Learning to modulate one's own brain activity: the effect of spontaneous mental strategies

Real-time fMRI neurofeedback of the anterior insula using arterial spin labelling

Arterial spin labelling (ASL) is the only non-invasive technique that allows absolute quantification of perfusion and is increasingly used in brain activation studies. Contrary to the blood oxygen level-dependent (BOLD) effect ASL measures the cerebral blood flow (CBF) directly. However, the ASL signal has a lower signal-to-noise ratio (SNR), than the BOLD signal, which constrains its utilization in neurofeedback studies. If successful, ASL neurofeedback can be used to aid in the rehabilitation of health conditions with impaired blood flow, for example, stroke. We provide the first ASL-based neurofeedback study incorporating a double-blind, sham-controlled design. A pseudo-continuous ASL (pCASL) approach with background suppression and 3D GRASE readout was combined with a real-time post-processing pipeline. The real-time pipeline allows to monitor the ASL signal and provides real-time feedback on the neural activity to the subject. In total 41 healthy adults (19-56 years) divided into three groups underwent a neurofeedback-based emotion imagery training of the left anterior insula. Two groups differing only in the explicitness level of instruction received real training and a third group received sham feedback. Only those participants receiving real feedback with explicit instruction showed significantly higher absolute CBF values in the trained region during neurofeedback than participants receiving sham feedback. However, responder analyses of percent signal change values show no differences in activation between the three groups. Persisting limitations, such as the lower SNR, confounding effects of arterial transit time and partial volume effects still impact negatively the implementation of ASL neurofeedback.

Functional near-infrared spectroscopy-based neurofeedback training targeting the dorsolateral prefrontal cortex induces changes in cortico-striatal functional connectivity

Due to its central role in cognitive control, the dorso-lateral prefrontal cortex (dlPFC) has been the target of multiple brain modulation studies. In the context of the present pilot study, the dlPFC was the target of eight repeated neurofeedback (NF) sessions with functional near infrared spectroscopy (fNIRS) to assess the brain responses during NF and with functional and resting state magnetic resonance imaging (task-based fMRI and rsMRI) scanning. Fifteen healthy participants were recruited. Cognitive task fMRI and rsMRI were performed during the 1st and the 8th NF sessions. During NF, our data revealed an increased activity in the dlPFC as well as in brain regions involved in cognitive control and self-regulation learning (pFWE < 0.05). Changes in functional connectivity between the 1st and the 8th session revealed increased connectivity between the posterior cingulate cortex and the dlPFC, and between the posterior cingulate cortex and the dorsal striatum (pFWE < 0.05). Decreased left dlPFC-left insula connectivity was also observed. Behavioural results revealed a significant effect of hunger and motivation on the participant control feeling and a lower control feeling when participants did not identify an effective mental strategy, providing new insights on the effects of behavioural factors that may affect the NF learning.

Exploring the Feasibility of Bidirectional Control of Beta Oscillatory Power in Healthy Controls as a Potential Intervention for Parkinson's Disease Movement Impairment

Neurofeedback (NF) is a promising intervention for improvements in motor performance in Parkinson's disease. This NF pilot study in healthy participants aimed to achieve the following: (1) determine participants' ability to bi-directionally modulate sensorimotor beta power and (2) determine the effect of NF on movement performance. A real-time EEG-NF protocol was used to train participants to increase and decrease their individual motor cortex beta power amplitude, using a within-subject double-blind sham-controlled approach. Movement was assessed using a Go/No-go task. Participants completed the NASA Task Load Index and provided verbal feedback of the NF task difficulty. All 17 participants (median age = 38 (19-65); 10 females) reliably reduced sensorimotor beta power. No participant could reliably increase their beta activity. Participants reported that the NF task was challenging, particularly increasing beta. A modest but significant increase in reaction time correlated with a reduction in beta power only in the real condition. Findings suggest that beta power control difficulty varies by modulation direction, affecting participant perceptions. A correlation between beta power reduction and reaction times only in the real condition suggests that intentional beta power reduction may shorten reaction times. Future research should examine the minimum beta threshold for meaningful motor improvements, and the relationship between EEG mechanisms and NF learning to optimise NF outcomes.

Assessing the Anxiolytic and Relaxation Effects of Cinnamomum camphora Essential Oil in University Students: A Comparative Study of EEG, Physiological Measures, and Psychological Responses

Background

Cinnamomum camphora is a commercially important tree species in China, and it's also a common native tree in the forests of southern China. However, literature on the impact of Cinnamomum camphora essential oil (CCEO) on human psychophysiological activity is scarce. Hence, the primary objective of this study was to examine the effect of exposure to CCEO on the functioning of the human autonomic nervous system, electroencephalographic (EEG) activity, and emotional state.

Methods

Forty-three healthy university students participated. The data collected included heart rate (HR), blood pressure (BP), pulse rate, blood oxygen saturation (SpO2), electroencephalographic (EEG) activity, and the results of the Profile of Mood States (POMS) test.

Results

A drop in diastolic pressure (DBP) and pulse rate was also noticed after participants inhaled CCEO. Furthermore, EEG studies have demonstrated notable reductions in absolute beta (AB), absolute gamma (AG), absolute high beta (AHB), and relative gamma (RG) power spectra during exposure to CCEO. Conversely, the relative theta (RT) and power spectra values showed a significant increase. Additionally, the finding from POMS indicated that the fragrance evoked positive emotions and suppressed negative feelings.

Conclusion

The results suggest that exposure to CCEO may promote mental and physical relaxation, facilitate cognitive processes such as memory and attention, and enhance mood states.

Modulation of human frontal midline theta by neurofeedback: A systematic review and quantitative meta-analysis

Human brain activity consists of different frequency bands associated with varying functions. Oscillatory activity of frontal brain regions in the theta range (4-8 Hz) is linked to cognitive processing and can be modulated by neurofeedback - a technique where participants receive real-time feedback about their brain activity and learn to modulate it. However, criticism of this technique evolved, and high heterogeneity of study designs complicates a valid evaluation of its effectiveness. This meta-analysis provides the first systematic overview over studies attempting to modulate frontal midline theta with neurofeedback in healthy human participants. Out of 1261 articles screened, 14 studies were eligible for systematic review and 11 for quantitative meta-analyses. Studies were evaluated following the DIAD model and the PRISMA guidelines. A significant across-study effect of medium size (Hedges' g = .66; 95%-CI [-0.62, 1.73]) with substantial between-study heterogeneity (Q(16) = 167.43, p < .001) was observed and subanalysis revealed effective frontal midline theta upregulation. We discuss moderators of effect sizes and provide guidelines for future research in this dynamic field.

Do Miniature Eye Movements Affect Neurofeedback Training Performance? A Combined EEG-Eye Tracking Study

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.

Integrated use of biofeedback and neurofeedback techniques in treating pathological conditions and improving performance: a narrative review

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.

A feasibility study of goal-directed network-based real-time fMRI neurofeedback for anhedonic depression

Anhedonia is a hallmark symptom of depression that often lacks adequate interventions. The translational gap remains in clinical treatments based on neural substrates of anhedonia. Our pilot study found that depressed individuals depended less on goal-directed (GD) reward learning (RL), with reduced reward prediction error (RPE) BOLD signal. Previous studies have found that anhedonia is related to abnormal activities and/or functional connectivities of the central executive network (CEN) and salience network (SN), both of which belong to the goal-directed system. In addition, it was found that real-time functional magnetic resonance imaging (rt-fMRI) neurofeedback (NF) could improve the balance between CEN and SN in healthy individuals. Therefore, we speculate that rt-fMRI NF of the CEN and SN associated with the GD system may improve depressive and/or anhedonic symptoms. Therefore, this study (1) will examine individuals with anhedonic depression using GD-RL behavioral task, combined with functional magnetic resonance imaging and computational modeling to explore the role of CEN/SN deficits in anhedonic depression; and (2) will utilize network-based rt-fMRI NF to investigate whether it is feasible to regulate the differential signals of brain CEN/SN of GD system through rt-fMRI NF to alleviate depressive and/or anhedonic symptoms. This study highlights the need to elucidate the intervention effects of rt-fMRI NF and the underlying computational network neural mechanisms.

Mechanisms underlying fNIRS-neurofeedback over the prefrontal cortex for participants with binge-eating disorder

OBJECTIVE

Despite the increasing popularity of neurofeedback (NF), aiming at voluntary modulation of dysfunctional prefrontal cortex (PFC) signals in the treatment of binge-eating disorder (BED) and/or overweight, mechanisms remain poorly understood.

METHODS

Based on a randomized-controlled trial offering 12 food-specific real-time functional near-infrared spectroscopy (rtfNIRS)-NF sessions to participants with BED (n = 22), this preregistered study examined (1) online regulation success as predictor for offline regulation success, defined by PFC signals during regulation versus watch, and subjective regulation success, and (2) changes in loss of control (LOC) eating after vs. before and across 12 rtfNIRS-NF-sessions.

RESULTS

Higher online regulation success expectedly predicted better subjective, but worse offline regulation success. LOC eating decreased after vs. before, but not over rtfNIRS-NF-sessions, and was not associated with subjective or offline regulation success.

CONCLUSIONS

The association between online and subjective regulation success confirmed the presumed mechanism of operant conditioning underlying rtfNIRS-NF-learning. The contrary association between online and offline regulation indicated differential PFC involvement upon subtraction of automatic food-specific responses from regulation signals for offline success. Decreased LOC eating after food-specific rtfNIRS-NF-sessions suggested the potential of NF in BED treatment.

SIGNIFICANCE

Results may guide the optimization of future NF studies in larger samples with BED.

Association between lesion location and sensorimotor rhythms in stroke - a systematic review with narrative synthesis

BACKGROUND

Stroke causes alterations in the sensorimotor rhythms (SMRs) of the brain. However, little is known about the influence of lesion location on the SMRs. Understanding this relationship is relevant for the use of SMRs in assistive and rehabilitative therapies, such as Brain-Computer Interfaces (BCIs)..

METHODS

We reviewed current evidence on the association between stroke lesion location and SMRs through systematically searching PubMed and Embase and generated a narrative synthesis of findings.

RESULTS

We included 12 articles reporting on 161 patients. In resting-state studies, cortical and pontine damage were related to an overall decrease in alpha (∼8-12 Hz) and increase in delta (∼1-4 Hz) power. In movement paradigm studies, attenuated alpha and beta (∼15-25 Hz) event-related desynchronization (ERD) was shown in stroke patients during (attempted) paretic hand movement, compared to controls. Stronger reductions in alpha and beta ERD in the ipsilesional, compared to contralesional hemisphere, were observed for cortical lesions. Subcortical stroke was found to affect bilateral ERD and ERS, but results were highly variable.

CONCLUSIONS

Findings suggest a link between stroke lesion location and SMR alterations, but heterogeneity across studies and limited lesion location descriptions precluded a meta-analysis.

SIGNIFICANCE

Future research would benefit from more uniformly defined outcome measures, homogeneous methodologies, and improved lesion location reporting.

Neurofeedback strategies in binge-eating disorder as predictors of EEG-neurofeedback regulation success

Introduction

Treatment options such as neurofeedback (NF) that directly target the link between aberrant brain activity patterns and dysfunctional eating behaviors in binge-eating disorder (BED) are emerging. However, virtually nothing is known about mental strategies used to modulate food-specific brain activity and the associated brain-based or subjective success of specific strategies. This study firstly investigated the use of mental strategies in response to individually appetitive food cues in adults with BED and overweight or obesity based on a randomized-controlled trial providing electroencephalography (EEG)- or real-time functional near-infrared spectroscopy (rtfNIRS)-NF to BED.

Methods

Strategy reports written by participants were classified with qualitative content analysis. Additionally, the mental strategies employed by the N = 23 patients who received EEG-NF targeting the reduction of fronto-central high beta activity were analyzed quantitatively through their link with subjective and EEG-NF regulation success.

Results

The following eight categories, ordered by frequency in descending order, were found: "Behavior," "Imagination," "Emotion," "Distraction," "Thought," "Concentration," "Self-Talk" and "No Strategy." Linear mixed models revealed "Imagination," "Behavior," and "Thought" strategies as positive predictors of EEG-NF regulation success (defined as high beta activity during regulation beneath the baseline), and "Concentration" as a negative predictor of subjective (i.e., self-reported) NF regulation success.

Discussion

In conclusion, our study offers a classification system that may be used in future studies assessing strategy use for regulating food-related responses in patients with BED and associated overweight/obesity, providing valuable information on potential benefits of specific strategies and transferability to situations outside the NF treatment.

A large EEG database with users' profile information for motor imagery brain-computer interface research

We present and share a large database containing electroencephalographic signals from 87 human participants, collected during a single day of brain-computer interface (BCI) experiments, organized into 3 datasets (A, B, and C) that were all recorded using the same protocol: right and left hand motor imagery (MI). Each session contains 240 trials (120 per class), which represents more than 20,800 trials, or approximately 70 hours of recording time. It includes the performance of the associated BCI users, detailed information about the demographics, personality profile as well as some cognitive traits and the experimental instructions and codes (executed in the open-source platform OpenViBE). Such database could prove useful for various studies, including but not limited to: (1) studying the relationships between BCI users' profiles and their BCI performances, (2) studying how EEG signals properties varies for different users' profiles and MI tasks, (3) using the large number of participants to design cross-user BCI machine learning algorithms or (4) incorporating users' profile information into the design of EEG signal classification algorithms.

The Use of Quantitative Electroencephalography (QEEG) to Assess Post-COVID-19 Concentration Disorders in Professional Pilots: An Initial Concept

Announced by WHO in 2020, the global COVID-19 pandemic caused by SARS-CoV-2 has affected many people, leading to serious health consequences. These consequences are observed in the daily lives of infected patients as various dysfunctions and limitations. More and more people are suffering post-COVID-19 complications that interfere with or completely prevent them from working or even functioning independently on a daily basis. The aim of our study was to demonstrate that innovative quantitative electroencephalography (QEEG) can be used to assess cognitive function disorders reported after the COVID-19 pandemic. It is worth noting that no similar study has been conducted to date in a group of pilots. The QEEG method we used is currently one of the basic neurological examinations, enabling easy observation of post-COVID-19 changes in the nervous system. With the innovativeness of this technique, our study shows that the use of quantitative electroencephalography can be a precursor in identifying complications associated with cognitive function disorders after COVID-19. Our study was conducted on twelve 26-year-old pilots. All participants had attended the same flight academy and had contracted SARS-CoV-2 infection. The pilots began to suspect COVID-19 infection when they developed typical symptoms such as loss of smell and taste, respiratory problems, and rapid fatigue. Quantitative electroencephalography (QEEG), which is one of the most innovative forms of diagnostics, was used to diagnose the patients. Comparison of the results between the study and control groups showed significantly higher values of all measurements of alpha, theta, and beta2 waves in the study group. In the case of the sensorimotor rhythm (SMR), the measurement results were significantly higher in the control group compared to the study group. Our study, conducted on pilots who had recovered from COVID-19, showed changes in the amplitudes of brain waves associated with relaxation and concentration. The results confirmed the issues reported by pilots as evidenced by the increased amplitudes of alfa, theta, and beta2 waves. It should be emphasized that the modern diagnostic method (QEEG) presented here has significant importance in the medical diagnosis of various symptoms and observation of treatment effects in individuals who have contracted the SARS-CoV-2 virus. The present study demonstrated an innovative approach to the diagnosis of neurological complications after COVID-19.

Subjective feeling of control during fNIRS-based neurofeedback targeting the DL-PFC is related to neural activation determined with short-channel correction

Neurofeedback (NF) training is a promising preventive and therapeutic approach for brain and behavioral impairments, the dorsolateral prefrontal cortex (DL-PFC) being a relevant region of interest. Functional near-infrared spectroscopy (NIRS) has recently been applied in NF training. However, this approach is highly sensitive to extra-cerebral vascularization, which could bias measurements of cortical activity. Here, we examined the feasibility of a NF training targeting the DL-PFC and its specificity by assessing the impact of physiological confounds on NF success via short-channel offline correction under different signal filtering conditions. We also explored whether the individual mental strategies affect the NF success. Thirty volunteers participated in a single 15-trial NF session in which they had to increase the oxy-hemoglobin (HbO2) level of their bilateral DL-PFC. We found that 0.01-0.09 Hz band-pass filtering was more suited than the 0.01-0.2 Hz band-pass filter to highlight brain activation restricted to the NF channels in the DL-PFC. Retaining the 10 out of 15 best trials, we found that 18 participants (60%) managed to control their DL-PFC. This number dropped to 13 (43%) with short-channel correction. Half of the participants reported a positive subjective feeling of control, and the "cheering" strategy appeared to be more effective in men (p<0.05). Our results showed successful DL-PFC fNIRS-NF in a single session and highlighted the value of accounting for extra cortical signals, which can profoundly affect the success and specificity of NF training.

Neurofeedback therapy to improve cognitive function in patients with chronic post-stroke attention deficits: a within-subjects comparison

Introduction

We investigated a slow-cortical potential (SCP) neurofeedback therapy approach for rehabilitating chronic attention deficits after stroke. This study is the first attempt to train patients who survived stroke with SCP neurofeedback therapy.

Methods

We included N = 5 participants in a within-subjects follow-up design. We assessed neuropsychological and psychological performance at baseline (4 weeks before study onset), before study onset, after neurofeedback training, and at 3 months follow-up. Participants underwent 20 sessions of SCP neurofeedback training.

Results

Participants learned to regulate SCPs toward negativity, and we found indications for improved attention after the SCP neurofeedback therapy in some participants. Quality of life improved throughout the study according to engagement in activities of daily living. The self-reported motivation was related to mean SCP activation in two participants.

Discussion

We would like to bring attention to the potential of SCP neurofeedback therapy as a new rehabilitation method for treating post-stroke cognitive deficits. Studies with larger samples are warranted to corroborate the results.

Evaluation of Neurofeedback Learning in Patients with ADHD: A Systematic Review

NFB has a clear potential as a recognised treatment option for ADHD, but suffers from a lack of clarity about its efficacy, still unresolved after multiple controlled trials. Comparing learners and non-learners based on the evolution of patient-level indicators during the trial serves as a 'natural' control, and can help elucidate the mechanisms of NFB. We present a systematic review motivated by the need to establish the state of the art of patient learning during NFB treatment in current clinical literature. One particularly striking question we would like to answer here is whether existing NFB papers study learning variability, since only individual performance differences can give us information about mechanisms of learning. The results show that very few clinical trial reports have dealt with the heterogeneity of NFB learning, nor analysed whether NFB efficacy is dependent on NFB learning, even though NFB is believed to be a treatment based on learning to perform. In this systematic review we examine not only what has been reported, but also provide a critical analysis of possible flaws or gaps in existing studies, and discuss why no generalized conclusions about NFB efficacy have yet been made. Future research should focus on finding reliable ways of identifying the performers and studying participants' individual learning trajectories as it might enhance prognosis and the allocation of clinical resources.

Effects of SMR Neurofeedback on Cognitive Functions in an Adult Population with Sleep Problems: A Tele-neurofeedback Study

A good night's sleep is vital for normal human cognitive performance. We earlier reported that a home-based tele-neurofeedback program effectively reduced sleep problems (Krepel et al. in Appl Psychophysiol Biofeedback, https://doi.org/10.1007/s10484-021-09525-z , 2021). The present article presents a follow-up on this earlier study and investigates improvements in cognitive functions after sensory-motor rhythm (SMR) neurofeedback. Thirty-seven participants reporting sleep problems received SMR neurofeedback. Cognitive measures were assessed pre- and post-treatment. Measurements included a continuous performance/working memory (CPT/WM) task, Stroop task, and Trailmaking A and B test (from the IntegNeuro cognitive test battery). For neurofeedback-Learners relative to non-Learners significantly improved CPT/WM response time (d = 0.50), omission errors (d = 0.67), and Stroop incongruent performance (d = 0.72) were found. A significant time effect for both groups were found for the Stroop, the Trailmaking test part B (d = 0.52), and the Stroop interference score (d = 0.55). No significant correlations between changes in sleep and changes in cognition (p > 0.05) were found for the sample. SMR neurofeedback specifically improved measures of attention (response time and omission errors in a CPT/WM test) and working memory (Stroop incongruent) for SMR Learners compared to non-Learners with medium effect sizes. Furthermore, overall improvements for the whole sample were found on measures of executive function and visual attention, possibly reflecting non-specific or practice effects. Future better powered randomized control trials are needed to investigate if cognitive improvements are a direct effect of SMR neurofeedback or mediated by sleep improvements.

Riemannian geometry-based metrics to measure and reinforce user performance changes during brain-computer interface user training

Despite growing interest and research into brain-computer interfaces (BCI), their usage remains limited outside of research laboratories. One reason for this is BCI inefficiency, the phenomenon where a significant number of potential users are unable to produce machine-discernible brain signal patterns to control the devices. To reduce the prevalence of BCI inefficiency, some have advocated for novel user-training protocols that enable users to more effectively modulate their neural activity. Important considerations for the design of these protocols are the assessment measures that are used for evaluating user performance and for providing feedback that guides skill acquisition. Herein, we present three trial-wise adaptations (running, sliding window and weighted average) of Riemannian geometry-based user-performance metrics (classDistinct reflecting the degree of class separability and classStability reflecting the level of within-class consistency) to enable feedback to the user following each individual trial. We evaluated these metrics, along with conventional classifier feedback, using simulated and previously recorded sensorimotor rhythm-BCI data to assess their correlation with and discrimination of broader trends in user performance. Analysis revealed that the sliding window and weighted average variants of our proposed trial-wise Riemannian geometry-based metrics more accurately reflected performance changes during BCI sessions compared to conventional classifier output. The results indicate the metrics are a viable method for evaluating and tracking user performance changes during BCI-user training and, therefore, further investigation into how these metrics may be presented to users during training is warranted.

Exploring electroencephalographic infraslow neurofeedback treatment for chronic low back pain: a double-blinded safety and feasibility randomized placebo-controlled trial

Chronic low back pain (CLBP) is a disabling condition worldwide. In CLBP, neuroimaging studies demonstrate abnormal activities in cortical areas responsible for pain modulation, emotional, and sensory components of pain experience [i.e., pregenual and dorsal anterior cingulate cortex (pgACC, dACC), and somatosensory cortex (SSC), respectively]. This pilot study, conducted in a university setting, evaluated the feasibility, safety, and acceptability of a novel electroencephalography-based infraslow-neurofeedback (EEG ISF-NF) technique for retraining activities in pgACC, dACC and SSC and explored its effects on pain and disability. Participants with CLBP (n = 60), recruited between July'20 to March'21, received 12 sessions of either: ISF-NF targeting pgACC, dACC + SSC, a ratio of pgACC*2/dACC + SSC, or Placebo-NF. Descriptive statistics demonstrated that ISF-NF training is feasible [recruitment rate (7 participants/month), dropouts (25%; 20-27%), and adherence (80%; 73-88%)], safe (no adverse events reported), and was moderate to highly acceptable [Mean ± SD: 7.8 ± 2.0 (pgACC), 7.5 ± 2.7 (dACC + SCC), 8.2 ± 1.9 (Ratio), and 7.7 ± 1.5 (Placebo)]. ISF-NF targeting pgACC demonstrated the most favourable clinical outcomes, with a higher proportion of participants exhibiting a clinically meaningful reduction in pain severity [53%; MD (95% CI): - 1.9 (- 2.7, - 1.0)], interference [80%; MD (95% CI): - 2.3 (- 3.5, - 1.2)], and disability [73%; MD (95% CI): - 4.5 (- 6.1, - 2.9)] at 1-month follow-up. ISF-NF training is a feasible, safe, and an acceptable treatment approach for CLBP.

The more, the better? Learning rate and self-pacing in neurofeedback enhance cognitive performance in healthy adults

Real time electroencephalogram (EEG) based neurofeedback has been shown to be effective in regulating brain activity, thereby modifying cognitive performance and behavior. Nevertheless, individual variations in neurofeedback learning rates limit the overall efficacy of EEG based neurofeedback. In the present study we investigated the effects of learning rate and control over training realized by self-pacing on cognitive performance and electrocortical activity. Using a double-blind design, we randomly allocated 60 participants to either individual upper alpha (IUA) or sham neurofeedback and subsequently to self- or externally paced training. Participants receiving IUA neurofeedback improved their IUA activity more than participants receiving sham neurofeedback. Furthermore, the learning rate predicted enhancements in resting-state activity and mental rotation ability. The direction of this linear relationship depended on the neurofeedback condition being positive for IUA and negative for sham neurofeedback. Finally, self-paced training increased higher-level cognitive skills more than externally paced training. These results underpin the important role of learning rate in enhancing both resting-state activity and cognitive performance. Our design allowed us to differentiate the effect of learning rate between neurofeedback conditions, and to demonstrate the positive effect of self-paced training on cognitive performance in IUA 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.

Neurofeedback training for children with ADHD using individual beta rhythm

Neurofeedback training (NFT) is a noninvasive neuromodulation method for children with attention-deficit/hyperactivity disorder (ADHD). Brain rhythms, the unique pattern in electroencephalogram (EEG), are widely used as the training target. Most of current studies used a fixed frequency division of brain rhythms, which ignores the individual developmental difference of each child. In this study, we validated the feasibility of NFT using individual beta rhythm. A total of 55 children with ADHD were divided into two groups using the relative power of individual or fixed beta rhythms as the training index. ADHD rating scale (ADHD-RS) was completed before and after NFT, and the EEG and behavioral features were extracted during the training process. After intervention, the attention ability of both groups was significantly improved, showing a significant increase in beta power, a decrease in scores of ADHD-RS and an improvement in behavioral and other EEG features. The training effect was significantly better with individualized beta training, showing more improvement in ADHD-RS scores. Furthermore, the distribution of brain rhythms moved towards high frequency after intervention. This study demonstrates the effectiveness of NFT based on individual beta rhythm for the intervention of children with ADHD. When designing a NFT protocol and the corresponding data analysis process, an individualized brain rhythm division should be applied to reflect the actual brain state and to accurately evaluate the effect of NFT.

Infraslow closed-loop brain training for anxiety and depression (ISAD): a protocol for a randomized, double-blind, sham-controlled pilot trial in adult females with internalizing disorders

BACKGROUND

The core intrinsic connectivity networks (core-ICNs), encompassing the default-mode network (DMN), salience network (SN) and central executive network (CEN), have been shown to be dysfunctional in individuals with internalizing disorders (IDs, e.g. major depressive disorder, MDD; generalized anxiety disorder, GAD; social anxiety disorder, SOC). As such, source-localized, closed-loop brain training of electrophysiological signals, also known as standardized low-resolution electromagnetic tomography (sLORETA) neurofeedback (NFB), targeting key cortical nodes within these networks has the potential to reduce symptoms associated with IDs and restore normal core ICN function. We intend to conduct a randomized, double-blind (participant and assessor), sham-controlled, parallel-group (3-arm) trial of sLORETA infraslow (<0.1 Hz) fluctuation neurofeedback (sLORETA ISF-NFB) 3 times per week over 4 weeks in participants (n=60) with IDs. Our primary objectives will be to examine patient-reported outcomes (PROs) and neurophysiological measures to (1) compare the potential effects of sham ISF-NFB to either genuine 1-region ISF-NFB or genuine 2-region ISF-NFB, and (2) assess for potential associations between changes in PRO scores and modifications of electroencephalographic (EEG) activity/connectivity within/between the trained regions of interest (ROIs). As part of an exploratory analysis, we will investigate the effects of additional training sessions and the potential for the potentiation of the effects over time.

METHODS

We will randomly assign participants who meet the criteria for MDD, GAD, and/or SOC per the MINI (Mini International Neuropsychiatric Interview for DSM-5) to one of three groups: (1) 12 sessions of posterior cingulate cortex (PCC) ISF-NFB up-training (n=15), (2) 12 sessions of concurrent PCC ISF up-training and dorsal anterior cingulate cortex (dACC) ISF-NFB down-training (n=15), or (3) 6 sessions of yoked-sham training followed by 6 sessions genuine ISF-NFB (n=30). Transdiagnostic PROs (Hospital Anxiety and Depression Scale, HADS; Inventory of Depression and Anxiety Symptoms - Second Version, IDAS-II; Multidimensional Emotional Disorder Inventory, MEDI; Intolerance of Uncertainty Scale - Short Form, IUS-12; Repetitive Thinking Questionnaire, RTQ-10) as well as resting-state neurophysiological measures (full-band EEG and ECG) will be collected from all subjects during two baseline sessions (approximately 1 week apart) then at post 6 sessions, post 12 sessions, and follow-up (1 month later). We will employ Bayesian methods in R and advanced source-localisation software (i.e. exact low-resolution brain electromagnetic tomography; eLORETA) in our analysis.

DISCUSSION

This protocol will outline the rationale and research methodology for a clinical pilot trial of sLORETA ISF-NFB targeting key nodes within the core-ICNs in a female ID population with the primary aims being to assess its potential efficacy via transdiagnostic PROs and relevant neurophysiological measures.

TRIAL REGISTRATION

Our study was prospectively registered with the Australia New Zealand Clinical Trials Registry (ANZCTR; Trial ID: ACTRN12619001428156). Registered on October 15, 2019.

A pediatric near-infrared spectroscopy brain-computer interface based on the detection of emotional valence

Brain-computer interfaces (BCIs) are being investigated as an access pathway to communication for individuals with physical disabilities, as the technology obviates the need for voluntary motor control. However, to date, minimal research has investigated the use of BCIs for children. Traditional BCI communication paradigms may be suboptimal given that children with physical disabilities may face delays in cognitive development and acquisition of literacy skills. Instead, in this study we explored emotional state as an alternative access pathway to communication. We developed a pediatric BCI to identify positive and negative emotional states from changes in hemodynamic activity of the prefrontal cortex (PFC). To train and test the BCI, 10 neurotypical children aged 8–14 underwent a series of emotion-induction trials over four experimental sessions (one offline, three online) while their brain activity was measured with functional near-infrared spectroscopy (fNIRS). Visual neurofeedback was used to assist participants in regulating their emotional states and modulating their hemodynamic activity in response to the affective stimuli. Child-specific linear discriminant classifiers were trained on cumulatively available data from previous sessions and adaptively updated throughout each session. Average online valence classification exceeded chance across participants by the last two online sessions (with 7 and 8 of the 10 participants performing better than chance, respectively, in Sessions 3 and 4). There was a small significant positive correlation with online BCI performance and age, suggesting older participants were more successful at regulating their emotional state and/or brain activity. Variability was seen across participants in regards to BCI performance, hemodynamic response, and discriminatory features and channels. Retrospective offline analyses yielded accuracies comparable to those reported in adult affective BCI studies using fNIRS. Affective fNIRS-BCIs appear to be feasible for school-aged children, but to further gauge the practical potential of this type of BCI, replication with more training sessions, larger sample sizes, and end-users with disabilities is necessary.

Triathletes are experts in self-regulating physical activity - But what about self-regulating neural activity?

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 min. 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.

Doubting the double-blind: Introducing a questionnaire for awareness of experimental purposes in neurofeedback studies

Double-blinding subjects to the experiment's purpose is an important standard in neurofeedback studies. However, it is difficult to provide evidence that humans are entirely unaware of certain information. This study used insights from consciousness studies and neurophenomenology to develop a contingency awareness questionnaire for neurofeedback. We assessed whether participants had an awareness of experimental purposes to manipulate their attention and multisensory perception. A subset of subjects (5 out of 20) gained a degree of awareness of experimental purposes as evidenced by their correct guess about the purposes of the experiment to affect their attention and multisensory perceptions specific to their double-blinded group assignment. The results warrant replication before they are applied to clinical neurofeedback studies, given the considerable time taken to perform the questionnaire (∼25 min). We discuss the strengths and limitations of our contingency awareness questionnaire and the growing appeal of the double-blinded standard in clinical neurofeedback studies.

Winners and losers in brain computer interface competitive gaming: Directional connectivity analysis

OBJECTIVE

to characterize the direction within and between brain connectivity in winning and losing players in a competitive brain-computer interface game.

APPROACH

ten dyads (26.9 ± 4.7 years old, eight females and 12 males) participated in the study. In a competitive game based on neurofeedback, they used their relative alpha (RA) band power from the electrode location Pz, to control a virtual seesaw. The players in each pair were separated into winners (W) and losers (L) based on their scores. Intrabrain connectivity was analyzed using multivariate Granger Causality (GC) and Directed Transfer Function, while interbrain connectivity was analyzed using bivariate GC.

RESULTS

linear regression analysis revealed a significant relationship (p<0.05) between RA and individual scores. During the game, W players maintained a higher RA than L players, although it was not higher than their baseline RA. The analysis of intrabrain GC indicated that both groups engaged in general social interactions, but only the W group succeeded in controlling their brain activity at Pz. Group L applied an inappropriate metal strategy, characterized by strong activity in the left frontal cortex, indicative of collaborative gaming. Interbrain GC showed a larger flow of information from the L to the W group, suggesting a higher capability of the W group to monitor the activity of their opponent.

SIGNIFICANCE

both innate neurological indices and gaming mental strategies contribute to game outcomes. Future studies should investigate whether there is a causal relationship between these two factors.

Toward an Adapted Neurofeedback for Post-stroke Motor Rehabilitation: State of the Art and Perspectives

Stroke is a severe health issue, and motor recovery after stroke remains an important challenge in the rehabilitation field. Neurofeedback (NFB), as part of a brain–computer interface, is a technique for modulating brain activity using on-line feedback that has proved to be useful in motor rehabilitation for the chronic stroke population in addition to traditional therapies. Nevertheless, its use and applications in the field still leave unresolved questions. The brain pathophysiological mechanisms after stroke remain partly unknown, and the possibilities for intervention on these mechanisms to promote cerebral plasticity are limited in clinical practice. In NFB motor rehabilitation, the aim is to adapt the therapy to the patient’s clinical context using brain imaging, considering the time after stroke, the localization of brain lesions, and their clinical impact, while taking into account currently used biomarkers and technical limitations. These modern techniques also allow a better understanding of the physiopathology and neuroplasticity of the brain after stroke. We conducted a narrative literature review of studies using NFB for post-stroke motor rehabilitation. The main goal was to decompose all the elements that can be modified in NFB therapies, which can lead to their adaptation according to the patient’s context and according to the current technological limits. Adaptation and individualization of care could derive from this analysis to better meet the patients’ needs. We focused on and highlighted the various clinical and technological components considering the most recent experiments. The second goal was to propose general recommendations and enhance the limits and perspectives to improve our general knowledge in the field and allow clinical applications. We highlighted the multidisciplinary approach of this work by combining engineering abilities and medical experience. Engineering development is essential for the available technological tools and aims to increase neuroscience knowledge in the NFB topic. This technological development was born out of the real clinical need to provide complementary therapeutic solutions to a public health problem, considering the actual clinical context of the post-stroke patient and the practical limits resulting from it.

ERD modulations during motor imageries relate to users' traits and BCI performances

Improving user performances is one of the major issues for Motor Imagery (MI) - based BCI control. MI-BCIs exploit the modulation of sensorimotor rhythms (SMR) over the motor and sensorimotor cortices to discriminate several mental states and enable user interaction. Such modulations are known as Event-Related Desynchronization (ERD) and Synchronization (ERS), coming from the mu (7-13 Hz) and beta (15-30 Hz) frequency bands. This kind of BCI opens up promising fields, particularly to control assistive technologies, for sport training or even for post-stroke motor rehabilitation. However, MI - BCIs remain barely used outside laboratories, notably due to their lack of robustness and usability (15 to 30% of users seem unable to gain control of an MI-BCI). One way to increase user performance would be to better understand the relationships between user traits and ERD/ERS modulations underlying BCI performance. Therefore, in this article we analyzed how cerebral motor patterns underlying MI tasks (i.e., ERDs and ERSs) are modulated depending (i) on nature of the task (i.e., right-hand MI and left-hand MI), (ii) the session during which the task was performed (i.e., calibration or user training) and (iii) on the characteristics of the user (e.g., age, gender, manual activity, personality traits) on a large MI-BCI data base of N=75 participants. One of the originality of this study is to combine the investigation of human factors related to the user's traits and the neurophysiological ERD modulations during the MI task. Our study revealed for the first time an association between ERD and self-control from the 16PF5 questionnaire.

The importance of self-efficacy and negative affect for neurofeedback success for central neuropathic pain after a spinal cord injury

EEG-based neurofeedback uses mental behaviours (MB) to enable voluntary self-modulation of brain activity, and has potential to relieve central neuropathic pain (CNP) after a spinal cord injury (SCI). This study aimed to understand neurofeedback learning and the relationship between MB and neurofeedback success. Twenty-five non-CNP participants and ten CNP participants received neurofeedback training (reinforcing 9–12 Hz; suppressing 4–8 Hz and 20–30 Hz) on four visits. Participants were interviewed about the MB they used after each visit. Questionnaires examined the following factors: self-efficacy, locus of control, motivation, and workload of neurofeedback. MB were grouped into mental strategies (a goal-directed mental action) and affect (emotional experience during neurofeedback). Successful non-CNP participants significantly used more imagination-related MS and reported more negative affect compared to successful CNP participants. However, no mental strategy was clearly associated with neurofeedback success. There was some association between the lack of success and negative affect. Self-efficacy was moderately correlated with neurofeedback success (r = < 0.587, p = < 0.020), whereas locus of control, motivation, and workload had low, non-significant correlations (r < 0.300, p > 0.05). Affect may be more important than mental strategies for a successful neurofeedback performance. Self-efficacy was associated with neurofeedback success, suggesting that increasing confidence in one’s neurofeedback abilities may improve neurofeedback performance.

Recovering Hidden Responder Groups in Individuals Receiving Neurofeedback for Tinnitus

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.

Alpha/Theta Ratio Neurofeedback Training for Attention Enhancement in Normal Developing Children: A Brief Report

Attention plays an important role in children's development and learning, and neurofeedback training (NFT) has been proposed as a promising method to improve attention, mainly in population with attention problems such as attention deficit hyperactivity disorder. However, whether this approach has a positive effect on attention in normal developing children has been rarely investigated. This pilot study conducted ten sessions of alpha/theta ratio (ATR) NFT on eight primary students in school environment, with two to three sessions per week. The results showed inter-individual difference in NFT learning efficacy that was assessed by the slope of ATR over training sessions. In addition, the attention performance was significantly improved after NFT. Importantly, the improvement of attention performance was positively correlated with the NFT learning efficacy. It thus highlighted the need for optimizing ATR NFT protocol for the benefits on attention at the individual level. Future work can employ a double-blind placebo-controlled design with larger sample size to validate the benefits of ATR NFT for attention in normal developing children.

Neurofeedback through the lens of reinforcement learning

Despite decades of experimental and clinical practice, the neuropsychological mechanisms underlying neurofeedback (NF) training remain obscure. NF is a unique form of reinforcement learning (RL) task, during which participants are provided with rewarding feedback regarding desired changes in neural patterns. However, key RL considerations - including choices during practice, prediction errors, credit-assignment problems, or the exploration-exploitation tradeoff - have infrequently been considered in the context of NF. We offer an RL-based framework for NF, describing different internal states, actions, and rewards in common NF protocols, thus fashioning new proposals for characterizing, predicting, and hastening the course of learning. In this way we hope to advance current understanding of neural regulation via NF, and ultimately to promote its effectiveness, personalization, and clinical utility.

Neurofeedback Training of Alpha Relative Power Improves the Performance of Motor Imagery Brain-Computer Interface

Significant variation in performance in motor imagery (MI) tasks impedes their wide adoption for brain-computer interface (BCI) applications. Previous researchers have found that resting-state alpha-band power is positively correlated with MI-BCI performance. In this study, we designed a neurofeedback training (NFT) protocol based on the up-regulation of the alpha band relative power (RP) to investigate its effect on MI-BCI performance. The principal finding of this study is that alpha NFT could successfully help subjects increase alpha-rhythm power and improve their MI-BCI performance. An individual difference was also found in this study in that subjects who increased alpha power more had a better performance improvement. Additionally, the functional connectivity (FC) of the frontal-parietal (FP) network was found to be enhanced after alpha NFT. However, the enhancement failed to reach a significant level after multiple comparisons correction. These findings contribute to a better understanding of the neurophysiological mechanism of cognitive control through alpha regulation.

The Effect of Alpha Neurofeedback Training on Cognitive Performance in Healthy Adults

This study investigates the effect of long-term alpha neurofeedback training (NFT) in healthy adults using music stimuli. The optimal protocol for future research is presented in this study. The data from 40 healthy participants, divided into two groups (NFT group and Control group), were analyzed in the current study. We found a significantly enhanced alpha rhythm after training in the NFT group which was not observed in the control group. The immediate subsequent effects were greater in more than 80% of the sessions from the initial recordings. Stroop task and behavioral questionnaires, mini-mental state exam (MMSE), and perceived stress scale (PSS) did not reveal any training-specific changes. Within-training session effects were significant from the baseline and were more pronounced at the beginning of the session as compared to the end of the session. It is also observed that a shorter session length with multiple sessions may be more effective than a long and continuous run of a single session.

Individual Sensory Modality Dominance as an Influential Factor in the Prefrontal Neurofeedback Training for Spatial Processing: A Functional Near-Infrared Spectroscopy Study

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.

Volitional control of individual neurons in the human brain

Brain-machine interfaces allow neuroscientists to causally link specific neural activity patterns to a particular behaviour. Thus, in addition to their current clinical applications, brain-machine interfaces can also be used as a tool to investigate neural mechanisms of learning and plasticity in the brain. Decades of research using such brain-machine interfaces have shown that animals (non-human primates and rodents) can be operantly conditioned to self-regulate neural activity in various motor-related structures of the brain. Here, we ask whether the human brain, a complex interconnected structure of over 80 billion neurons, can learn to control itself at the most elemental scale-a single neuron. We used the unique opportunity to record single units in 11 individuals with epilepsy to explore whether the firing rate of a single (direct) neuron in limbic and other memory-related brain structures can be brought under volitional control. To do this, we developed a visual neurofeedback task in which participants were trained to move a block on a screen by modulating the activity of an arbitrarily selected neuron from their brain. Remarkably, participants were able to volitionally modulate the firing rate of the direct neuron in these previously uninvestigated structures. We found that a subset of participants (learners), were able to improve their performance within a single training session. Successful learning was characterized by (i) highly specific modulation of the direct neuron (demonstrated by significantly increased firing rates and burst frequency); (ii) a simultaneous decorrelation of the activity of the direct neuron from the neighbouring neurons; and (iii) robust phase-locking of the direct neuron to local alpha/beta-frequency oscillations, which may provide some insights in to the potential neural mechanisms that facilitate this type of learning. Volitional control of neuronal activity in mnemonic structures may provide new ways of probing the function and plasticity of human memory without exogenous stimulation. Furthermore, self-regulation of neural activity in these brain regions may provide an avenue for the development of novel neuroprosthetics for the treatment of neurological conditions that are commonly associated with pathological activity in these brain structures, such as medically refractory epilepsy.

Evaluation of the URGOnight Tele-neurofeedback Device: An Open-label Feasibility Study with Follow-up

SMR neurofeedback shows potential as a therapeutic tool for reducing sleep problems. It is hypothesized that SMR neurofeedback trains the reticulo-thalamocortical-cortical circuit involved in sleep-spindle generation. As such, strengthening this circuit is hypothesized to reduce sleep problems. The current study aims to investigate the effectiveness of a home-based device that uses SMR neurofeedback to help reduce sleep problems. Thirty-seven participants reporting sleep problems received the SMR neurofeedback-based program for 40 (n = 21) or 60 (n = 16) sessions. The Pittsburgh Sleep Quality Index (PSQI) and Holland Sleep Disorders Questionnaire (HSDQ) were assessed at baseline, session 20, outtake, and follow-up (FU). Actigraphy measurements were taken at baseline, session 20, and outtake. Significant improvements were observed in PSQI Total (d = 0.78), PSQI Sleep Duration (d = 0.52), HSDQ Total (d = 0.80), and HSDQ Insomnia (d = 0.79). Sleep duration (based on PSQI) increased from 5.3 h at baseline to 5.8 after treatment and 6.0 h. at FU. No effects of number of sessions were found. Participants qualified as successful SMR-learners demonstrated a significantly larger gain in sleep duration (d = 0.86 pre-post; average gain = 1.0 h.) compared to non-learners. The home-based SMR tele-neurofeedback device shows the potential to effectively reduce sleep problems, with SMR-learners demonstrating significantly better improvement. Although randomized controlled trials (RCTs) are needed to further elucidate the specific effect of this device on sleep problems, this is the first home-based SMR neurofeedback device using dry electrodes demonstrating effectiveness and feasibility.

Does Real-Time Feedback Affect Sensorimotor EEG Patterns in Routine Motor Imagery Practice?

Background. Motor imagery engages much of the same neural circuits as an overt movement. Therefore, the mental rehearsal of movements is often used to supplement physical training and might aid motor neurorehabilitation after stroke. One attempt to capture the brain’s involvement in imagery involves the use, as a marker, of the depression or event-related desynchronization (ERD) of thalamocortical sensorimotor rhythms found in a human electroencephalogram (EEG). Using fast real-time processing, it is possible to make the subject aware of their own brain reactions or—even better—to turn them into actions through a technology called the brain–computer interface (BCI). However, it remains unclear whether BCI-enabled imagery facilitates a stronger or qualitatively different brain response compared to the open-loop training. Methods. Seven healthy volunteers who were experienced in both closed and open-loop motor imagery took part in six experimental sessions over a period of 4.5 months, in which they performed kinesthetic imagery of a previously known set of finger and arm movements with simultaneous 30-channel EEG acquisition. The first and the last session mostly consisted of feedback trials in which the subjects were presented with the classification results of the EEG patterns in real time; during the other sessions, no feedback was provided. Spatiotemporal and amplitude features of the ERD patterns concomitant with imagery were compared across experimental days and between feedback conditions using linear mixed-effects modeling. Results. The main spatial sources of ERD appeared to be highly stable across the six experimental days, remaining nearly identical in five of seven subjects (Pearson’s ρ > 0.94). Only in one subject did the spatial pattern of activation statistically significantly differ (p = 0.009) between the feedback and no-feedback conditions. Real-time visual feedback delivered through the BCI did not significantly increase the ERD strength. Conclusion. The results imply that the potential benefits of MI could be yielded by well-habituated subjects with a simplified open-loop setup, e.g., through at-home self-practice.

Alpha activity neuromodulation induced by individual alpha-based neurofeedback learning in ecological context: a double-blind randomized study

The neuromodulation induced by neurofeedback training (NFT) remains a matter of debate. Investigating the modulation of brain activity specifically associated with NF requires controlling for multiple factors, such as reward, performance, congruency between task and targeted brain activity. This can be achieved using sham feedback (FB) control condition, equating all aspects of the experiment but the link between brain activity and FB. We aimed at investigating the modulation of individual alpha EEG activity induced by NFT in a double-blind, randomized, sham-controlled study. Forty-eight healthy participants were assigned to either NF (n = 25) or control (n = 23) group and performed alpha upregulation training (over 12 weeks) with a wearable EEG device. Participants of the NF group received FB based on their individual alpha activity. The control group received the auditory FB of participants of the NF group. An increase of alpha activity across training sessions was observed in the NF group only (p < 0.001). This neuromodulation was selective in that there was no evidence for similar effects in the theta (4-8 Hz) and low beta (13-18 Hz) bands. While alpha upregulation was found in the NF group only, psychological outcome variables showed overall increased feeling of control, decreased anxiety level and increased relaxation feeling, without any significant difference between the NF and the control groups. This is interpreted in terms of learning context and placebo effects. Our results pave the way to self-learnt, NF-based neuromodulation with light-weighted, wearable EEG systems.

A Multivariate Randomized Controlled Experiment about the Effects of Mindfulness Priming on EEG Neurofeedback Self-Regulation Serious Games

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.

Neurofeedback Learning Is Skill Acquisition but Does Not Guarantee Treatment Benefit: Continuous-Time Analysis of Learning-Curves From a Clinical Trial for ADHD

Neurofeedback for attention deficit/hyperactivity disorder (ADHD) has long been studied as an alternative to medication, promising non-invasive treatment with minimal side-effects and sustained outcome. However, debate continues over the efficacy of neurofeedback, partly because existing evidence for efficacy is mixed and often non-specific, with unclear relationships between prognostic variables, patient performance when learning to self-regulate, and treatment outcomes. We report an extensive analysis on the understudied area of neurofeedback learning. Our data comes from a randomised controlled clinical trial in adults with ADHD (registered trial ISRCTN13915109; N = 23; 13:10 female:male; age 25–57). Patients were treated with either theta-beta ratio or sensorimotor-rhythm regimes for 40 one-hour sessions. We classify 11 learners vs 12 non-learners by the significance of random slopes in a linear mixed growth-curve model. We then analyse the predictors, outcomes, and processes of learners vs non-learners, using these groups as mutual controls. Significant predictive relationships were found in anxiety disorder (GAD), dissociative experience (DES), and behavioural inhibition (BIS) scores obtained during screening. Low DES, but high GAD and BIS, predicted positive learning. Patterns of behavioural outcomes from Test Of Variables of Attention, and symptoms from adult ADHD Self-Report Scale, suggested that learning itself is not required for positive outcomes. Finally, the learning process was analysed using structural-equations modelling with continuous-time data, estimating the short-term and sustained impact of each session on learning. A key finding is that our results support the conceptualisation of neurofeedback learning as skill acquisition, and not merely operant conditioning as originally proposed in the literature.

An Online Data Visualization Feedback Protocol for Motor Imagery-Based BCI Training

Brain-computer interface (BCI) has developed rapidly over the past two decades, mainly due to advancements in machine learning. Subjects must learn to modulate their brain activities to ensure a successful BCI. Feedback training is a practical approach to this learning process; however, the commonly used classifier-dependent approaches have inherent limitations such as the need for calibration and a lack of continuous feedback over long periods of time. This paper proposes an online data visualization feedback protocol that intuitively reflects the EEG distribution in Riemannian geometry in real time. Rather than learning a hyperplane, the Riemannian geometry formulation allows iterative learning of prototypical covariance matrices that are translated into visualized feedback through diffusion map process. Ten subjects were recruited for MI-BCI (motor imagery-BCI) training experiments. The subjects learned to modulate their sensorimotor rhythm to centralize the points within one category and to separate points belonging to different categories. The results show favorable overall training effects in terms of the class distinctiveness and EEG feature discriminancy over a 3-day training with 30% learners. A steadily increased class distinctiveness in the last three sessions suggests that the advanced training protocol is effective. The optimal frequency band was consistent during the 3-day training, and the difference between subjects with good or low MI-BCI performance could be clearly observed. We believe that the proposed feedback protocol has promising application prospect.

Crosstalk disrupts the production of motor imagery brain signals in brain-computer interfaces

Brain-computer interfaces (BCIs) target specific brain activity for neuropsychological rehabilitation, and also allow patients with motor disabilities to control mobility and communication devices. Motor imagery of single-handed actions is used in BCIs but many users cannot control the BCIs effectively, limiting applications in the health systems. Crosstalk is unintended brain activations that interfere with bimanual actions and could also occur during motor imagery. To test if crosstalk impaired BCI user performance, we recorded EEG in 46 participants while they imagined movements in four experimental conditions using motor imagery: left hand (L), right hand (R), tongue (T) and feet (F). Pairwise classification accuracies of the tasks were compared (LR, LF, LT, RF, RT, FT), using common spatio-spectral filters and linear discriminant analysis. We hypothesized that LR classification accuracy would be lower than every other combination that included a hand imagery due to crosstalk. As predicted, classification accuracy for LR (58%) was reliably the lowest. Interestingly, participants who showed poor LR classification also demonstrated at least one good TR, TL, FR or FL classification; and good LR classification was detected in 16% of the participants. For the first time, we showed that crosstalk occurred in motor imagery, and affected BCI performance negatively. Such effects are effector-sensitive regardless of the BCI methods used; and likely not apparent to the user or the BCI developer. This means that tasks choice is crucial when designing BCI. Critically, the effects of crosstalk appear mitigatable. We conclude that understanding crosstalk mitigation is important for improving BCI applicability.

Supplementary Information

The online version of this article contains supplementary material available (10.1007/s13755-021-00142-y).

Comparison of Biofeedback and Combined Interventions on Athlete's Performance

The aim of this study was the comparison of neurofeedback and biofeedback as a combination, against biofeedback intervention alone on athletic performance. 45 novice basketball players were allocated into three groups and assigned accordingly, two experimental and one control group. The experimental group 1 received 24 biofeedback sessions only, experimental group 2 received 24 biofeedback and neurofeedback sessions combined, whereas the control group didn't receive any form of intervention. Athletic performance scales were used before and after each intervention and multivariate analysis of covariance was used to compare the two groups. Results showed that in comparison to the control group, the athletic performance scales scores in both experimental groups were significantly increased. Furthermore, in experimental group 2 (combined method), we noticed a significantly greater improvement in performance levels than experimental group 1. We concluded that neurofeedback and biofeedback interventions combined, can be used as an effective method to enhance athletic performance.

A randomized controlled trial (RCT) to explore the effect of audio-visual entrainment among psychological disorders

BACKGROUND AND AIM

Although many mental disorders have relevant proud in neurobiological dysfunctions, most intervention approaches neglect neurophysiological features or use pharmacological intervention alone. Non-invasive Brain-Computer Interfaces (BCIs), providing natural ways of modulating mood states, can be promoted as an alternative intervention to cope with neurobiological dysfunction.

METHODS

A BCI prototype was proposed to feedback a person's affective state such that a closed-loop interaction between the participant's brain responses and the musical stimuli is established. It feedbacks in real-time flickering lights matching with the individual's brain rhythms undergo to auditory stimuli. A RCT was carried out on 15 individuals of both genders (mean age = 49.27 years) with anxiety and depressive spectrum disorders randomly assigned to 2 groups (experimental vs. active control).

RESULTS

Outcome measures revealed either a significant decrease in Hamilton Rating Scale for Depression (HAM-D) scores and gains in cognitive functions only for participants who undergone to the experimental treatment. Variability in HAM-D scores seems explained by the changes in beta 1, beta 2 and delta bands. Conversely, the rise in cognitive function scores appear associated with theta variations.

CONCLUSIONS

Future work needs to validate the relationship proposed here between music and brain responses. Findings of the present study provided support to a range of research examining BCI brain modulation and contributes to the understanding of this technique as instruments to alternative therapies We believe that Neuro-Upper can be used as an effective new tool for investigating affective responses, and emotion regulation (www.actabiomedica.it).

Differential Effects of Up- and Down-Regulation of SMR Coherence on EEG Activity and Memory Performance: A Neurofeedback Training Study

Modulating connectivity measures in EEG-based neurofeedback studies is assumed to be a promising therapeutic and training tool. However, little is known so far about its effects and trainability. In the present study, we investigated the effects of up- and down-regulating SMR (12-15 Hz) coherence by means of neurofeedback training on EEG activity and memory functions. Twenty adults performed 10 neurofeedback training sessions in which half of them tried to increase EEG coherence between Cz and CPz in the SMR frequency range, while the other half tried to down-regulate coherence. Up-regulation of SMR coherence led to between- and within-session changes in EEG coherence. SMR power increased across neurofeedback training sessions but not within training sessions. Cross-over training effects on baseline EEG measures were also observed in this group. Up-regulation of SMR coherence was also associated with improvements in memory functions when comparing pre- and post-test results. Participants were not able to down-regulate SMR coherence. This group did not show any changes in baseline EEG measures or memory functions comparing pre- and post-test. Our results provide insights in the trainability and effects of connectivity-based neurofeedback training and indications for its practical application.

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.

Psychological, Neurophysiological, and Mental Factors Associated With Gamma-Enhancing Neurofeedback Success

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.