Predictors of neurofeedback training outcome: A systematic review

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.

Multimodal and hemispheric graph-theoretical brain network predictors of learning efficacy for frontal alpha asymmetry neurofeedback

EEG neurofeedback using frontal alpha asymmetry (FAA) has been widely used for emotion regulation, but its effectiveness is controversial. Studies indicated that individual differences in neurofeedback training can be traced to neuroanatomical and neurofunctional features. However, they only focused on regional brain structure or function and overlooked possible neural correlates of the brain network. Besides, no neuroimaging predictors for FAA neurofeedback protocol have been reported so far. We designed a single-blind pseudo-controlled FAA neurofeedback experiment and collected multimodal neuroimaging data from healthy participants before training. We assessed the learning performance for evoked EEG modulations during training (L1) and at rest (L2), and investigated performance-related predictors based on a combined analysis of multimodal brain networks and graph-theoretical features. The main findings of this study are described below. First, both real and sham groups could increase their FAA during training, but only the real group showed a significant increase in FAA at rest. Second, the predictors during training blocks and at rests were different: L1 was correlated with the graph-theoretical metrics (clustering coefficient and local efficiency) of the right hemispheric gray matter and functional networks, while L2 was correlated with the graph-theoretical metrics (local and global efficiency) of the whole-brain and left the hemispheric functional network. Therefore, the individual differences in FAA neurofeedback learning could be explained by individual variations in structural/functional architecture, and the correlated graph-theoretical metrics of learning performance indices showed different laterality of hemispheric networks. These results provided insight into the neural correlates of inter-individual differences in neurofeedback learning.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11571-023-09939-x.

Could neurofeedback improve therapist-patient communication? Considering the potential for neuroscience informed examinations of the psychotherapeutic relationship

Empathic communication between a patient and therapist is an essential component of psychotherapy. However, finding objective neural markers of the quality of the psychotherapeutic relationship have been elusive. Here we conceptualize how a neuroscience-informed approach involving real-time neurofeedback, facilitated via existing functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) technologies, could provide objective information for facilitating therapeutic rapport. We propose several neurofeedback-assisted psychotherapy (NF-AP) approaches that could be studied as a way to optimize the experience of the individual patient and therapist across the spectrum of psychotherapeutic treatment. Finally, we consider how the possible strengths of these approaches are balanced by their current limitations and discuss the future prospects of NF-AP.

Mu-Suppression Neurofeedback Training Targeting the Mirror Neuron System: A Pilot Study

Neurofeedback training (NFT) is a promising adjuvant intervention method. The desynchronization of mu rhythm (8-13 Hz) in the electroencephalogram (EEG) over centro-parietal areas is known as a valid indicator of mirror neuron system (MNS) activation, which has been associated with social skills. Still, the effect of neurofeedback training on the MNS requires to be well investigated. The present study examined the possible impact of NFT with a mu suppression training protocol encompassing 15 NFT sessions (45 min each) on 16 healthy neurotypical participants. In separate pre- and post-training sessions, 64-channel EEG was recorded while participants (1) observed videos with various types of movements (including complex goal-directed hand movements and social interaction scenes) and (2) performed the "Reading the Mind in the Eyes Test" (RMET). EEG source reconstruction analysis revealed statistically significant mu suppression during hand movement observation across MNS-attributed fronto-parietal areas after NFT. The frequency analysis showed no significant mu suppression after NFT, despite the fact that numerical mu suppression appeared to be visible in a majority of participants during goal-directed hand movement observation. At the behavioral level, RMET accuracy scores did not suggest an effect of NFT on the ability to interpret subtle emotional expressions, although RMET response times were reduced after NFT. In conclusion, the present study exhibited preliminary and partial evidence that mu suppression NFT can induce mu suppression in MNS-attributed areas. More powerful experimental designs and longer training may be necessary to induce substantial and consistent mu suppression, particularly while observing social scenarios.

Effects of Four Different EEG-Neurofeedback Reinforcement Types in Healthy Individuals - A Pilot Study

EEG neurofeedback (EEG-NFB) is a promising tool for the treatment of depressive disorders. However, many methods for the presentation of neurobiological reactions are available and it is widely unknown which of these feedback options are preferrable. Moreover, the influence of motivation on NFB training success is insufficiently studied. This study analyzed the efficacy of a novel EEG protocol (FC3/Pz) based on findings for NFB in depression. The role of four feedback options (Rumination, Anxiety, Meditation Master, Moving Art) from the NFB software "Brain Assistant" and motivation in EEG-based NFB performance was studied. Regarding "Anxiety" and "Rumination" visual feedback was used to evoke emotions; reinforcement (both negative and positive operant conditioning) was continuous. Regarding "Meditation Master" visual feedback was combined with continuous positive reinforcement. Regarding "Moving Art" 20-min calm nature films with neutral character were used; both visual and auditive feedback were applied. The reinforcement was positive and continuous. 13 healthy participants completed 15 EEG sessions over four months combining simultaneous frontal (aims: reduction of theta-, alpha- and high beta-activity, increase of low and mid beta-activity) and parietal training (aims: reduction of theta-, alpha 1-, mid and high beta-activity, increase of alpha 2- and low beta-activity). We observed significantly more pronounced percentage change in the expected direction for Anxiety than Moving Art (mean difference = 3.32; p = 0.003). The association between motivation and performance was non-significant. Based on these results we conclude that feedback with both negative and positive operant conditioning and emotion evoking effects should be preferred.

Successful learning of alpha up-regulation through neurofeedback training modulates sustained attention

As a fundamental attention function, sustained attention plays a critical role in general cognitive abilities and is closely linked to EEG alpha oscillations. Neurofeedback training (NFT) of alpha activity on different aspects of attention has been studied previously. However, it remains unclear how NFT with up- or down-regulation directions modulates sustained attention. Here we employed a counterbalanced single-blind sham-controlled crossover design, in which healthy young adults underwent one NFT session of alpha up-regulation, one NFT session of alpha down-regulation, and one sham-control NFT session over the posterior area. The session order was counterbalanced with a 7-day interval between each session. After each NFT session, the participants completed a visual continuous temporal expectancy task (vCTET) to assess their sustained attention performance. The results showed that compared to sham-control NFT, successful learning of alpha up-regulation resulted in increased reaction time at the beginning of the attention task but a slower increase over vCTET blocks. On the other hand, successful learning of alpha down-regulation had no impact on attention performance compared to sham-control NFT. These findings suggest that successful learning of alpha up-regulation through NFT could impair initial attention performance but slow down visual attention deterioration over time, i.e., alpha enhancement by NFT stabilizing visual attention.

Near-infrared spectroscopy and electroencephalography neurofeedback for binge-eating disorder: an exploratory randomized trial

BACKGROUND

Binge-eating disorder (BED) co-occurs with neurobehavioral alterations in the processing of disorder-relevant content such as visual food stimuli. Whether neurofeedback (NF) directly targeting them is suited for treatment remains unclear. This study sought to determine feasibility and estimate effects of individualized, functional near-infrared spectroscopy-based real-time NF (rtfNIRS-NF) and high-beta electroencephalography-based NF (EEG-NF), assuming superiority over waitlist (WL).

METHODS

Single-center, assessor-blinded feasibility study with randomization to rtfNIRS-NF, EEG-NF, or WL and assessments at baseline (t0), postassessment (t1), and 6-month follow-up (t2). NF comprised 12 60-min food-specific rtfNIRS-NF or EEG-NF sessions over 8 weeks. Primary outcome was the binge-eating frequency at t1 assessed interview-based. Secondary outcomes included feasibility, eating disorder symptoms, mental and physical health, weight management-related behavior, executive functions, and brain activity at t1 and t2.

RESULTS

In 72 patients (intent-to-treat), the results showed feasibility of NF regarding recruitment, attrition, adherence, compliance, acceptance, and assessment completion. Binge eating improved at t1 by -8.0 episodes, without superiority of NF v. WL (-0.8 episodes, 95% CI -2.4 to 4.0), but with improved estimates in NF at t2 relative to t1. NF was better than WL for food craving, anxiety symptoms, and body mass index, but overall effects were mostly small. Brain activity changes were near zero.

CONCLUSIONS

The results show feasibility of food-specific rtfNIRS-NF and EEG-NF in BED, and no posttreatment differences v. WL, but possible continued improvement of binge eating. Confirmatory and mechanistic evidence is warranted in a double-blind randomized design with long-term follow-up, considering dose-response relationships and modes of delivery.

Self-regulation training for people with knee osteoarthritis: a protocol for a feasibility randomised control trial (MiNT trial)

Introduction

Knee osteoarthritis (OA) is a chronic secondary musculoskeletal pain condition resulting in disability, reduced quality of life, and high societal costs. Pain associated with knee OA is linked to increased sensitivity in sensory, cognitive, and emotional areas of the brain. Self-regulation training targeting brain functioning related to pain experience could reduce pain and its associated disability. Self-regulatory treatments such as mindfulness meditation (MM) and electroencephalography neurofeedback (EEG-NF) training improve clinical outcomes in people with knee OA. A feasibility clinical trial can address factors that could inform the design of the full trial investigating the effectiveness of self-regulation training programmes in people with knee OA. This clinical trial will evaluate the feasibility, safety, acceptability, experience and perceptions of the self-regulatory training programmes.

Methods

The proposed feasibility trial is based on a double-blind (outcome assessor and investigators), three-arm (MM usual care, EEG-NF + usual care and usual care control group) randomised controlled parallel clinical trial. Participants with knee OA will be recruited from the community and healthcare practices. A research assistant (RA) will administer both interventions (20-min sessions, four sessions each week, and 12 sessions over three successive weeks). Feasibility measures (participant recruitment rate, adherence to interventions, retention rate), safety, and acceptability of interventions will be recorded. An RA blinded to the group allocation will record secondary outcomes at baseline, immediately post-intervention (4th week), and 3 months post-intervention. The quantitative outcome measures will be descriptively summarised. The qualitative interviews will evaluate the participants' experiences and perceptions regarding various aspects of the trial, which includes identifying the barriers and facilitators in participating in the trial, evaluating their opinions on the research procedures, such as their preferences for the study site, and determining the level of acceptability of the interventions as potential clinical treatments for managing knee OA. Māori participant perceptions of how assessment and training practices could be acceptable to a Māori worldview will be explored. The interviews will be audio-recorded and analysed thematically.

Discussion

This trial will provide evidence on the feasibility, safety, and acceptability of the MM and EEG-NF training in people with knee OA, thus informing the design of a full randomised clinical control trial.

Amygdala-related electroencephalogram neurofeedback as add-on therapy for treatment-resistant childhood sexual abuse posttraumatic stress disorder: feasibility study

AIM

Childhood sexual abuse (CSA) among women is an alarmingly prevalent traumatic experience that often leads to debilitating and treatment-refractory posttraumatic stress disorder (PTSD), raising the need for novel adjunctive therapies. Neuroimaging investigations systematically report that amygdala hyperactivity is the most consistent and reliable neural abnormality in PTSD and following childhood abuse, raising the potential of implementing volitional neural modulation using neurofeedback (NF) aimed at down-regulating amygdala activity. This study aimed to reliably probe limbic activity but overcome the limited applicability of functional magnetic resonance imaging (fMRI) NF by using a scalable electroencephalogram NF probe of amygdala-related activity, termed amygdala electrical-finger-print (amyg-EFP) in a randomized controlled trial.

METHOD

Fifty-five women with CSA-PTSD who were in ongoing intensive trauma-focused psychotherapy for a minimum of 1 year but still met Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) PTSD criteria were randomized to either 10 add-on sessions of amyg-EFP-NF training (test group) or continuing psychotherapy (control group). Participants were blindly assessed for PTSD symptoms before and after the NF training period, followed by self-reported clinical follow-up at 1, 3, and 6 months, as well as one session of amygdala real-time fMRI-NF before and after NF training period.

RESULTS

Participants in the test group compared with the control group demonstrated a marginally significant immediate reduction in PTSD symptoms, which progressively improved during the follow-up period. In addition, successful neuromodulation during NF training was demonstrated.

CONCLUSION

This feasibility study for patients with treatment-resistant CSA-PTSD indicates that amyg-EFP-NF is a viable and efficient intervention.

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.

Predictors of neurofeedback treatment outcome in binge-eating disorder: An exploratory study

OBJECTIVE

Knowledge on predictors for treatment response to psychotherapy in binge-eating disorder (BED) is mixed and not yet available for increasingly popular neurofeedback (NF) treatment targeting self-regulation of aberrant brain activity. This study examined eating disorder- and psychopathology-related predictors for NF treatment success in BED.

METHOD

Patients with BED (N = 78) were randomized to 12 sessions of real-time functional near-infrared spectroscopy (rtfNIRS)-NF, targeting individual prefrontal cortex signal up-regulation, electroencephalography (EEG)-NF, targeting down-regulation of fronto-central beta activity, or waitlist (WL). The few studies assessing predictors for clinical outcomes after NF and evidenced predictors for psychotherapy guided the selection of baseline eating disorder-related predictors, including objective binge-eating (OBE) frequency, eating disorder psychopathology (EDP), food cravings, and body mass index (BMI), and general psychopathology-related predictors, including depressive and anxiety symptoms, impulsivity, emotion dysregulation, and self-efficacy. These questionnaire-based or objectively assessed (BMI) predictors were regressed on outcomes OBE frequency and EDP as key features of BED at post-treatment (t1) and 6-month follow-up (t2) in preregistered generalized mixed models (https://osf.io/4aktp).

RESULTS

Higher EDP, food cravings, and BMI predicted worse outcomes across all groups at t1 and t2. General psychopathology-related predictors did not predict outcomes at t1 and t2. Explorative analyses indicated that lower OBE frequency and higher self-efficacy predicted lower OBE frequency, and lower EDP predicted lower EDP after the waiting period in WL.

DISCUSSION

Consistent with findings for psychotherapy, higher eating disorder-related predictors were associated with higher EDP and OBE frequency. The specificity of psychopathological predictors for NF treatment success warrants further examination.

PUBLIC SIGNIFICANCE

This exploratory study firstly assessed eating disorder- and psychopathology-related predictors for neurofeedback treatment outcome in binge-eating disorder and overweight. Findings showed an association between higher eating disorder symptoms and worse neurofeedback outcomes, indicating special needs to be considered in neurofeedback treatment for patients with a higher binge-eating disorder symptom burden. In general, outcomes and assignment to neurofeedback treatment may be improved upon consideration of baseline psychological variables.

Evaluation and treatment approaches for neurological post-acute sequelae of COVID-19: A consensus statement and scoping review from the global COVID-19 neuro research coalition

Post-acute neurological sequelae of COVID-19 affect millions of people worldwide, yet little data is available to guide treatment strategies for the most common symptoms. We conducted a scoping review of PubMed/Medline from 1/1/2020-4/1/2023 to identify studies addressing diagnosis and treatment of the most common post-acute neurological sequelae of COVID-19 including: cognitive impairment, sleep disorders, headache, dizziness/lightheadedness, fatigue, weakness, numbness/pain, anxiety, depression and post-traumatic stress disorder. Utilizing the available literature and international disease-specific society guidelines, we constructed symptom-based differential diagnoses, evaluation and management paradigms. This pragmatic, evidence-based consensus document may serve as a guide for a holistic approach to post-COVID neurological care and will complement future clinical trials by outlining best practices in the evaluation and treatment of post-acute neurological signs/symptoms.

Distinct effects of different neurofeedback protocols on the neural mechanisms of response inhibition in ADHD

OBJECTIVE

In attention deficit/hyperactivity disorder (ADHD), impaired response inhibition is frequently observed. A promising non-pharmacological treatment is electroencephalography (EEG)-neurofeedback (NF) training. However, the widely used theta-down/beta-up regulation (↓θ↑β) NF protocol may not be optimal for targeting these deficits. We examined how neurofeedback protocols training the upregulation of theta and/or beta power affect inhibitory control in children and adolescents with ADHD.

METHODS

64 patients with ADHD took part in the three NF trainings. Aside from parent-reported ADHD symptoms and behavioural performance data, neurophysiological parameters collected via a Go/Nogo task and corrected to account for intraindividual variability were compared in a pre-post design and to an ADHD (n = 20) as well as a typically developing control group (n = 24).

RESULTS

The examined NF protocols resulted in similar improvements in response inhibition with the neurophysiological mechanisms differing substantially. The upregulation of theta led to a specific Nogo-P3 increase, while training beta upregulation as well as the combined protocol resulted in less specific effects.

CONCLUSIONS

This study shows distinct effects of different theta/beta-neurofeedback protocols on the neural mechanisms underlying improvements in response inhibition in patients with ADHD.

SIGNIFICANCE

These effects shed further light on the oscillatory dynamics underlying cognitive control in ADHD and how these may be targeted in neurofeedback treatments.

Long-term improvements in executive functions after frontal-midline theta neurofeedback in a (sub)clinical group

Impairments in executive functions (EFs) are common across disorders and can greatly affect daily functioning. Frontal-midline (FM) theta neurofeedback (NF) has been shown effective in enhancing EFs in healthy adults, prompting interest in exploring its potential as an alternative treatment for EFs in (sub)clinical samples. This study aims to determine the effects of FM theta NF on EFs in a sample of 58 adults (aged 20-60 years) with pronounced subjective EF complaints in daily life. Using a pre/post/follow-up design with a sham NF group, the present study assessed upregulation of FM theta in an eight-session individualized FM theta NF training and its immediate and long-term transfer effects on objective and subjective measures of EFs. These included behavioral performance on EF tasks assessing working memory updating (N-back task), set-shifting (Switching task), conflict monitoring (Stroop task), and response inhibition (Stop-signal task), as well as FM theta power during these tasks, and subjective EFs in daily life (BRIEF-A). The results indicate that there are only differences in FM theta self-upregulation between the NF group and sham group when non-responders are excluded from the analysis. Regarding behavioral transfer effects, NF-specific improvements are found in working memory updating reaction time (RT) and conflict monitoring RT variability at 6-month follow-up, but not immediately after the NF training. The effects on FM theta power during the EF tasks and subjective changes in EFs in daily life were not specific to the NF training. As a next step, research should identify the best predictors to stratify NF training, as well as explore ways to improve NF responsiveness, for instance by increasing neuroplasticity.

Neurofeedback Treatment Affects Affective Symptoms, But Not Perceived Cognitive Impairment in Cancer Patients: Results of an Explorative Randomized Controlled Trial

BACKGROUND

EEG biofeedback (NF) is an established therapy to enable individuals to influence their own cognitive-emotional state by addressing changes in brainwaves. Psycho-oncological approaches of NF in cancer patients are rare and effects are hardly studied.

OBJECTIVE

The aim of this explorative, randomized controlled trial was to test the effectiveness of an alpha and theta NF training protocol, compared to mindfulness based therapy as an established psycho-oncological treatment.

METHODS

Of initially 62 screened patients, 56 were included (inclusion criteria were cancer independent of tumor stage, age >18 years, German speaking; exclusion criteria suicidal ideation, brain tumor). Randomization and stratification (tumor stage) was conducted by a computer system. Participants got 10 sessions over 5 weeks, in (a) an NF intervention (n = 21; 13 female, 8 male; MAge = 52.95(10 519); range = 31 to 73 years)) or (b) a mindfulness group therapy as control condition (CG; n = 21; ie, 15 female, 6 male; MAge = 50.33(8708); range = 32 to 67 years)). Outcome parameters included self-reported cognitive impairment (PCI) as primary outcome, and secondary outcomes of emotional distress (DT, PHQ-8, GAD-7), fatigue (MFI-20), rumination (RSQ), quality of life (QoL, EORTC-30 QoL), self-efficacy (GSE), and changes in EEG alpha, and theta-beta band performance in the NF condition.

RESULTS

No changes in cognitive impairment were found (P = .079), neither in NF nor CG. High affective distress was evident, with 70.7% showing elevated distress and 34.1% showing severe depressive symptoms. Affective symptoms of distress (P ≤ .01), depression (P ≤ .05) and generalized anxiety (P ≤ .05) decreased significantly over time. No differences between NF and CG were found. There was a significant increase of the alpha band (P ≤ .05; N = 15) over the NF sessions. Self-efficacy predicted QoL increase in NF with P ≤ .001 and an explained variance of 48.2%.

CONCLUSION

This is the first study to investigate NF technique with regard to basic mechanisms of effectiveness in a sample of cancer patients, compared to an established psycho-oncological intervention in this field. Though there were no changes in cognitive impairment, present data show that NF improves affective symptoms comparably to mindfulness-based therapy and even more pronounced in QoL and self-efficacy.Trial registration: ID: DRKS00015773.

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.

Multimodal resting-state connectivity predicts affective neurofeedback performance

Neurofeedback has been suggested as a potential complementary therapy to different psychiatric disorders. Of interest for this approach is the prediction of individual performance and outcomes. In this study, we applied functional connectivity-based modeling using electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) modalities to (i) investigate whether resting-state connectivity predicts performance during an affective neurofeedback task and (ii) evaluate the extent to which predictive connectivity profiles are correlated across EEG and fNIRS techniques. The fNIRS oxyhemoglobin and deoxyhemoglobin concentrations and the EEG beta and gamma bands modulated by the alpha frequency band (beta-m-alpha and gamma-m-alpha, respectively) recorded over the frontal cortex of healthy subjects were used to estimate functional connectivity from each neuroimaging modality. For each connectivity matrix, relevant edges were selected in a leave-one-subject-out procedure, summed into "connectivity summary scores" (CSS), and submitted as inputs to a support vector regressor (SVR). Then, the performance of the left-out-subject was predicted using the trained SVR model. Linear relationships between the CSS across both modalities were evaluated using Pearson's correlation. The predictive model showed a mean absolute error smaller than 20%, and the fNIRS oxyhemoglobin CSS was significantly correlated with the EEG gamma-m-alpha CSS (r = -0.456, p = 0.030). These results support that pre-task electrophysiological and hemodynamic resting-state connectivity are potential predictors of neurofeedback performance and are meaningfully coupled. This investigation motivates the use of joint EEG-fNIRS connectivity as outcome predictors, as well as a tool for functional connectivity coupling investigation.

How standardized are “standard protocols”? Variations in protocol and performance evaluation for slow cortical potential neurofeedback: A systematic review

Neurofeedback (NF) aims to alter neural activity by enhancing self-regulation skills. Over the past decade NF has received considerable attention as a potential intervention option for many somatic and mental conditions and ADHD in particular. However, placebo-controlled trials have demonstrated insufficient superiority of NF compared to treatment as usual and sham conditions. It has been argued that the reason for limited NF effects may be attributable to participants' challenges to self-regulate the targeted neural activity. Still, there is support of NF efficacy when only considering so-called “standard protocols,” such as Slow Cortical Potential NF training (SCP-NF). This PROSPERO registered systematic review following PRISMA criteria searched literature databases for studies applying SCP-NF protocols. Our review focus concerned the operationalization of self-regulatory success, and protocol-details that could influence the evaluation of self-regulation. Such details included; electrode placement, number of trials, length per trial, proportions of training modalities, handling of artifacts and skill-transfer into daily-life. We identified a total of 63 eligible reports published in the year 2000 or later. SCP-NF protocol-details varied considerably on most variables, except for electrode placement. However, due to the increased availability of commercial systems, there was a trend to more uniform protocol-details. Although, token-systems are popular in SCP-NF for ADHD, only half reported a performance-based component. Also, transfer exercises have become a staple part of SCP-NF. Furthermore, multiple operationalizations of regulatory success were identified, limiting comparability between studies, and perhaps usefulness of so-called transfer-exercises, which purpose is to facilitate the transfer of the self-regulatory skills into every-day life. While studies utilizing SCP as Brain-Computer-Interface mainly focused on the acquisition of successful self-regulation, clinically oriented studies often neglected this. Congruently, rates of successful regulators in clinical studies were mostly low (<50%). The relation between SCP self-regulation and behavior, and how symptoms in different disorders are affected, is complex and not fully understood. Future studies need to report self-regulation based on standardized measures, in order to facilitate both comparability and understanding of the effects on symptoms. When applied as treatment, future SCP-NF studies also need to put greater emphasis on the acquisition of self-regulation (before evaluating symptom outcomes).

Source localized infraslow neurofeedback training in people with chronic painful knee osteoarthritis: A randomized, double-blind, sham-controlled feasibility clinical trial

Persistent pain is a key symptom in people living with knee osteoarthritis (KOA). Infra-slow Neurofeedback (ISF-NF) training is a recent development focusing on modulating cortical slow-wave activity to improve pain outcomes. A parallel, two-armed double-blinded, randomized sham-controlled, feasibility clinical trial aimed to determine the feasibility and safety of a novel electroencephalography-based infraslow fluctuation neurofeedback (EEG ISF-NF) training in people with KOA and determine the variability of clinical outcomes and EEG changes following NF training. Eligible participants attended nine 30-min ISF-NF training sessions involving three cortical regions linked to pain. Feasibility measures were monitored during the trial period. Pain and functional outcomes were measured at baseline, post-intervention, and follow-up after 2 weeks. Resting-state EEG was recorded at baseline and immediate post-intervention. Participants were middle-aged (61.7 ± 7.6 years), New Zealand European (90.5%), and mostly females (62%) with an average knee pain duration of 4 ± 3.4 years. The study achieved a retention rate of 91%, with 20/22 participants completing all the sessions. Participants rated high levels of acceptance and “moderate to high levels of perceived effectiveness of the training.” No serious adverse events were reported during the trial. Mean difference (95% CI) for clinical pain and function measures are as follows for pain severity [active: 0.89 ± 1.7 (−0.27 to 2.0); sham: 0.98 ± 1.1 (0.22–1.7)], pain interference [active: 0.75 ± 2.3 (−0.82 to 2.3); Sham: 0.89 ± 2.1 (−0.60 to 2.4)], pain unpleasantness [active: 2.6 ± 3.7 (0.17–5.1); sham: 2.8 ± 3 (0.62–5.0)] and physical function [active: 6.2 ± 13 (−2.6 to 15); sham: 1.6 ± 12 (−6.8 to 10)]. EEG sources demonstrated frequency-specific neuronal activity, functional connectivity, and ISF ratio changes following NF training. The findings of the study indicated that the ISF-NF training is a feasible, safe, and acceptable intervention for pain management in people with KOA, with high levels of perceived effectiveness. The study also reports the variability in clinical, brain activity, and connectivity changes following training.

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.

Combined Aerobic Exercise and Neurofeedback Lead to Improved Task-Relevant Intrinsic Network Synchrony

Lifestyle interventions such as exercise and mindfulness training have the potential to ameliorate mental health symptoms and restore dysregulated intrinsic connectivity network (ICN) dynamics, seen in many psychopathologies. Multiple lifestyle interventions, in combination, may interact synergistically for enhanced benefits. While the impacts of lifestyle interventions on subjective measures of mood are well-documented, their impacts on ICN dynamics are not well-established. In this study, we assessed the validity of EEG-derived measures of ICN dynamics as potential markers of mood disorders, by tracking ICN dynamics and mood symptoms through the course of a longitudinal exercise intervention. Specifically, we investigated the separate and combined effects of aerobic exercise and mindfulness-like neurofeedback training on task-linked ICN dynamics of the default mode network (DMN), central executive network (CEN), and salience network (SN). Participants were assigned pseudo-randomly into four experimental conditions—Control, Running, Neurofeedback, and Combined, performing the corresponding intervention for 16 sessions across 8 weeks. Intervention-linked changes in ICN dynamics were studied using EEG-based neuroimaging scans before and after the 8-week intervention, during which participants performed multiple blocks of autobiographical memory recall (AM) and working memory (WM) trials, designed to activate the DMN and CEN, respectively, and to activate the SN in conjunction with the task-appropriate network. The EEG-based features for classification of the three core networks had been identified in our prior research from simultaneously recorded EEG and fMRI during the same AM and WM tasks. We categorized participants as “responders” or “non-responders” based on whether the exercise intervention increased their aerobic capacity (VO2-max) (Running/Combined group), and/or neurofeedback increased the percentage time spent in the calm mindfulness state (Neurofeedback/Combined group). In responders, compared to each intervention alone, the combined exercise-neurofeedback intervention resulted in a more healthy CEN-SN synchrony pattern. Interestingly, non-responders to neurofeedback exhibited a maladaptive pattern of persistent, task-inappropriate DMN-SN synchrony which we speculate could be linked to depressive rumination. Furthermore, the CEN-SN synchrony at baseline predicted NFB response with up to 80% accuracy, demonstrating the potential utility of such network-based biomarkers in personalizing intervention plans.

Results of Neurofeedback in Treatment of Children with ADHD: A Systematic Review of Randomized Controlled Trials

Attention-deficit/hyperactivity disorder (ADHD) is one of the most prevalent disorders in children and adolescents. Neurofeedback, a nonpharmaceutical treatment, has shown promising results. To review the evidence of efficacy of neurofeedback as a treatment for children and adolescents with ADHD. A systematic review of the specific scientific studies published in 1995-2021, identifying and analyzing randomized controlled trials (RCT). A total of 1636 articles were identified and 165 met inclusion criteria, of which 67 were RCTs. Neurofeedback training was associated with significant long-term reduction in symptoms of ADHD. Though limitations exist regarding conclusions about the specific effects of neurofeedback, the review documents improvements in school, social, and family environments.

Training the Conductor of the Brainwave Symphony: In Search of a Common Mechanism of Action for All Methods of Neurofeedback

There are several different methods of neurofeedback, most of which presume an operant conditioning model whereby the subject learns to control their brain activity in particular regions of the brain and/or at particular brainwave frequencies based on reinforcement. One method, however, called infra-low frequency [ILF] neurofeedback cannot be explained through this paradigm, yet it has profound effects on brain function. Like a conductor of a symphony, recent evidence demonstrates that the primary ILF (typically between 0.01–0.1 Hz), which correlates with the fluctuation of oxygenated and deoxygenated blood in the brain, regulates all of the classic brainwave bands (i.e. alpha, theta, delta, beta, gamma). The success of ILF neurofeedback suggests that all forms of neurofeedback may work through a similar mechanism that does not fit the operant conditioning paradigm. This chapter focuses on the possible mechanisms of action for ILF neurofeedback, which may be generalized, based on current evidence.

Utility of Cognitive Neural Features for Predicting Mental Health Behaviors

Cognitive dysfunction underlies common mental health behavioral symptoms including depression, anxiety, inattention, and hyperactivity. In this study of 97 healthy adults, we aimed to classify healthy vs. mild-to-moderate self-reported symptoms of each disorder using cognitive neural markers measured with an electroencephalography (EEG). We analyzed source-reconstructed EEG data for event-related spectral perturbations in the theta, alpha, and beta frequency bands in five tasks, a selective attention and response inhibition task, a visuospatial working memory task, a Flanker interference processing task, and an emotion interference task. From the cortical source activation features, we derived augmented features involving co-activations between any two sources. Logistic regression on the augmented feature set, but not the original feature set, predicted the presence of psychiatric symptoms, particularly for anxiety and inattention with >80% sensitivity and specificity. We also computed current flow closeness and betweenness centralities to identify the “hub” source signal predictors. We found that the Flanker interference processing task was the most useful for assessing the connectivity hubs in general, followed by the inhibitory control go-nogo paradigm. Overall, these interpretable machine learning analyses suggest that EEG biomarkers collected on a rapid suite of cognitive assessments may have utility in classifying diverse self-reported mental health symptoms.

Is There Evidence for the Specificity of Closed-Loop Brain Training in the Treatment of Internalizing Disorders? A Systematic Review

Introduction

Internalizing disorders (IDs), e.g., major depressive disorder (MDD), posttraumatic stress disorder (PTSD), obsessive-compulsive disorder (OCD) are the most prevalent psychopathologies experienced worldwide. Current first-line therapies (i.e., pharmacotherapy and/or psychotherapy) offer high failure rates, limited accessibility, and substantial side-effects. Electroencephalography (EEG) guided closed-loop brain training, also known as EEG-neurofeedback (EEG-NFB), is believed to be a safe and effective alternative, however, there is much debate in the field regarding the existence of specificity [i.e., clinical effects specific to the modulation of the targeted EEG variable(s)]. This review was undertaken to determine if there is evidence for EEG-NFB specificity in the treatment of IDs.

Methods

We considered only randomized, double-blind, sham-controlled trials. Outcomes of interest included self/parent/teacher reports and clinician ratings of ID-related symptomatology.

Results

Of the four reports (total participant number = 152) meeting our eligibility criteria, three had point estimates suggesting small to moderate effect sizes favoring genuine therapy over sham, however, due to small sample sizes, all 95% confidence intervals (CIs) were wide and spanned the null. The fourth trial had yet to post results as of the submission date of this review. The limited overall number of eligible reports (and participants), large degree of inter-trial heterogeneity, and restricted span of ID populations with published/posted outcome data (i.e., PTSD and OCD) precluded a quantitative synthesis.

Discussion

The current literature suggests that EEG-NFB may induce specific effects in the treatment of some forms of IDs, however, the evidence is very limited. Ultimately, more randomized, double-blind, sham-controlled trials encompassing a wider array of ID populations are needed to determine the existence and, if present, degree of EEG-NFB specificity in the treatment of IDs.

Systematic Review Registration

[https://www.crd.york.ac.uk/prospero], identifier [CRD42020159702].

Validation of eyes-closed resting alpha amplitude predicting neurofeedback learning of upregulation alpha activity

Neurofeedback training (NFT) enables users to learn self-control of EEG activity of interest and then to create many benefits on cognitive function. A considerable number of nonresponders who fail to achieve successful NFT have often been reported in the within-session prediction. This study aimed to investigate successful EEG NFT of upregulation alpha activity in terms of trainability, independence, and between-session predictability validation. Forty-six participants completed 12 training sessions. Spectrotemporal analysis revealed the upregulation success on brain activity of 8-12 Hz exclusively to demonstrate trainability and independence of alpha NFT. Three learning indices of between-session changes exhibited significant correlations with eyes-closed resting state (ECRS) alpha amplitude before the training exclusively. Through a stepwise linear discriminant analysis, the prediction model of ECRS's alpha frequency band amplitude exhibited the best accuracy (89.1%) validation regarding the learning index of increased alpha amplitude on average. This study performed a systematic analysis on NFT success, the performance of the 3 between-session learning indices, and the validation of ECRS alpha activity for responder prediction. The findings would assist researchers in obtaining insight into the training efficacy of individuals and then attempting to adapt an efficient strategy in NFT success.

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.

Multimodal Neuroimaging Predictors of Learning Performance of Sensorimotor Rhythm Up-Regulation Neurofeedback

Electroencephalographic (EEG) neurofeedback (NFB) is a popular neuromodulation method to help one selectively enhance or inhibit his/her brain activities by means of real-time visual or auditory feedback of EEG signals. Sensory motor rhythm (SMR) NFB protocol has been applied to improve cognitive performance, but a large proportion of participants failed to self-regulate their brain activities and could not benefit from NFB training. Therefore, it is important to identify the neural predictors of SMR up-regulation NFB training performance for a better understanding the mechanisms of individual difference in SMR NFB. Twenty-seven healthy participants (12 males, age: 23.1 ± 2.36) were enrolled to complete three sessions of SMR up-regulation NFB training and collection of multimodal neuroimaging data [resting-state EEG, structural magnetic resonance imaging (MRI), and resting-state functional MRI (fMRI)]. Correlation analyses were performed between within-session NFB learning index and anatomical and functional brain features extracted from multimodal neuroimaging data, in order to identify the neuroanatomical and neurophysiological predictors for NFB learning performance. Lastly, machine learning models were trained to predict NFB learning performance using features from each modality as well as multimodal features. According to our results, most participants were able to successfully increase the SMR power and the NFB learning performance was significantly correlated with a set of neuroimaging features, including resting-state EEG powers, gray/white matter volumes from MRI, regional and functional connectivity (FC) of resting-state fMRI. Importantly, results of prediction analysis indicate that NFB learning index can be better predicted using multimodal features compared with features of single modality. In conclusion, this study highlights the importance of multimodal neuroimaging technique as a tool to explain the individual difference in within-session NFB learning performance, and could provide a theoretical framework for early identification of individuals who cannot benefit from NFB training.

Enhancing the Effects of Neurofeedback Training: The Motivational Value of the Reinforcers

The brain activity that is measured by electroencephalography (EEG) can be modified through operant conditioning, specifically using neurofeedback (NF). NF has been applied to several disorders claiming that a change in the erratic brain activity would be accompanied by a reduction of the symptoms. However, the expected results are not always achieved. Some authors have suggested that the lack of an adequate response may be due to an incorrect application of the operant conditioning principles. A key factor in operant conditioning is the use of reinforcers and their value in modifying behavior, something that is not always sufficiently taken into account. This work aims to clarify the relevance of the motivational value versus the purely informational value of the reinforcer. In this study, 113 subjects were randomly assigned two different reinforcer conditions: a selected reinforcer—the subjects subjectively selected the reinforcers—or an imposed reinforcer—the reinforcers were assigned by the experimenter—and both groups undertook NF sessions to enhance the sensorimotor rhythm (SMR). In addition, the selected reinforcer group was divided into two subgroups: one receiving real NF and the other one sham NF. There were no significant differences between the groups at baseline in terms of SMR amplitude. After the intervention, only those subjects belonging to the selected reinforcer group and receiving real NF increased their SMR. Our results provide evidence for the importance of the motivational value of the reinforcer in Neurofeedback success.

Individual Alpha Peak Frequency, an Important Biomarker for Live Z-Score Training Neurofeedback in Adolescents with Learning Disabilities

Learning disabilities (LDs) have an estimated prevalence between 5% and 9% in the pediatric population and are associated with difficulties in reading, arithmetic, and writing. Previous electroencephalography (EEG) research has reported a lag in alpha-band development in specific LD phenotypes, which seems to offer a possible explanation for differences in EEG maturation. In this study, 40 adolescents aged 10–15 years with LDs underwent 10 sessions of Live Z-Score Training Neurofeedback (LZT-NF) Training to improve their cognition and behavior. Based on the individual alpha peak frequency (i-APF) values from the spectrogram, a group with normal i-APF (ni-APF) and a group with low i-APF (li-APF) were compared in a pre-and-post-LZT-NF intervention. There were no statistical differences in age, gender, or the distribution of LDs between the groups. The li-APF group showed a higher theta absolute power in P4 (p = 0.016) at baseline and higher Hi-Beta absolute power in F3 (p = 0.007) post-treatment compared with the ni-APF group. In both groups, extreme waves (absolute Z-score of ≥1.5) were more likely to move toward the normative values, with better results in the ni-APF group. Conversely, the waves within the normal range at baseline were more likely to move out of the range after treatment in the li-APF group. Our results provide evidence of a viable biomarker for identifying optimal responders for the LZT-NF technique based on the i-APF metric reflecting the patient’s neurophysiological individuality.

A systematic review of fMRI neurofeedback reporting and effects in clinical populations

Real-time fMRI-based neurofeedback is a relatively young field with a potential to impact the currently available treatments of various disorders. In order to evaluate the evidence of clinical benefits and investigate how consistently studies report their methods and results, an exhaustive search of fMRI neurofeedback studies in clinical populations was performed. Reporting was evaluated using a limited number of Consensus on the reporting and experimental design of clinical and cognitive-behavioral neurofeedback studies (CRED-NF checklist) items, which was, together with a statistical power and sensitivity calculation, used to also evaluate the existing evidence of the neurofeedback benefits on clinical measures. The 62 found studies investigated regulation abilities and/or clinical benefits in a wide range of disorders, but with small sample sizes and were therefore unable to detect small effects. Most points from the CRED-NF checklist were adequately reported by the majority of the studies, but some improvements are suggested for the reporting of group comparisons and relations between regulation success and clinical benefits. To establish fMRI neurofeedback as a clinical tool, more emphasis should be placed in the future on using larger sample sizes determined through a priori power calculations and standardization of procedures and reporting.

Regression Networks for Neurophysiological Indicator Evaluation in Practicing Motor Imagery Tasks

Motor Imagery (MI) promotes motor learning in activities, like developing professional motor skills, sports gestures, and patient rehabilitation. However, up to 30% of users may not develop enough coordination skills after training sessions because of inter and intra-subject variability. Here, we develop a data-driven estimator, termed Deep Regression Network (DRN), which jointly extracts and performs the regression analysis in order to assess the efficiency of the individual brain networks in practicing MI tasks. The proposed double-stage estimator initially learns a pool of deep patterns, extracted from the input data, in order to feed a neural regression model, allowing for infering the distinctiveness between subject assemblies having similar variability. The results, which were obtained on real-world MI data, prove that the DRN estimator fosters pre-training neural desynchronization and initial training synchronization to predict the bi-class accuracy response, thus providing a better understanding of the Brain-Computer Interface inefficiency of subjects.