Delineating implicit and explicit processes in neurofeedback learning

Mechanisms of brain self-regulation: psychological factors, mechanistic models and neural substrates

While neurofeedback represents a promising tool for neuroscience and a brain self-regulation approach to psychological rehabilitation, the field faces several problems and challenges. Current research has shown great variability and even failure among human participants in learning to self-regulate target features of brain activity with neurofeedback. A better understanding of cognitive mechanisms, psychological factors and neural substrates underlying self-regulation might help improve neurofeedback's scientific and clinical practices. This article reviews the current understanding of the neural mechanisms of brain self-regulation by drawing on findings from human and animal studies in neurofeedback, brain-computer/machine interfaces and neuroprosthetics. In this article, we look closer at the following topics: cognitive processes and psychophysiological factors affecting self-regulation, theoretical models and neural substrates underlying self-regulation, and finally, we provide an outlook on the outstanding gaps in knowledge and technical challenges. This article is part of the theme issue 'Neurofeedback: new territories and neurocognitive mechanisms of endogenous neuromodulation'.

Online self-evaluation of fMRI-based neurofeedback performance

This study explores the subjective evaluation of supplementary motor area (SMA) regulation performance in a real-time functional magnetic resonance imaging neurofeedback (fMRI-NF) task. In fMRI-NF, people learn how to self-regulate their brain activity by performing mental actions to achieve a certain target level (TL) of blood-oxygen-level-dependent (BOLD) activation. Here, we studied two types of self-evaluation: performance predictions and perceived confidence in the prediction judgement. Participants completed three sessions of SMA regulation in a 7 T fMRI scanner, performing a mental drawing task. During each trial, they modulated their imagery strategy to achieve one of two different levels of SMA activation and reported a performance prediction and their confidence in the prediction before receiving delayed BOLD-activation feedback. Results show that participants' performance predictions improved with learning throughout the three sessions, and that these improvements were not driven exclusively by their knowledge of previous performance. Confidence reports on the other hand showed no change throughout training and did not correlate with better and worse predictions. In addition to shedding light on mechanisms of internal self-evaluation during neurofeedback training, these results also point to a dissociation between predictions of performance and confidence reports in the presence of feedback. This article is part of the theme issue 'Neurofeedback: new territories and neurocognitive mechanisms of endogenous neuromodulation'.

Real-Time fMRI Neurofeedback Training of Selective Attention in Older Adults

BACKGROUND

Selective attention declines with age, due to age-related functional changes in dorsal anterior cingulate cortex (dACC). Real-time functional magnetic resonance imaging (rtfMRI) neurofeedback has been used in young adults to train volitional control of brain activity, including in dACC.

METHODS

For the first time, this study used rtfMRI neurofeedback to train 19 young and 27 older adults in volitional up- or down-regulation of bilateral dACC during a selective attention task.

RESULTS

Older participants in the up-regulation condition (experimental group) showed greater reward points and dACC BOLD signal across training sessions, reflective of neurofeedback training success; and faster reaction time and better response accuracy, suggesting behavioral benefits on selective attention. These effects were not observed for older participants in the down-regulation condition (inverse condition control group), supporting specificity of volitional dACC up-regulation training in older adults. These effects were, unexpectedly, also not observed for young participants in the up-regulation condition (age control group), perhaps due to a lack of motivation to continue the training.

CONCLUSIONS

These findings provide promising first evidence of functional plasticity in dACC in late life via rtfMRI neurofeedback up-regulation training, enhancing selective attention, and demonstrate proof of concept of rtfMRI neurofeedback training in cognitive aging.

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.

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.

Simulated operant reflex conditioning environment reveals effects of feedback parameters

Operant conditioning of neural activation has been researched for decades in humans and animals. Many theories suggest two parallel learning processes, implicit and explicit. The degree to which feedback affects these processes individually remains to be fully understood and may contribute to a large percentage of non-learners. Our goal is to determine the explicit decision-making processes in response to feedback representing an operant conditioning environment. We developed a simulated operant conditioning environment based on a feedback model of spinal reflex excitability, one of the simplest forms of neural operant conditioning. We isolated the perception of the feedback signal from self-regulation of an explicit unskilled visuomotor task, enabling us to quantitatively examine feedback strategy. Our hypothesis was that feedback type, biological variability, and reward threshold affect operant conditioning performance and operant strategy. Healthy individuals (N = 41) were instructed to play a web application game using keyboard inputs to rotate a virtual knob representative of an operant strategy. The goal was to align the knob with a hidden target. Participants were asked to "down-condition" the amplitude of the virtual feedback signal, which was achieved by placing the knob as close as possible to the hidden target. We varied feedback type (knowledge of performance, knowledge of results), biological variability (low, high), and reward threshold (easy, moderate, difficult) in a factorial design. Parameters were extracted from real operant conditioning data. Our main outcomes were the feedback signal amplitude (performance) and the mean change in dial position (operant strategy). We observed that performance was modulated by variability, while operant strategy was modulated by feedback type. These results show complex relations between fundamental feedback parameters and provide the principles for optimizing neural operant conditioning for non-responders.

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.

Unconscious Manipulation of Conceptual Representations with Decoded Neurofeedback Impacts Search Behavior

The necessity of conscious awareness in human learning has been a long-standing topic in psychology and neuroscience. Previous research on non-conscious associative learning is limited by the low signal-to-noise ratio of the subliminal stimulus, and the evidence remains controversial, including failures to replicate. Using functional MRI decoded neurofeedback, we guided participants from both sexes to generate neural patterns akin to those observed when visually perceiving real-world entities (e.g., dogs). Importantly, participants remained unaware of the actual content represented by these patterns. We utilized an associative DecNef approach to imbue perceptual meaning (e.g., dogs) into Japanese hiragana characters that held no inherent meaning for our participants, bypassing a conscious link between the characters and the dogs concept. Despite their lack of awareness regarding the neurofeedback objective, participants successfully learned to activate the target perceptual representations in the bilateral fusiform. The behavioral significance of our training was evaluated in a visual search task. DecNef and control participants searched for dogs or scissors targets that were pre-cued by the hiragana used during DecNef training or by a control hiragana. The DecNef hiragana did not prime search for its associated target but, strikingly, participants were impaired at searching for the targeted perceptual category. Hence, conscious awareness may function to support higher-order associative learning. Meanwhile, lower-level forms of re-learning, modification, or plasticity in existing neural representations can occur unconsciously, with behavioral consequences outside the original training context. The work also provides an account of DecNef effects in terms of neural representational drift.

Effect of a single session of sensorimotor rhythm neurofeedback training on the putting performance of professional golfers

Sensorimotor rhythm (SMR) activity has been associated with automaticity and flow in motor execution. Studies have revealed that neurofeedback training (NFT) of the SMR can improve sports performance; however, few studies have adequately explored the effects of a single session of such NFT or examined the possible mechanisms underlying these effects on sports performance. This study recruited 44 professional golfers to address these gaps in the literature. A crossover design was employed to determine the order of the participation in the NFT and no-training control conditions. The participants were asked to perform 60 10-foot putts while electroencephalograms (EEGs) were recorded before and after the tasks. In pre-and post-tests, visual analog scales were used to assess the psychological states associated with SMR activities including the levels of attention engagement, conscious motor control, and physical relaxation. The results revealed that a single NFT session effectively increased SMR power and improved putting performance compared with the control condition. The subjective assessments also revealed that the participants reported lower attention engagement, less conscious control of the motor details and were more relaxed in the putting task, suggesting that SMR NFT promoted effortless and quiescent mental states during motor preparation for a putting task. This study aligns with theoretical hypotheses and extends current knowledge by revealing that a single session of SMR NFT can effectively enhance SMR power and improve putting performance in professional golfers. It also provides preliminary evidence of the possible underlying mechanisms that drive the effect of SMR NFT on putting performances.

A new EEG neurofeedback training approach in sports: the effects function-specific instruction of Mu rhythm and visuomotor skill performance

Introduction

Achieving optimal visuomotor performance in precision sports relies on maintaining an optimal psychological state during motor preparation. To uncover the optimal psychological state, extensive EEG studies have established a link between the Mu rhythm (8-13 Hz at Cz) and cognitive resource allocation during visuomotor tasks (i.e., golf or shooting). In addition, the new approach in EEG neurofeedback training (NFT), called the function-specific instruction (FSI) approach, for sports involves providing function-directed verbal instructions to assist individuals to control specific EEG parameters and align them with targeted brain activity features. While this approach was initially hypothesized to aid individuals in attaining a particular mental state during NFT, the impact of EEG-NFT involving Mu rhythm on visuomotor performance, especially when contrasting the traditional instruction (TI) approach with the FSI approach, underscores the necessity for additional exploration. Hence, the objective of this study is to investigate the impact of the FSI approach on modulating Mu rhythm through EEG-NFT in the context of visuomotor performance.

Methods

Thirty novice participants were recruited and divided into three groups: function-specific instruction (FSI, four females, six males; mean age = 27.00 ± 7.13), traditional instruction (TI, five females, five males; mean age = 27.00 ± 3.88), and sham control (SC, five females, five males; mean age = 27.80 ± 5.34). These groups engaged in a single-session EEG-NFT and performed golf putting tasks both before and after the EEG-NFT.

Results

The results showed that within the FSI group, single-session NFT with augmented Mu power led to a significant decrease in putting performance (p = 0.013). Furthermore, we noted a marginal significance indicating a slight increase in Mu power and a reduction in the subjective sensation of action control following EEG-NFT (p = 0.119). While there was a positive correlation between Mu power and mean radial error in golf putting performance (p = 0.043), it is important to interpret this relationship cautiously in the context of reduced accuracy in golf putting.

Discussion

The findings emphasize the necessity for extended investigation to attain a more profound comprehension of the nuanced significance of Mu power in visuomotor performance. The study highlights the potential effectiveness of the FSI approach in EEG-NFT and in enhancing visuomotor performance, but it also emphasizes the potential impact of skill level and attentional control, particularly in complex visuomotor tasks.

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.

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.

OPERANT REFLEX CONDITIONING SIMULATION ENVIRONMENT REVEALS EFFECTS OF FEEDBACK PARAMETERS

Operant conditioning of neural activation has been researched for decades in humans and animals. Many theories suggest two parallel learning processes, implicit and explicit. The degree to which feedback affects these processes individually remains to be fully understood and may contribute to a large percentage of non-learners. Our goal is to determine the explicit decision-making processes in response to feedback representing an operant conditioning environment. We developed a simulated operant conditioning environment based on a feedback model of spinal reflex excitability, one of the simplest forms of neural operant conditioning. We isolated the perception of the feedback signal from self-regulation of an explicit unskilled visuomotor task, enabling us to quantitatively examine feedback strategy. Our hypothesis was that feedback type, signal quality and success threshold affect operant conditioning performance and operant strategy. Healthy individuals (N = 41) were instructed to play a web application game using keyboard inputs to rotate a virtual knob representative of an operant strategy. The goal was to align the knob with a hidden target. Participants were asked to "down-condition" the amplitude of the virtual feedback signal, which was achieved by placing the knob as close as possible to the hidden target. We varied feedback type (knowledge of performance, knowledge of results), success threshold (easy, moderate, difficult), and biological variability (low, high) in a factorial design. Parameters were extracted from real operant conditioning data. Our main outcomes were the feedback signal amplitude (performance) and the mean change in dial position (operant strategy). We observed that performance was modulated by variability, while operant strategy was modulated by feedback type. These results show complex relations between fundamental feedback parameters and provide the principles for optimizing neural operant conditioning for non-responders.

Mental strategies and resting state EEG: Effect on high alpha amplitude modulation by neurofeedback in healthy young adults

Neurofeedback (NFB) is a brain-computer interface which allows individuals to modulate their brain activity. Despite the self-regulatory nature of NFB, the effectiveness of strategies used during NFB training has been little investigated. In a single session of NFB training (6*3 min training blocks) with healthy young participants, we experimentally tested if providing a list of mental strategies (list group, N = 46), compared with a group receiving no strategies (no list group, N = 39), affected participants' neuromodulation ability of high alpha (10-12 Hz) amplitude. We additionally asked participants to verbally report the mental strategies used to enhance high alpha amplitude. The verbatim was then classified in pre-established categories in order to examine the effect of type of mental strategy on high alpha amplitude. First, we found that giving a list to the participants did not promote the ability to neuromodulate high alpha activity. However, our analysis of the specific strategies reported by learners during training blocks revealed that cognitive effort and recalling memories were associated with higher high alpha amplitude. Furthermore, the resting amplitude of trained high alpha frequency predicted an amplitude increase during training, a factor that may optimize inclusion in NFB protocols. The present results also corroborate the interrelation with other frequency bands during NFB training. Although these findings are based on a single NFB session, our study represents a further step towards developing effective protocols for high alpha neuromodulation by NFB.

The effect of explicit and implicit online self-compassion interventions on sleep quality among Chinese adults: A longitudinal and diary study

Objective

This study aimed to investigate the effects of explicit and implicit online intervention methods for self-compassion on improving sleep quality among Chinese adults.

Methods

A total of 328 adult participants were recruited to complete the Pittsburgh Sleep Quality Questionnaire and Self-compassion Scale, and 168 participants were randomly assigned to one of three different conditions: two self-compassion intervention groups (self-compassion writing intervention asked participants to write several sentences with self-compassion, and self-compassion combination intervention asked participants to combine words into complete sentences with self-compassion) and one control group. After 1 week of online self-compassion intervention with daily sleep quality measured simultaneously, 150 participants completed the posttest of the Pittsburgh Sleep Quality Questionnaire and Self-Compassion Scale.

Results

The pretest and posttests results showed that the self-compassion level and sleep quality of the self-compassion writing intervention group were significantly better than those of the control group. However, there was no significant difference between the self-compassion combination intervention group and the control group. For the diary tracking results, sleep quality was significantly better for both the self-compassion writing intervention group and self-compassion combination intervention group than the control group, however, the self-compassion writing intervention group showed great improvements.

Conclusion

Both self-compassion writing and combination interventions were effective in improving sleep quality, and the effect of self-compassion writing was more stable.

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.

Performance comparison of systemic activity correction in functional near-infrared spectroscopy for methods with and without short distance channels

Significance: Functional near-infrared spectroscopy (fNIRS) is a promising tool for neurofeedback (NFB) or brain-computer interfaces (BCIs). However, fNIRS signals are typically highly contaminated by systemic activity (SA) artifacts, and, if not properly corrected, NFB or BCIs run the risk of being based on noise instead of brain activity. This risk can likely be reduced by correcting for SA, in particular when short-distance channels (SDCs) are available. Literature comparing correction methods with and without SDCs is still sparse, specifically comparisons considering single trials are lacking. Aim: This study aimed at comparing the performance of SA correction methods with and without SDCs. Approach: Semisimulated and real motor task data of healthy older adults were used. Correction methods without SDCs included a simple and a more advanced spatial filter. Correction methods with SDCs included a regression approach considering only the closest SDC and two GLM-based methods, one including all eight SDCs and one using only two a priori selected SDCs as regressors. All methods were compared with data uncorrected for SA and correction performance was assessed with quality measures quantifying signal improvement and spatial specificity at single trial level. Results: All correction methods were found to improve signal quality and enhance spatial specificity as compared with the uncorrected data. Methods with SDCs usually outperformed methods without SDCs. Correction methods without SDCs tended to overcorrect the data. However, the exact pattern of results and the degree of differences observable between correction methods varied between semisimulated and real data, and also between quality measures. Conclusions: Overall, results confirmed that both Δ [ HbO ] and Δ [ HbR ] are affected by SA and that correction methods with SDCs outperform methods without SDCs. Nonetheless, improvements in signal quality can also be achieved without SDCs and should therefore be given priority over not correcting for SA.

Frontostriatal circuitry as a target for fMRI-based neurofeedback interventions: A systematic review

Dysregulated frontostriatal circuitries are viewed as a common target for the treatment of aberrant behaviors in various psychiatric and neurological disorders. Accordingly, experimental neurofeedback paradigms have been applied to modify the frontostriatal circuitry. The human frontostriatal circuitry is topographically and functionally organized into the "limbic," the "associative," and the "motor" subsystems underlying a variety of affective, cognitive, and motor functions. We conducted a systematic review of the literature regarding functional magnetic resonance imaging-based neurofeedback studies that targeted brain activations within the frontostriatal circuitry. Seventy-nine published studies were included in our survey. We assessed the efficacy of these studies in terms of imaging findings of neurofeedback intervention as well as behavioral and clinical outcomes. Furthermore, we evaluated whether the neurofeedback targets of the studies could be assigned to the identifiable frontostriatal subsystems. The majority of studies that targeted frontostriatal circuitry functions focused on the anterior cingulate cortex, the dorsolateral prefrontal cortex, and the supplementary motor area. Only a few studies (n = 14) targeted the connectivity of the frontostriatal regions. However, post-hoc analyses of connectivity changes were reported in more cases (n = 32). Neurofeedback has been frequently used to modify brain activations within the frontostriatal circuitry. Given the regulatory mechanisms within the closed loop of the frontostriatal circuitry, the connectivity-based neurofeedback paradigms should be primarily considered for modifications of this system. The anatomical and functional organization of the frontostriatal system needs to be considered in decisions pertaining to the neurofeedback targets.

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.

Can neurofeedback provide evidence of direct brain-behavior causality?

Neurofeedback is a procedure that measures brain activity in real-time and presents it as feedback to an individual, thus allowing them to self-regulate brain activity with effects on cognitive processes inferred from behavior. One common argument is that neurofeedback studies can reveal how the measured brain activity causes a particular cognitive process. The causal claim is often made regarding the measured brain activity being manipulated as an independent variable, similar to brain stimulation studies. However, this causal inference is vulnerable to the argument that other upstream brain activities change concurrently and cause changes in the brain activity from which feedback is derived. In this paper, we outline the inference that neurofeedback may causally affect cognition by indirect means. We further argue that researchers should remain open to the idea that the trained brain activity could be part of a "causal network" that collectively affects cognition rather than being necessarily causally primary. This particular inference may provide a better translation of evidence from neurofeedback studies to the rest of neuroscience. We argue that the recent advent of multivariate pattern analysis, when combined with implicit neurofeedback, currently comprises the strongest case for causality. Our perspective is that although the burden of inferring direct causality is difficult, it may be triangulated using a collection of various methods in neuroscience. Finally, we argue that the neurofeedback methodology provides unique advantages compared to other methods for revealing changes in the brain and cognitive processes but that researchers should remain mindful of indirect causal effects.

Neurofeedback training: Decreases in Mu rhythm lead to improved motor performance in complex visuomotor skills

The physiological function of the Mu rhythm (8-13 Hz in the central region) is still unclear, particularly its role in visuomotor performance in sports (shooting vs. golf putting), as both the complexity of the motor skills (i.e., simple vs. complex visuomotor skills) and the skill level (e.g., novices vs. experts or low-skilled vs. highly skilled) may modulate Mu rhythm. To gain a broader understanding of the association between Mu rhythm and visuomotor skill performance, a study design that considers both a control moderator (the difference in skill level) and the ability to manipulate Mu rhythm (i.e., either increase or decrease Mu rhythm) is required. To achieve this, we recruited 30 novice golfers who were randomly assigned to either the increased Mu rhythm group (IMG), decreased Mu rhythm group (DMG), or sham group (SG) and used electroencephalographic-neurofeedback training (EEG-NFT) to manipulate Mu rhythm during a golf putting task (complex visuomotor skill). The aim was to determine whether the complexity of the motor skill was a potential moderator of Mu rhythm. We mainly found that Mu power was significantly decreased in the DMG following EEG-NFT, which lead to increased motor control and improved performance. We suggest that (1) the complexity of the motor skill, rather than the difference in skill level, may be a potential moderator of Mu rhythm and visuomotor performance, as our results were not consistent with a previous study that reported that increased Mu rhythm improved shooting performance (a simple visuomotor task) in novices.

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.

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.

Closed-loop neuromodulation for studying spontaneous activity and causality

Having established that spontaneous brain activity follows meaningful coactivation patterns and correlates with behavior, researchers have turned their attention to understanding its function and behavioral significance. We suggest closed-loop neuromodulation as a neural perturbation tool uniquely well suited for this task. Closed-loop neuromodulation has primarily been viewed as an interventionist tool to teach subjects to directly control their own brain activity. We examine an alternative operant conditioning model of closed-loop neuromodulation which, through implicit feedback, can manipulate spontaneous activity at the network level, without violating the spontaneous or endogenous nature of the signal, thereby providing a direct test of network causality.

An Investigation of Awareness and Metacognition in Neurofeedback with the Amygdala Electrical Fingerprint

Awareness theory posits that individuals connected to a brain-computer interface can learn to estimate and discriminate their brain states. We used the amygdala Electrical Fingerprint (amyg-EFP) - a functional Magnetic Resonance Imaging-inspired Electroencephalogram surrogate of deep brain activation - to investigate whether participants could accurately estimate their own brain activation. Ten participants completed up to 20 neurofeedback runs and estimated their amygdala-EFP activation (depicted as a thermometer) and confidence in this rating during each trial. We analysed data using multilevel models, predicting the real thermometer position with participant rated position and adjusted for activation during the previous trial. Hypotheses on learning regulation and improvement of estimation were not confirmed. However, participant ratings were significantly associated with the amyg-EFP signal. Higher rating accuracy also predicted higher subjective confidence in the rating. This proof-of-concept study introduces an approach to study awareness with fMRI-informed neurofeedback and provides initial evidence for metacognition in neurofeedback.

Closed-loop Modulation of the Self-regulating Brain: A Review on Approaches, Emerging Paradigms, and Experimental Designs

Closed-loop approaches, setups, and experimental designs have been applied within the field of neuroscience to enhance the understanding of basic neurophysiology principles (closed-loop neuroscience; CLNS) and to develop improved procedures for modulating brain circuits and networks for clinical purposes (closed-loop neuromodulation; CLNM). The contents of this review are thus arranged into the following sections. First, we describe basic research findings that have been made using CLNS. Next, we provide an overview of the application, rationale, and therapeutic aspects of CLNM for clinical purposes. Finally, we summarize methodological concerns and critics in clinical practice of neurofeedback and novel applications of closed-loop perspective and techniques to improve and optimize its experiments. Moreover, we outline the theoretical explanations and experimental ideas to test animal models of neurofeedback and discuss technical issues and challenges associated with implementing closed-loop systems. We hope this review is helpful for both basic neuroscientists and clinical/ translationally-oriented scientists interested in applying closed-loop methods to improve mental health and well-being.

Value signals guide abstraction during learning

The human brain excels at constructing and using abstractions, such as rules, or concepts. Here, in two fMRI experiments, we demonstrate a mechanism of abstraction built upon the valuation of sensory features. Human volunteers learned novel association rules based on simple visual features. Reinforcement-learning algorithms revealed that, with learning, high-value abstract representations increasingly guided participant behaviour, resulting in better choices and higher subjective confidence. We also found that the brain area computing value signals – the ventromedial prefrontal cortex – prioritised and selected latent task elements during abstraction, both locally and through its connection to the visual cortex. Such a coding scheme predicts a causal role for valuation. Hence, in a second experiment, we used multivoxel neural reinforcement to test for the causality of feature valuation in the sensory cortex, as a mechanism of abstraction. Tagging the neural representation of a task feature with rewards evoked abstraction-based decisions. Together, these findings provide a novel interpretation of value as a goal-dependent, key factor in forging abstract representations.

Effects of Transcranial Alternating Current Stimulation and Neurofeedback on Alpha (EEG) Dynamics: A Review

Transcranial alternating current stimulation (tACS) and neurofeedback (NFB) are two different types of non-invasive neuromodulation techniques, which can modulate brain activity and improve brain functioning. In this review, we compared the current state of knowledge related to the mechanisms of tACS and NFB and their effects on electroencephalogram (EEG) activity (online period/stimulation period) and on aftereffects (offline period/post/stimulation period), including the duration of their persistence and potential behavioral benefits. Since alpha bandwidth has been broadly studied in NFB and in tACS research, the studies of NFB and tACS in modulating alpha bandwidth were selected for comparing the online and offline effects of these two neuromodulation techniques. The factors responsible for variability in the responsiveness of the modulated EEG activity by tACS and NFB were analyzed and compared too. Based on the current literature related to tACS and NFB, it can be concluded that tACS and NFB differ a lot in the mechanisms responsible for their effects on an online EEG activity but they possibly share the common universal mechanisms responsible for the induction of aftereffects in the targeted stimulated EEG band, namely Hebbian and homeostatic plasticity. Many studies of both neuromodulation techniques report the aftereffects connected to the behavioral benefits. The duration of persistence of aftereffects for NFB and tACS is comparable. In relation to the factors influencing responsiveness to tACS and NFB, significantly more types of factors were analyzed in the NFB studies compared to the tACS studies. Several common factors for both tACS and NFB have been already investigated. Based on these outcomes, we propose several new research directions regarding tACS and NFB.

The DecNef collection, fMRI data from closed-loop decoded neurofeedback experiments

Decoded neurofeedback (DecNef) is a form of closed-loop functional magnetic resonance imaging (fMRI) combined with machine learning approaches, which holds some promises for clinical applications. Yet, currently only a few research groups have had the opportunity to run such experiments; furthermore, there is no existing public dataset for scientists to analyse and investigate some of the factors enabling the manipulation of brain dynamics. We release here the data from published DecNef studies, consisting of 5 separate fMRI datasets, each with multiple sessions recorded per participant. For each participant the data consists of a session that was used in the main experiment to train the machine learning decoder, and several (from 3 to 10) closed-loop fMRI neural reinforcement sessions. The large dataset, currently comprising more than 60 participants, will be useful to the fMRI community at large and to researchers trying to understand the mechanisms underlying non-invasive modulation of brain dynamics. Finally, the data collection size will increase over time as data from newly run DecNef studies will be added.

Measurement(s)	functional brain measurement
Technology Type(s)	3 T MRI scanner • functional magnetic resonance imaging • Neurofeedback • machine learning
Factor Type(s)	type of task performed: visual, preference, perceptual, or memory task
Sample Characteristic - Organism	Homo sapiens

Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.13578008