
This review provides an updated overview of the neurophysiological rationale, basic and clinical research literature, and current methods of practice pertaining to clinical neurofeedback. It is based on documented findings, rational theory, and the research and clinical experience of the authors. While considering general issues of physiology, learning principles, and methodology, it focuses on the treatment of epilepsy with sensorimotor rhythm (SMR) training, arguably the best established clinical application of EEG operant conditioning. The basic research literature provides ample data to support a very detailed model of the neural generation of SMR, as well as the most likely candidate mechanism underlying its efficacy in clinical treatment. Further, while more controlled clinical trials would be desirable, a respectable literature supports the clinical utility of this alternative treatment for epilepsy. However, the skilled practice of clinical neurofeedback requires a solid understanding of the neurophysiology underlying EEG oscillation, operant learning principles and mechanisms, as well as an in-depth appreciation of the ins and outs of the various hardware/software equipment options open to the practitioner. It is suggested that the best clinical practice includes the systematic mapping of quantitative multi-electrode EEG measures against a normative database before and after treatment to guide the choice of treatment strategy and document progress towards EEG normalization. We conclude that the research literature reviewed in this article justifies the assertion that neurofeedback treatment of epilepsy/seizure disorders constitutes a well-founded and viable alternative to anticonvulsant pharmacotherapy.
Research groups have consistently reported on behavioral and cognitive improvements of children with ADHD after neurofeedback. However, neurofeedback has not been commonly accepted as a treatment for ADHD. This is due, in part, to several methodological limitations. The neurofeedback literature is further complicated by having several different training protocols. Differences between the clinical efficacy of such protocols have not been examined. This study addresses previous methodological shortcomings while comparing the training of theta-beta-frequencies (theta-beta-group) with the training of slow cortical potentials (SCP-group). Each group comprised of 19 children with ADHD that were blind to group assignment. The training procedure consisted of 30 sessions and a six months follow-up training. Pre-/post measures at pretest, the end of the training and the follow-up included tests of attention, intelligence and behavioral variables. After having already reported intermediate data (Strehl et al. 2004), this paper gives account on final results: Both groups are able to voluntarily regulate cortical activity, with the extent of learned self-regulation depending on task and condition. Both groups improve in attention and IQ. Parents and teachers report significant behavioral and cognitive improvements. Clinical effects for both groups remain stable six months after training. Groups do not differ in behavioral or cognitive outcome variables.
Behavioral and cognitive improvements in children with ADHD have been consistently reported after neurofeedback-treatment. However, neurofeedback has not been commonly accepted as a treatment for ADHD. This study addresses previous methodological shortcomings while comparing a neurofeedback-training of Theta-Beta frequencies and training of slow cortical potentials (SCPs). The study aimed at answering (a) whether patients were able to demonstrate learning of cortical self-regulation, (b) if treatment leads to an improvement in cognition and behavior and (c) if the two experimental groups differ in cognitive and behavioral outcome variables. SCP participants were trained to produce positive and negative SCP-shifts while the Theta/Beta participants were trained to suppress Theta (4-8 Hz) while increasing Beta (12-20 Hz). Participants were blind to group assignment. Assessment included potentially confounding variables. Each group was comprised of 19 children with ADHD (aged 8-13 years). The treatment procedure consisted of three phases of 10 sessions each. Both groups were able to intentionally regulate cortical activity and improved in attention and IQ. Parents and teachers reported significant behavioral and cognitive improvements. Clinical effects for both groups remained stable six months after treatment. Groups did not differ in behavioural or cognitive outcome.
This chapter aims to broaden practitioners' understanding of Asperger's syndrome (AS), a disorder along the continuum of autistic spectrum disorders (ASD). AS is becoming a relatively common diagnosis in schoolchildren who are very bright intellectually but totally inept socially. They are usually initially misdiagnosed as having attention deficit hyperactivity disorder (ADHD). This chapter emphasizes how to use neurofeedback (NFB) plus biofeedback (BFB), in conjunction with coaching in learning strategies (metacognition) to address the major symptoms observed in AS. It develops an understanding of how feedback can improve a person's cognitive, emotional, and even physical functioning, and has named this a systems theory of neural synergy (STNS). The name underscores the fact that NFB plus BFB influence dynamic circuits, and emphasizes that no matter where one enters the nervous system with an intervention the larger system adjusts as it seeks a new balance. If the intervention is done correctly, the new equilibrium will bring out the individual's potential. This chapter is divided into four sections. The first section gives a general overview of Asperger's syndrome including background, a historical note, information on prevalence, and a description of symptoms that includes the authors' clinical observations. The second section correlates symptoms with functional neuroanatomy and electroencephalographic (EEG) findings. The third section further highlights brain areas found to be dysfunctional in ASD, and cites research findings for each of seven key regions that are repeatedly found to differ when compared to people with typical development. The fourth section is concerned with intervention. It provides an overview of the use of NFB plus BFB for managing the symptoms of AS. It provides a summary of what to do, and a discussion of why it is effective.
Effects of a Neurofeedback-Based Alpha Training on Chronic TinnitusBackground: In Germany alone approximately 340 000 people are affected by chronic tinnitus. Chronic tinnitus, i.e. permanent and constant symptoms for at least 3 months cannot be cured by medicines. Psychotherapeutic treatment however is standard practice in order to reduce subjective annoyance due to chronic tinnitus. Patient and Method: The following case study investigates the therapeutic effects of neurofeedback-based alpha training on a 56-year-old female tinnitus patient. At the beginning of the therapy the patient suffered from preoccupation with the core tinnitus symptom, difficulties in relaxation and sleeping, episodes of anxiety and depressive moods, i.e. from symptoms often experienced by chronic tinnitus patients. The therapy was performed on an out-patient basis and included thorough counselling and 15 sessions of neurofeedback-based alpha training within 4 weeks. Results: At discharge from therapy, the patient was capable of promoting her alpha activity and reducing her physiological arousal. The favourable course of the therapy becomes particularly obvious in the reduction of the subjective tinnitus annoyance. A significant reduction in stress due to the ear noise was achieved by the end of the therapy and could still be maintained at 6-month follow-up. Conclusion: The results indicate that neurofeedback represents a new promising technique in the therapy of chronic tinnitus and deserves further research efforts.
Previously we demonstrated significant improvement of executive functions and social behavior in children with autism spectrum disorders (ASD) treated with 40 sessions of EEG neurofeedback in a nonrandomized waiting list control group design. In this paper we extend these findings by reporting the long-term results of neurofeedback treatment in the same group of children with ASD after 12 months. The present study indicates maintenance of improvement of executive functions and social behavior after 12 months in comparison with the immediate outcomes. Neurofeedback mediated suppression of theta power is supposed to promote more flexible functioning of the brain by enhancing activation in the medial prefrontal cortex and improving flexibility of activation in the default mode network supporting the improvement of executive functions and theory of mind in ASD.
This paper briefly reviews traditional thinking concerning Attention-Deficit/Hyperactivity Disorder in adult populations and then discusses neurofeedback (EEG biofeedback) as a helpful addition to the range of interventions. It reports clinical findings and observations that lead to effective interventions with adults and point the way to future research. Since EEG patterns differ in those with and without ADHD (Monastra et al., 1999) and since operant conditioning of brain wave patterns is possible (as reviewed by Sterman (2000)), it follows that people can learn how to produce EEG activity that is associated with being calm and alert and thus control their ADHD symptoms. Being able to change the brain with neurofeedback training is consistent with the new discoveries about neuroplasticity in adult brains. Studies indicate that there is growth of new dendrites and production of new neurons even late in life (Snowden, 2001).
Eighteen children with ADD/ADHD, some of whom were also LD, ranging in ages from 5 through 15 were randomly assigned to one of two conditions. The experimental condition consisted of 40 45-minute sessions of training in enhancing beta activity and suppressing theta activity, spaced over 6 months. The control condition, waiting list group, received no EEG biofeedback. No other psychological treatment or medication was administered to any subjects. All subjects were measured at pretreatment and at posttreatment on an IQ test and parent behavior rating scales for inattention, hyperactivity, and aggressive/defiant (oppositional) behaviors. At posttreatment the experimental group demonstrated a significant increase (mean of 9 points) on the K-Bit IQ Composite as compared to the control group (p<.05). The experimental group also significantly reduced inattentive behaviors as rated by parents (p<.05). The significant improvements in intellectual functioning and attentive behaviors might be explained as a result of the attentional enhancement affected by EEG biofeedback training. Further research utilizing improved data collection and analysis, more stringent control groups, and larger sample sizes are needed to support and replicate these findings.
We report on the feasibility of teaching 16 (DSM-IV) schizophrenic patients, subdivided by syndrome, self-regulation of interhemispheric asymmetry having demonstrated efficient learning of interhemispheric control in normal subjects. Reversal of asymmetry may be important to treatment and recovery in schizophrenia for following improvement on neuroleptic drugs functional hemispheric asymmetries have reversed, with directions of reversal and pre-existing asymmetry dependent on syndrome. Asymmetry reversal in animals, manifested by spatial turning tendencies, has been used as a marker of neuroleptic action and involves striatal dopamine under reciprocal hemispheric control. We gave as feedback the left right asymmetry in slow potential negativity recorded from the sensory motor strip (C3,4). Feedback took the form of a rocket on a screen which rose or fell with leftward or rightward shifts in negativity. Patients were able to learn control (P < 0.01). In those patients with lesser ability this was due to inability to sustain concentration throughout the session rather than slow initial learning. Active syndrome patients were better able to shift negativity rightward and withdrawn patients leftward, directions associated with drug reversal of functional asymmetry and symptom recovery for each syndrome. Accordingly our demonstration that many symptomatic schizophrenic patients are capable of learning control opens the door to electrocortical operant conditioning training in schizophrenia with therapeutic regimens.
Neurofeedback has been around for decades and has applications for both clinical and healthy populations yet there is no standard method for measuring learning or a way of defining successful learning. Thus the aim of this study was to focus on alpha neurofeedback and examine changes in three different measures: amplitude, percent time, and integrated alpha, across four methods: within sessions, across sessions, within sessions compared to baseline, and across sessions compared to baseline. Participants completed 10 weekly sessions of eyes open alpha (8-12 Hz) neurofeedback training (NFT) at Pz. Whilst all three measures showed changes within sessions, the inclusion of baselines revealed that such changes represented a return to baseline levels rather than an increase in alpha. Changes across sessions were only evident in amplitude and inclusion of baseline showed that NFT did not elicit any changes beyond baseline levels. Given this a case is made for incorporating baseline measures when attempting to identify evidence of learning. It is also suggested that both amplitude and percent time measures are used independently rather than incorporate them into a more conservative and less sensitive integrated measure. Finally, focusing on within sessions changes may be a more useful approach in identifying changes resulting from NFT.
To test whether instrumental conditioning of sensorimotor rhythm (SMR; 12-15 Hz) has an impact on sleep parameters as well as declarative memory performance in humans.
Randomized, parallel group design
10 instrumental conditioning sessions, pre- and posttreatment investigation including sleep evaluations
27 healthy subjects (13 male) Interventions: SMR-conditioning (experimental group) or randomized-frequency conditioning (control group); declarative memory task before and after a 90-min nap
The experimental group was trained to enhance the amplitude of their SMR-frequency range, whereas the control group participated in a randomized-frequency conditioning program (i.e., every session a different 3-Hz frequency bin between 7 and 20 Hz). During pre- and posttreatment the subjects had to attend the sleep laboratory to take a 90-min nap (2:00-3:30 pm) and to perform a declarative memory task before and after sleep. The experimental design was successful in conditioning an increase in relative 12-15 Hz amplitude within 10 sessions (d = 0.7). Increased SMR activity was also expressed during subsequent sleep by eliciting positive changes in different sleep parameters (sleep spindle number [d = 0.6], sleep onset latency [d = 0.7]); additionally, this increased 12-15 Hz amplitude was associated with enhancement in retrieval score computed at immediate cued recall (d = 0.9).
Relative SMR amplitude increased over 10 instrumental conditioning sessions (in the experimental group only) and this "shaping of one's own brain activity" improved subsequent declarative learning and facilitated the expression of 12-15 Hz spindle oscillations during sleep. Most interestingly, these electrophysiological changes were accompanied by a shortened sleep onset latency.
This study compared changes in quantitative EEG (QEEG) and CNV (contingent negative variation) of children suffering from ADHD treated by SCP (slow cortical potential) neurofeedback (NF) with the effects of group therapy (GT) to separate specific from non-specific neurophysiological effects of NF. Twenty-six children (age: 11.1 +/- 1.15 years) diagnosed as having ADHD were assigned to NF (N = 14) or GT (N = 12) training groups. QEEG measures at rest, CNV and behavioral ratings were acquired before and after the trainings and statistically analyzed. For children with ADHD-combined type in the NF group, treatment effects indicated a tendency toward improvement of selected QEEG markers. We could not find the expected improvement of CNV, but CNV reduction was less pronounced in good NF performers. QEEG changes were associated with some behavioral scales. Analyses of subgroups suggested specific influences of SCP training on brain functions. To conclude, SCP neurofeedback improves only selected attentional brain functions as measurable with QEEG at rest or CNV mapping. Effects of neurofeedback including the advantage of NF over GT seem mediated by both specific and non-specific factors.
The present study aimed at investigating to what extent the regulation of excitability in cortical networks, as indicated by surface-negative slow cortical potentials (SCPs), is impaired in epileptic patients and to what extent training of SCP self-regulation by means of biofeedback and instrumental learning procedures might affect seizure frequency. Twenty-five patients suffering from drug-refractory epilepsies (complex focal, grand mal, and absence type of seizures) participated in 28 1-h sessions of feedback and instrumental conditioning of their SCPs. Subjects' EEGs were obtained from the vertex. Depending on discriminative stimuli DC shifts towards increased or suppressed negativity relative to the pre-trial baseline were demonstrated by on-line visual feedback during intervals of 8 s each; each session comprised 110 trials. While performance on the SCP self-regulation task was initially below normal (as compared to healthy subjects), significant increases in SCP control were achieved by the patients across the 28 training sessions. In 18 patients at least 1-year follow-up data are available. Changes in seizure frequency were related to transfer of SCP control with six of the patients becoming seizure-free. Age affected the ability to acquire SCP control and its impact on seizure frequency.
Eighteen children with ADD/ADHD, some of whom were also LD, ranging in ages from 5 through 15 were randomly assigned to one of two conditions. The experimental condition consisted of 40 45-minute sessions of training in enhancing beta activity and suppressing theta activity, spaced over 6 months. The control condition, waiting list group, received no EEG biofeedback. No other psychological treatment or medication was administered to any subjects. All subjects were measured at pretreatment and at posttreatment on an IQ test and parent behavior rating scales for inattention, hyperactivity, and aggressive/defiant (oppositional) behaviors. At posttreatment the experimental group demonstrated a significant increase (mean of 9 points) on the K-Bit IQ Composite as compared to the control group (p <.05). The experimental group also significantly reduced inattentive behaviors as rated by parents (p < .05). The significant improvements in intellectual functioning and attentive behaviors might be explained as a result of the attentional enhancement affected by EEG biofeedback training. Further research utilizing improved data collection and analysis, more stringent control groups, and larger sample sizes are needed to support and replicate these findings.
Migraine patients are characterized by increased amplitudes of slow cortical potentials (SCPs), representing pronounced excitability of cortical networks. The present study investigated the efficiency of biofeedback training of SCPs in young migraineurs. Ten children suffering from migraine without aura participated in 10 feedback sessions. They were compared with 10 healthy children for regulation abilities of cortical negativity and with 10 migraineurs from the waiting list for clinical efficacy. During the first two sessions, the migraine children were characterised by lacking ability to control cortical negativity, especially during transfer trials, compared with healthy controls. However, there was no difference following 10 sessions of training. Feedback training was accompanied by significant reduction of cortical excitability. This was probably responsible for the clinical efficacy of the training; a significant reduction of days with migraine and other headache parameters was observed. It is suggested that normalization of the threshold regulation of cortical excitability during feedback training may result in clinical improvement.
To compare self-regulation of low-frequency EEG components (slow cortical potentials, SCPs) with other methods of seizure control for patients with drug-refractory partial epilepsy and to separate the real anticonvulsive effect from placebo effects.
Results of a treatment program of SCP self-regulation (experimental group) are compared with two groups of patients, one of which learned self-control of respiratory parameters (end-tidal CO2 and respiration rate: RES group); the other received medication with new anticonvulsive drugs (AEDs) in combination with psychosocial counseling (MED group). Clinical, cognitive, behavioral, and personality measures were assessed before and after treatment. In addition, to control for placebo responses, patients repeatedly estimated their beliefs in the efficiency of the respective treatment, their satisfaction and expectations, and the quality of the relationship with their therapists.
SCP and MED groups showed a significant decrease of seizure frequency, but the RES group did not. Clear positive changes in the sociopsychological adjustment were obtained in all three groups, with the maximal improvement being attained in the RES group.
All kinds of therapy result in considerable improvement of patients' emotional state, which may in part be due to potential placebo effects: however, this improvement is not related to the quality of the therapeutic effect proper (i.e., seizure reduction). Traditional double-blind control group designs are inappropriate for behavioral interventions or treatments with psychoactive pharmacologic drugs. Rather, specific tests can be developed to control the placebo effect and to separate it from the genuine therapeutic effects.
The use of neurofeedback as an operant conditioning paradigm has disclosed that participants are able to gain some control over particular aspects of their electroencephalogram (EEG). Based on the association between theta activity (4-7 Hz) and working memory performance, and sensorimotor rhythm (SMR) activity (12-15 Hz) and attentional processing, we investigated the possibility that training healthy individuals to enhance either of these frequencies would specifically influence a particular aspect of cognitive performance, relative to a non-neurofeedback control-group. The results revealed that after eight sessions of neurofeedback the SMR-group were able to selectively enhance their SMR activity, as indexed by increased SMR/theta and SMR/beta ratios. In contrast, those trained to selectively enhance theta activity failed to exhibit any changes in their EEG. Furthermore, the SMR-group exhibited a significant and clear improvement in cued recall performance, using a semantic working memory task, and to a lesser extent showed improved accuracy of focused attentional processing using a 2-sequence continuous performance task. This suggests that normal healthy individuals can learn to increase a specific component of their EEG activity, and that such enhanced activity may facilitate semantic processing in a working memory task and to a lesser extent focused attention. We discuss possible mechanisms that could mediate such effects and indicate a number of directions for future research.
Biofeedback-assisted modulation of electrocortical activity has been established to have intrinsic clinical benefits and has been shown to improve cognitive performance in healthy humans. In order to further investigate the pedagogic relevance of electroencephalograph (EEG) biofeedback (neurofeedback) for enhancing normal function, a series of investigations assessed the training's impact on an ecologically valid real-life behavioural performance measure: music performance under stressful conditions in conservatoire students. In a pilot study, single-blind expert ratings documented improvements in musical performance in a student group that received training on attention and relaxation related neurofeedback protocols, and improvements were highly correlated with learning to progressively raise theta (5-8 Hz) over alpha (8-11 Hz) band amplitudes. These findings were replicated in a second experiment where an alpha/theta training group displayed significant performance enhancement not found with other neurofeedback training protocols or in alternative interventions, including the widely applied Alexander technique.
To test a common assumption underlying the clinical use of electroencephalographic (EEG) biofeedback training (neurofeedback), that the modulation of discreet frequency bands is associated with frequency-specific effects. Specifically, the proposal was assessed that enhancement of the low beta components sensorimotor rhythm (SMR: 12-15 Hz) and beta1 (15-18 Hz) affect different aspects of attentional processing.
Subjects (n=25) were randomly allocated to training with either an SMR or beta1 protocol, or to a non-neurofeedback control group. Subjects were assessed prior and subsequent to the training process on two tests of sustained attention. The neurofeedback participants were also assessed on target P300 event-related potential (ERP) amplitudes in a traditional auditory oddball paradigm.
Protocol-specific effects were obtained in that SMR training was associated with increased perceptual sensitivity 'd prime' (d'), and reduced omission errors and reaction time variability. Beta1 training was associated with faster reaction times and increased target P300 amplitudes, whereas no changes were evident in the control group.
Neurofeedback training of SMR and beta1 band components led to significant and protocol-specific effects in healthy subjects. The data can be interpreted as indicating a general attention-enhancing effect of SMR training, and an arousal-enhancing effect of beta1 training.
With electroencephalographic (EEG) biofeedback (or neurofeedback), it is possible to train the brain to de-emphasize rhythms that lead to generation and propagation of seizure and emphasize rhythms that make seizures less likely to occur. With recent improvements in quantitative EEG measurement and improved neurofeedback protocols, it has become possible in clinical practice to eliminate seizures or reduce the amount of medication required to control them. In this article, the history of neurofeedback for epilepsy is presented followed by discussions of the relevant neurophysiology of epilepsy. A model of how neurofeedback might raise the seizure threshold is then presented. Clinical experience using a quantitative EEG-guided approach is described, including a representative case study.
Alpha/theta neurofeedback has been shown to be successful both in treating addictions and in enhancing artistry in music students. How its effects are mediated are not yet clear. The present study aimed to test the hypothesis that alpha/theta neurofeedback works inter alia by normalising extreme personality and raising feelings of well being. 12 participants with high scores for Withdrawal (as measured by the PSQ) were given either alpha/theta neurofeedback or mock feedback and their personality and mood were assessed. Withdrawal scores on the PSQ-80 were not found to change in either group but significant effects were found for the Profile Of Mood States (POMS), with real feedback producing higher overall scores than mock feedback (P = 0.056). Real feedback caused participants to feel significantly more energetic (P < 0.01) than did mock feedback. Sessions of real feedback made participants feel more composed (P < 0.01), agreeable (P < 0.01), elevated (P < 0.01) and confident (P < 0.05), whilst sessions of mock feedback made participants feel more tired (P < 0.05), yet composed (P < 0.01). These findings suggest that, whilst 9 sessions of alpha/theta neurofeedback was insufficient to change personality, improvements in mood may provide a partial explanation for the efficacy of alpha/theta neurofeedback.
The hypothesis was tested of whether neurofeedback training (NFT)--applied in order to increase upper alpha but decrease theta power--is capable of increasing cognitive performance. A mental rotation task was performed before and after upper alpha and theta NFT. Only those subjects who were able to increase their upper alpha power (responders) performed better on mental rotations after NFT. Training success (extent of NFT-induced increase in upper alpha power) was positively correlated with the improvement in cognitive performance. Furthermore, the EEG of NFT responders showed a significant increase in reference upper alpha power (i.e. in a time interval preceding mental rotation). This is in line with studies showing that increased upper alpha power in a prestimulus (reference) interval is related to good cognitive performance.