EEG Neurofeedback Is Under Strong Control of Psychosocial Factors

Analyzing and computing humans by means of the brain using Brain-Computer Interfaces - understanding the user - previous evidence, self-relevance and the user's self-concept as potential superordinate human factors of relevance

Brain-computer interfaces (BCIs) are well-known instances of how technology can convert a user's brain activity taken from non-invasive electroencephalography (EEG) into computer commands for the purpose of computer-assisted communication and interaction. However, not all users are attaining the accuracy required to use a BCI consistently, despite advancements in technology. Accordingly, previous research suggests that human factors could be responsible for the variance in BCI performance among users. Therefore, the user's internal mental states and traits including motivation, affect or cognition, personality traits, or the user's satisfaction, beliefs or trust in the technology have been investigated. Going a step further, this manuscript aims to discuss which human factors could be potential superordinate factors that influence BCI performance, implicitly, explicitly as well as inter- and intraindividually. Based on the results of previous studies that used comparable protocols to examine the motivational, affective, cognitive state or personality traits of healthy and vulnerable EEG-BCI users within and across well-investigated BCIs (P300-BCIs or SMR-BCIs, respectively), it is proposed that the self-relevance of tasks and stimuli and the user's self-concept provide a huge potential for BCI applications. As potential key human factors self-relevance and the user's self-concept (self-referential knowledge and beliefs about one's self) guide information processing and modulate the user's motivation, attention, or feelings of ownership, agency, and autonomy. Changes in the self-relevance of tasks and stimuli as well as self-referential processing related to one's self (self-concept) trigger changes in neurophysiological activity in specific brain networks relevant to BCI. Accordingly, concrete examples will be provided to discuss how past and future research could incorporate self-relevance and the user's self-concept in the BCI setting - including paradigms, user instructions, and training sessions.

Neurofeedback on twitter: Evaluation of the scientific credibility and communication about the technique

Neurofeedback is a popular technique to induce neuroplasticity with a controversial reputation. The public discourse on neurofeedback, as a therapeutic and neuroenhancement technique, encompasses scientific communication, therapeutic expectations and outcomes, as well as complementary and alternative practices. We investigated twitter publications from 2010 to 2022 on the keyword "neurofeedback". A total of over 138 k tweets were obtained, which originated from over 42 k different users. The communication flow in the neurofeedback community is mainly unidirectional and non-interactive. Analysis of hashtags revealed application fields, therapy provider and neuroenhancement to be the most popular contents in neurofeedback communication. A group of 1221 productive users was identified, in which clinicians, entrepreneurs, broadcasters, and scientists contribute. We identified reactions to critical publications in the twitter traffic and an increase in the number of tweets by academic users which suggest an increase in the interest on the scientific credibility of neurofeedback. More intense scientific communication on neurofeedback in twitter may contribute to promote a more realistic view on challenges and advances regarding good scientific practice of neurofeedback.

Assessment of the capacity to modulate brain signals in a home-based SMR neurofeedback training setting

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.

Self-modulation of motor cortex activity after stroke: a randomized controlled trial

Real-time functional MRI neurofeedback allows individuals to self-modulate their ongoing brain activity. This may be a useful tool in clinical disorders that are associated with altered brain activity patterns. Motor impairment after stroke has previously been associated with decreased laterality of motor cortex activity. Here we examined whether chronic stroke survivors were able to use real-time fMRI neurofeedback to increase laterality of motor cortex activity and assessed effects on motor performance and on brain structure and function.

We carried out a randomized, double-blind, sham-controlled trial (ClinicalTrials.gov: NCT03775915) in which 24 chronic stroke survivors with mild to moderate upper limb impairment experienced three training days of either Real (n = 12) or Sham (n = 12) neurofeedback. Assessments of brain structure, brain function and measures of upper-limb function were carried out before and 1 week after neurofeedback training. Additionally, measures of upper-limb function were repeated 1 month after neurofeedback training. Primary outcome measures were (i) changes in lateralization of motor cortex activity during movements of the stroke-affected hand throughout neurofeedback training days; and (ii) changes in motor performance of the affected limb on the Jebsen Taylor Test (JTT).

Stroke survivors were able to use Real neurofeedback to increase laterality of motor cortex activity within (P = 0.019), but not across, training days. There was no group effect on the primary behavioural outcome measure, which was average JTT performance across all subtasks (P = 0.116). Secondary analysis found improvements in the performance of the gross motor subtasks of the JTT in the Real neurofeedback group compared to Sham (P = 0.010). However, there were no improvements on the Action Research Arm Test or the Upper Extremity Fugl–Meyer score (both P > 0.5). Additionally, decreased white-matter asymmetry of the corticospinal tracts was detected 1 week after neurofeedback training (P = 0.008), indicating that the tracts become more similar with Real neurofeedback. Changes in the affected corticospinal tract were positively correlated with participants neurofeedback performance (P = 0.002).

Therefore, here we demonstrate that chronic stroke survivors are able to use functional MRI neurofeedback to self-modulate motor cortex activity in comparison to a Sham control, and that training is associated with improvements in gross hand motor performance and with white matter structural changes.

Brain Synchrony in Competition and Collaboration During Multiuser Neurofeedback-Based Gaming

EEG hyperscanning during multiuser gaming offers opportunities to study brain characteristics of social interaction under various paradigms. In this study, we aimed to characterize neural signatures and phase-based functional connectivity patterns of gaming strategies during collaborative and competitive alpha neurofeedback games. Twenty pairs of participants with no close relationship took part in three sessions of collaborative or competitive multiuser neurofeedback (NF), with identical graphical user interface, using Relative Alpha (RA) power as a control signal. Collaborating dyads had to keep their RA within 5% of each other for the team to be awarded a point, while members of competitive dyads scored points if their RA was 10% above their opponent's. Interbrain synchrony existed only during gaming but not during baseline in either collaborative or competitive gaming. Spectral analysis and interbrain connectivity showed that in collaborative gaming, players with higher resting state alpha content were more active in regulating their RA to match those of their partner. Moreover, interconnectivity was the strongest between homologous brain structures of the dyad in theta and alpha bands, indicating a similar degree of planning and social exchange. Competitive gaming emphasized the difference between participants who were able to relax and, in this way, maintain RA, and those who had an unsuccessful approach. Analysis of interbrain connections shows engagement of frontal areas in losers, but not in winners, indicating the formers' attempt to mentalise and apply strategies that might be suitable for conventional gaming, but inappropriate for the alpha neurofeedback-based game. We show that in gaming based on multiplayer non-verbalized NF, the winning strategy is dependent on the rules of the game and on the behavior of the opponent. Mental strategies that characterize successful gaming in the physical world might not be adequate for NF-based gaming.

Neurotherapeutics for Attention Deficit/Hyperactivity Disorder (ADHD): A Review

This review focuses on the evidence for neurotherapeutics for attention deficit/hyperactivity disorder (ADHD). EEG-neurofeedback has been tested for about 45 years, with the latest meta-analyses of randomised controlled trials (RCT) showing small/medium effects compared to non-active controls only. Three small studies piloted neurofeedback of frontal activations in ADHD using functional magnetic resonance imaging or near-infrared spectroscopy, finding no superior effects over control conditions. Brain stimulation has been applied to ADHD using mostly repetitive transcranial magnetic and direct current stimulation (rTMS/tDCS). rTMS has shown mostly negative findings on improving cognition or symptoms. Meta-analyses of tDCS studies targeting mostly the dorsolateral prefrontal cortex show small effects on cognitive improvements with only two out of three studies showing clinical improvements. Trigeminal nerve stimulation has been shown to improve ADHD symptoms with medium effect in one RCT. Modern neurotherapeutics are attractive due to their relative safety and potential neuroplastic effects. However, they need to be thoroughly tested for clinical and cognitive efficacy across settings and beyond core symptoms and for their potential for individualised treatment.

The Impact of Context on EEG Motor Imagery Neurofeedback and Related Motor Domains

Neurofeedback (NF) is a versatile non-invasive neuromodulation technique. In combination with motor imagery (MI), NF has considerable potential for enhancing motor performance or supplementing motor rehabilitation. However, not all users achieve reliable NF control. While research has focused on various brain signal properties and the optimisation of signal processing to solve this issue, the impact of context, i.e. the conditions in which NF motor tasks occur, is comparatively unknown. We review current research on the impact of context on MI NF and related motor domains. We identify long-term factors that act at the level of the individual or of the intervention, and short-term factors, with levels before/after and during a session. The reviewed literature indicates that context plays a significant role. We propose considering context factors as well as within-level and across-level interactions when studying MI NF.

A randomized-controlled neurofeedback trial in adult attention-deficit/hyperactivity disorder

Attention-deficit/hyperactivity disorder (ADHD) is a childhood onset disorder persisting into adulthood for a large proportion of cases. Neurofeedback (NF) has shown promising results in children with ADHD, but randomized controlled trials in adults with ADHD are scarce. We aimed to compare slow cortical potential (SCP)- and functional near-infrared spectroscopy (fNIRS) NF to a semi-active electromyography biofeedback (EMG-BF) control condition regarding changes in symptoms and the impact of learning success, as well as changes in neurophysiological parameters in an adult ADHD population. Patients were randomly assigned to SCP-NF (n = 26), fNIRS-NF (n = 21) or EMG-BF (n = 20). Outcome parameters were assessed over 30 training sessions (pre, intermediate, post) and at 6-months follow-up (FU) including 3 booster sessions. EEG was recorded during two auditory Go/NoGo paradigms assessing the P300 and contingent negative variation (CNV). fNIRS measurements were conducted during an n-back- as well as a Go/NoGo task. All three groups showed equally significant symptom improvements suggesting placebo- or non-specific effects on the primary outcome measure. Only when differentiating between learners and non-learners, fNIRS learners displayed stronger reduction of ADHD global scores compared to SCP non-learners at FU, and fNIRS learners showed specifically low impulsivity ratings. 30.8% in the SCP-NF and 61.9% of participants in the fNIRS-NF learned to regulate the respective NF target parameter. We conclude that some adults with ADHD learn to regulate SCP amplitudes and especially prefrontal hemodynamic activity during NF. We did not find any significant differences in outcome between groups when looking at the whole sample. When evaluating learners only, they demonstrate superior effects as compared to non-learners, which suggests specific effects in addition to non-specific effects of NF when learning occurs.

Vividness of Visual Imagery and Personality Impact Motor-Imagery Brain Computer Interfaces

Brain-computer interfaces (BCIs) are communication bridges between a human brain and external world, enabling humans to interact with their environment without muscle intervention. Their functionality, therefore, depends on both the BCI system and the cognitive capacities of the user. Motor-imagery BCIs (MI-BCI) rely on the users' mental imagination of body movements. However, not all users have the ability to sufficiently modulate their brain activity for control of a MI-BCI; a problem known as BCI illiteracy or inefficiency. The underlying mechanism of this phenomenon and the cause of such difference among users is yet not fully understood. In this study, we investigated the impact of several cognitive and psychological measures on MI-BCI performance. Fifty-five novice BCI-users participated in a left- versus right-hand motor imagery task. In addition to their BCI classification error rate and demographics, psychological measures including personality factors, affinity for technology, and motivation during the experiment, as well as cognitive measures including visuospatial memory and spatial ability and Vividness of Visual Imagery were collected. Factors that were found to have a significant impact on MI-BCI performance were Vividness of Visual Imagery, and the personality factors of orderliness and autonomy. These findings shed light on individual traits that lead to difficulty in BCI operation and hence can help with early prediction of inefficiency among users to optimize training for them.

Multi-Session Influence of Two Modalities of Feedback and Their Order of Presentation on MI-BCI User Training

By performing motor-imagery tasks, for example, imagining hand movements, Motor-Imagery based Brain-Computer Interfaces (MI-BCIs) users can control digital technologies, for example, neuroprosthesis, using their brain activity only. MI-BCI users need to train, usually using a unimodal visual feedback, to produce brain activity patterns that are recognizable by the system. The literature indicates that multimodal vibrotactile and visual feedback is more effective than unimodal visual feedback, at least for short term training. However, the multi-session influence of such multimodal feedback on MI-BCI user training remained unknown, so did the influence of the order of presentation of the feedback modalities. In our experiment, 16 participants trained to control a MI-BCI during five sessions with a realistic visual feedback and five others with both a realistic visual feedback and a vibrotactile one. training benefits from a multimodal feedback, in terms of performances and self-reported mindfulness. There is also a significant influence of the order presentation of the modality. Participants who started training with a visual feedback had higher performances than those who started training with a multimodal feedback. We recommend taking into account the order of presentation for future experiments assessing the influence of several modalities of feedback.

Neurofeedback training in major depressive disorder: A systematic review of clinical efficacy, study quality and reporting practices

Major depressive disorder (MDD) is the leading cause of disability worldwide. Neurofeedback training has been suggested as a potential additional treatment option for MDD patients not reaching remission from standard care (i.e., psychopharmacology and psychotherapy). Here we systematically reviewed neurofeedback studies employing electroencephalography, or functional magnetic resonance-based protocols in depressive patients. Of 585 initially screened studies, 24 were included in our final sample (N = 480 patients in experimental and N = 194 in the control groups completing the primary endpoint). We evaluated the clinical efficacy across studies and attempted to group studies according to the control condition categories currently used in the field that affect clinical outcomes in group comparisons. In most studies, MDD patients showed symptom improvement superior to the control group(s). However, most articles did not comply with the most stringent study quality and reporting practices. We conclude with recommendations on best practices for experimental designs and reporting standards for neurofeedback training.

A review of user training methods in brain computer interfaces based on mental tasks

Mental-Tasks based Brain-Computer Interfaces (MT-BCIs) allow their users to interact with an external device solely by using brain signals produced through mental tasks. While MT-BCIs are promising for many applications, they are still barely used outside laboratories due to their lack of reliability. MT-BCIs require their users to develop the ability to self-regulate specific brain signals. However, the human learning process to control a BCI is still relatively poorly understood and how to optimally train this ability is currently under investigation. Despite their promises and achievements, traditional training programs have been shown to be sub-optimal and could be further improved. In order to optimize user training and improve BCI performance, human factors should be taken into account. An interdisciplinary approach should be adopted to provide learners with appropriate and/or adaptive training. In this article, we provide an overview of existing methods for MT-BCI user training - notably in terms of environment, instructions, feedback and exercises. We present a categorization and taxonomy of these training approaches, provide guidelines on how to choose the best methods and identify open challenges and perspectives to further improve MT-BCI user training.

How Much Do Strategy Reports Tell About the Outcomes of Neurofeedback Training? A Study on the Voluntary Up-Regulation of the Sensorimotor Rhythm

The core learning mechanisms of neurofeedback (NF) training are associative, implicit, and, consequently, largely impervious to consciousness. Many other aspects of training that determine training outcomes, however, are accessible to conscious processing. The outcomes of sensorimotor rhythm (SMR) up-regulation training are related to the strategies reported by participants. The classification methods of individual strategies employed hitherto were possibly under influence of the idiosyncratic interpretation of the rater. To measure and possibly overcome this limitation, we employed independent raters to analyze strategies reported during SMR up-regulation training. Sixty-two healthy young participants took part in a single session of SMR up-regulation training. After completing six blocks of training, in which they received either simple visual feedback or a gamified version thereof, participants were required to report the strategies employed. Their individual learning outcomes were computed as well. Results point out that individual strategies as well as NF learning outcomes were not particularly sensitive to the presence of gamified elements in training the SMR up-regulation. A high degree of consistency across independent raters classifying strategy reports was observed. Some strategies were more typical of responders while other ones were more common among non-responders. In summary, we demonstrate a more objective and transparent way to analyze individual mental strategies to shed more light on the differences between NF responders and non-responders.

Consensus on the reporting and experimental design of clinical and cognitive-behavioural neurofeedback studies (CRED-nf checklist)

Neurofeedback has begun to attract the attention and scrutiny of the scientific and medical mainstream. Here, neurofeedback researchers present a consensus-derived checklist that aims to improve the reporting and experimental design standards in the field.

Home used, patient self-managed, brain-computer interface for the management of central neuropathic pain post spinal cord injury: usability study

BACKGROUND

Central Neuropathic Pain (CNP) is a frequent chronic condition in people with spinal cord injury (SCI). Previously, we showed that using laboratory brain-computer interface (BCI) technology for neurofeedback (NFB) training, it was possible to reduce CNP in people with SCI. In this study, we show results of patient self-managed treatment in their homes with a BCI-NFB using a consumer EEG device.

METHODS

Users: People with chronic SCI (17 M, 3 F, 50.6 ± 14.1 years old), and CNP ≥4 on a Visual Numerical Scale.

LOCATION

Laboratory training (up to 4 sessions) followed by home self-managed NFB. User Activity: Upregulating the EEG alpha band power by 10% above a threshold and at the same time downregulating the theta and upper beta (20-30 Hz) band power by 10% at electrode location C4. Technology: A consumer grade multichannel EEG headset (Epoch, Emotiv, USA), a tablet computer and custom made NFB software.

EVALUATION

EEG analysis, before and after NFB assessment, interviews and questionnaires.

RESULTS

Effectiveness: Out of 20 initially assessed participants, 15 took part in the study. Participants used the system for 6.9 ± 5.5 (median 4) weeks. Twelve participants regulated their brainwaves in a frequency specific manner and were most successful upregulating the alpha band power. However they typically upregulated power around their individual alpha peak (7.6 ± 0.8 Hz) that was lower than in people without CNP. The reduction in pain experienced was statistically significant in 12 and clinically significant (greater than 30%) in 8 participants. Efficiency: The donning was between 5 and 15 min, and approximately 10-20% of EEG data recorded in the home environment was noise. Participants were mildly stressed when self-administering NFB at home (2.4 on a scale 1-10). User satisfaction: Nine participants who completed the final assessment reported a high level of satisfaction (QUESQ, 4.5 ± 0.8), naming effectiveness, ease of use and comfort as main priorities. The main factors influencing frequency of NFB training were: health related issues, free time and pain intensity.

CONCLUSION

Portable NFB is a feasible solution for home-based self-managed treatment of CNP. Compared to pharmacological treatments, NFB has less side effects and provides users with active control over pain.

TRIAL REGISTRATION

GN15NE124 , Registered 9th June 2016.

Brainwave Self-Regulation During Bispectral IndexTM Neurofeedback in Trauma Center Nurses and Physicians After Receiving Mindfulness Instructions

Fifty-seven level I trauma center nurses/physicians participated in a 4-day intervention to learn relaxed alertness using mindfulness-based instructions and EEG neurofeedback. Neurofeedback was provided by a Bispectral Index^TM (BIS) system that continuously displays a BIS value (0-100) on the monitor screen. Reductions in the BIS value indicate that power in a high-frequency band (30-47 Hz) is decreased and power in an intermediate band (11-20 Hz) is increased. A wellbeing tool with four positive affect and seven negative affect items based on a 5-category Likert scale was used. The wellbeing score is the sum of the positive affect items (positive affect score) and the reverse-scored negative affect items (non-stress score). Of functional concern were four negative affect items rated as moderately, quite a bit, or extremely in a large percent. Of greater concern were all four positive affect items rated as very slightly or none at all, a little, or moderately in over half of the participants. Mean and nadir BIS values were markedly decreased during neurofeedback when compared to baseline values. Post-session relaxation scores were higher than pre-session relaxation scores. Post-session relaxation scores had an inverse relationship with mean and nadir BIS values. Mean and nadir BIS values were inversely associated with NFB cognitive states (i.e., widening the visual field, decreasing effort, attention to space, and relaxed alertness). For all participants, the wellbeing score was higher on day 4 than on day 1. Participants had a higher wellbeing score on day 4 than a larger group of nurses/physicians who did not participate in the BIS neurofeedback trial. Eighty percent of participants demonstrated an improvement in the positive affect or non-stress score on day 4, when compared to day 1; the wellbeing, non-stress, and positive affect scores were substantially higher on day 4 than on day 1. Additionally, for that 80% of participants, the improvements in wellbeing and non-stress were associated with reductions in day 3 BIS values. These findings indicate that trauma center nurses/physicians participating in an EEG neurofeedback trial with mindfulness instructions had improvements in wellbeing. Clinical Trial Registration: www.ClinicalTrials.gov, identifier NCT03152331. Registered May 15, 2017.

EEG Correlates of Self-Managed Neurofeedback Treatment of Central Neuropathic Pain in Chronic Spinal Cord Injury

BACKGROUND

Neurofeedback (NFB) is a neuromodulatory technique that enables voluntary modulation of brain activity in order to treat neurological condition, such as central neuropathic pain (CNP). A distinctive feature of this technique is that it actively involves participants in the therapy. In this feasibility study, we present results of participant self-managed NFB treatment of CNP.

METHODS

Fifteen chronic spinal cord injured (SCI) participants (13M, 2F), with chronic CNP equal or greater than 4 on the Visual Numeric Scale, took part in the study. After initial training in hospital (up to 4 sessions), they practiced NF at home, on average 2-3 times a week, over a period of several weeks (min 4, max 20). The NFB protocol consisted of upregulating the alpha (9-12 Hz) and downregulating the theta (4-8 Hz) and the higher beta band (20-30 Hz) power from electrode location C4, for 30 min. The output measures were pain before and after NFB, EEG before and during NFB and pain questionnaires. We analyzed EEG results and show NFB strategies based on the Power Spectrum Density of each single participant.

RESULTS

Twelve participants achieved statistically significant reduction in pain and in eight participants this reduction was clinically significant (larger than 30%). The most successfully regulated frequency band during NFB was alpha. However, most participants upregulated their individual alpha band, that had an average dominant frequency at αp = 7.6 ± 0.8 Hz (median 8 Hz) that is lower than the average of the general population, which is around 10 Hz. Ten out of fifteen participants significantly upregulated their individual alpha power (αp ± 2 Hz) as compared to 4 participants who upregulated the power in the fixed alpha band (8-12 Hz). Eight out of the twelve participants who achieved a significant reduction of pain, significantly upregulated their individual alpha band power. There was a significantly larger increase in alpha power (p < 0.0001) and decrease of theta power (p < 0.04) in participant specific rather than in fixed frequency bands.

CONCLUSION

Neurofeedback is a neuromodulatory technique that gives participants control over their pain and can be self-administered at home. Regulation of individual frequency band was related to a significant reduction in pain.