EEG-neurofeedback for optimising performance. II: Creativity, the performing arts and ecological validity

Interest of neurofeedback training for cognitive performance and risk of brain disorders in the military context

Operational environments are characterized by a range of psycho-physiological constraints that can degrade combatants' performance and impact on their long-term health. Neurofeedback training (NFT), a non-invasive, safe and effective means of regulating brain activity, has been shown to be effective for mental disorders, as well as for cognitive and motor capacities and aiding sports performance in healthy individuals. Its value in helping soldiers in operational condition or suffering from post-traumatic stress (PTSD) is undeniable, but relatively unexplored. The aim of this narrative review is to show the applicability of NFT to enhance cognitive performance and to treat (or manage) PTSD symptoms in the military context. It provides an overview of NFT use cases before, during or after military operations, and in the treatment of soldiers suffering from PTSD. The position of NFT within the broad spectrum of performance enhancement techniques, as well as several key factors influencing the effectiveness of NFT are discussed. Finally, suggestions for the use of NFT in the military context (pre-training environments, and during and post-deployments to combat zones or field operations), future research directions, recommendations and caveats (e.g., on transfer to operational situations, inter-individual variability in responsiveness) are offered. This review is thus expected to draw clear perspectives for both researchers and armed forces regarding NFT for cognitive performance enhancement and PTSD treatment related to the military context.

Toward neuroscientific understanding in posttraumatic growth: Scoping review identifying electrophysiological neurofeedback training targets for brain-based research

Improved neural understanding of posttraumatic growth (PTG) is required for effective trauma care. PTG is the advantageous psychological change some individuals derive from their struggle to overcome trauma. This comprehensive review critically examined the limited neural PTG research, to identify electrophysiological training targets for future research examining neurofeedback to enhance PTG, and provides novel insights into the emerging neural theory of PTG. PRISMA-ScR (Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews) informed the process. Findings from the studies N=8 (participants N=765) revealed PTG was correlated with left-lateralised alpha frequency power patterns. Specifically, PTG was associated with lower left frontal alpha power, higher left central alpha power, and lower parietal alpha power. Differences between studies may identify different components of PTG-related neural circuitry, or represent variations in PTG and sub-factor strength, mechanistic differences between studies, or the potential confounding presence of posttraumatic stress disorder (PTSD). While lower alpha power has been associated with higher PTSD in existing literature, higher left central alpha power was associated with lower PTSD. Therefore, alpha upregulation neurofeedback delivered over the sensorimotor cortices of the brain, around left central EEG electrode C3, presented the most promising neurofeedback target.

Controlling Virtual Reality With Brain Signals: State of the Art of Using VR-Based Feedback in Neurofeedback Applications

The rapid progress of commercial virtual reality (VR) technology, open access to VR development software as well as open-source instructions for creating brain-VR interfaces have increased the number of VR-based neurofeedback (NF) training studies. Controlling a VR environment with brain signals has potential advantages for NF applications. More entertaining, multimodal and adaptive virtual feedback modalities might positively affect subjective user experience and could consequently enhance NF training performance and outcome. Nevertheless, there are certain pitfalls and contraindications that make VR-based NF not suitable for everyone. In the present review, we summarize applications of VR-based NF and discuss positive effects of VR-based NF training as well as contraindications such as cybersickness in VR or age- and sex-related differences. The existing literature implies that VR-based feedback is a promising tool for the improvement of NF training performance. Users generally rate VR-based feedback more positively than traditional 2D feedback, albeit to draw meaningful conclusions and to rule out adverse effects of VR, more research on this topic is necessary. The pace in the development of brain-VR synchronization furthermore necessitates ethical considerations on these technologies.

Evaluating EEG neurofeedback in sport psychology: a systematic review of RCT studies for insights into mechanisms and performance improvement

Electroencephalographic Neurofeedback Training (EEG NFT) aims to improve sport performance by teaching athletes to control their mental states, leading to better cognitive, emotional, and physical outcomes. The psychomotor efficiency hypothesis suggests that optimizing brain function could enhance athletic ability, indicating the potential of EEG NFT. However, evidence for EEG-NFT's ability to alter critical brain activity patterns, such as sensorimotor rhythm and frontal midline theta-key for concentration and relaxation-is not fully established. Current research lacks standardized methods and comprehensive studies. This shortfall is due to inconsistent EEG target selection and insufficient focus on coherence in training. This review aims to provide empirical support for EEG target selection, conduct detailed control analyses, and examine the specificity of electrodes and frequencies to relation to the psychomotor efficiency hypothesis. Following the PRISMA method, 2,869 empirical studies were identified from PubMed, Science Direct, Web of Science, Embase, CNKI, and PsycINFO. Thirteen studies met the inclusion criteria: (i) proficient skill levels; (ii) use of EEG; (iii) neurofeedback training (NFT); (iv) motor performance metrics (reaction time, precision, dexterity, balance); (v) control group for NFT comparison; (vi) peer-reviewed English-language publication; and (vii) randomized controlled trial (RCT) design. Studies indicate that NFT can enhance sports performance, including improvements in shooting accuracy, golf putting, and overall motor skills, as supported by the psychomotor efficiency hypothesis. EEG NFT demonstrates potential in enhancing sports performance by optimizing performers' mental states and psychomotor efficiency. However, the current body of research is hampered by inconsistent methodologies and a lack of standardized EEG target selection. To strengthen the empirical evidence supporting EEG NFT, future studies need to focus on standardizing target selection, employing rigorous control analyses, and investigating underexplored EEG markers. These steps are vital to bolster the evidence for EEG NFT and enhance its effectiveness in boosting sport performance.

Toward Development of a Novel Proprioceptive Trail-Making Test: Comparing Healthy Dancers and Non-Dancers

There is a pressing need for ecologically valid versions of traditional neuropsychological tests indexing executive function (EF), such as the Trail-Making Task (TMT), that incorporate movement and bodily awareness in healthy participants with varying abilities. We designed a proprioceptive version of the TMT (pTMT) that involved coordinated gross motor movement and proprioceptive awareness to investigate whether this measure of visual attention, task switching, and working memory positively correlated with a computerized version of the TMT (the dTMT). We aimed to establish the initial validity of our proprioceptive TMT (pTMT) by comparing performances on the dTMT and pTMT among a cohort of 36 healthy participants (18 dancers, 18 non-dancers; M age = 22, SD = 5.27; 64% female) anticipating that dancers would express higher intrinsic bodily awareness than non-dancers. Results revealed a mild to moderate but statistically significant positive correlation between dTMT and pTMT completion times [part A: r (36) = .33, p = .04; part B: r (36) = .37, p = .03] and numbers of errors [part B: r (36) = .41, p = .01] across both participant groups. These data suggest partial measurement convergence between these two TMT versions. Relative to non-dancers, dancers exhibited a higher level of performance (likely due to their better proprioceptive ability) through their faster completion times on dTMT-B [t (34) = 3.81, p = .006, d = 1.27] and pTMT-B [t (34) = 2.97, p = .005, d = .99], and their fewer errors on dTMT-B [t (34) = 2.93, p = .006, d = 1.0]. By identifying cognitive differences between these different groups of healthy individuals, our data contribute to both a theoretical understanding and the initial development of gross motor movement-based cognitive assessments, providing a path toward the further refinement of an ecologically valid full-body TMT.

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

In recent years, the scientific community has begun tо explore the efficacy оf an integrated neurofeedback + biofeedback approach іn various conditions, both pathological and non-pathological. Although several studies have contributed valuable insights into its potential benefits, this review aims tо further investigate its effectiveness by synthesizing current findings and identifying areas for future research. Our goal іs tо provide a comprehensive overview that may highlight gaps іn the existing literature and propose directions for subsequent studies. The search for articles was conducted on the digital databases PubMed, Scopus, and Web of Science. Studies to have used the integrated neurofeedback + biofeedback approach published between 2014 and 2023 and reviews to have analyzed the efficacy of neurofeedback and biofeedback, separately, related to the same time interval and topics were selected. The search identified five studies compatible with the objectives of the review, related to several conditions: nicotine addiction, sports performance, Autism Spectrum Disorder (ASD), and Attention Deficit Hyperactivity Disorder (ADHD). The integrated neurofeedback + biofeedback approach has been shown to be effective in improving several aspects of these conditions, such as a reduction in the presence of psychiatric symptoms, anxiety, depression, and withdrawal symptoms and an increase in self-esteem in smokers; improvements in communication, imitation, social/cognitive awareness, and social behavior in ASD subjects; improvements in attention, alertness, and reaction time in sports champions; and improvements in attention and inhibitory control in ADHD subjects. Further research, characterized by greater methodological rigor, is therefore needed to determine the effectiveness of this method and the superiority, if any, of this type of training over the single administration of either. This review іs intended tо serve as a catalyst for future research, signaling promising directions for the advancement оf biofeedback and neurofeedback methodologies.

A shared novelty-seeking basis for creativity and curiosity

Curiosity and creativity are central pillars of human growth and invention. Although they have been studied extensively in isolation, the relationship between them has not yet been established. We propose that both curiosity and creativity emanate from the same mechanism of novelty seeking. We first present a synthesis showing that curiosity and creativity are affected similarly by a number of key cognitive faculties such as memory, cognitive control, attention, and reward. We then review empirical evidence from neuroscience research, indicating that the same brain regions are involved in both curiosity and creativity, focusing on the interplay between three major brain networks: the default mode network, the salience network, and the executive control network. After substantiating the link between curiosity and creativity, we propose a novelty-seeking model (NSM) that underlies them and suggests that the manifestation of the NSM is governed by one's state of mind.

Does ASMR propensity reflect a mentally flexible mindset? Exploring the relationship between ASMR propensity, transliminality, emotional contagion, schizotypal traits, roleplaying ability, and creativity

Autonomous Sensory Meridian Response (ASMR) is an alternative state of consciousness characterised by changes in affect, feelings of relaxation, and tingling sensations on the body. Online videos designed to stimulate ASMR in viewers have become increasingly popular. Although there is evidence that ASMR may improve sleep, emotion regulation, and relaxation, the current understanding of ASMR propensity remains limited. This study examined whether a mentally flexible cognitive style may underlie the ability to experience ASMR. Undergraduate students (N = 376) completed an online survey involving a series of self-report questionnaires and two performance-based creative ability tasks. Findings did not provide support for an overall mentally flexible mindset, however, transliminality, emotional contagion susceptibility, positive schizotypal traits, and roleplaying ability all significantly positively predicted ASMR propensity. These findings suggest that ASMR propensity represents several possible underlying cognitive styles relating to enhanced imagination and perceptual ability, and cannot be simply characterised by mental flexibility.

Does combined training of biofeedback and neurofeedback affect smoking status, behavior, and longitudinal brain plasticity?

Introduction: Investigations of biofeedback (BF) and neurofeedback (NF) training for nicotine addiction have been long documented to lead to positive gains in smoking status, behavior and to changes in brain activity. We aimed to: (a) evaluate a multi-visit combined BF/NF intervention as an alternative smoking cessation approach, (b) validate training-induced feedback learning, and (c) document effects on resting-state functional connectivity networks (rsFCN); considering gender and degree of nicotine dependence in a longitudinal design. Methods: We analyzed clinical, behavioral, and electrophysiological data from 17 smokers who completed five BF and 20 NF sessions and three evaluation stages. Possible neuroplastic effects were explored comparing whole-brain rsFCN by phase-lag index (PLI) for different brain rhythms. PLI connections with significant change across time were investigated according to different resting-state networks (RSNs). Results: Improvements in smoking status were observed as exhaled carbon monoxide levels, Total Oxidative Stress, and Fageström scores decreased while Vitamin E levels increased across time. BF/NF promoted gains in anxiety, self-esteem, and several aspects of cognitive performance. BF learning in temperature enhancement was observed within sessions. NF learning in theta/alpha ratio increase was achieved across baselines and within sessions. PLI network connections significantly changed across time mainly between or within visual, default mode and frontoparietal networks in theta and alpha rhythms, while beta band RSNs mostly changed significantly after BF sessions. Discussion: Combined BF/NF training positively affects the clinical and behavioral status of smokers, displays benefit in smoking harm reduction, plays a neuroprotective role, leads to learning effects and to positive reorganization of RSNs across time. Clinical Trial Registration: https://clinicaltrials.gov/ct2/show/NCT02991781.

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.

Neurofeedback and neural self-regulation: a new perspective based on allostasis

The field of neurofeedback training (NFT) has seen growing interest and an expansion of scope, resulting in a steadily increasing number of publications addressing different aspects of NFT. This development has been accompanied by a debate about the underlying mechanisms and expected outcomes. Recent developments in the understanding of psychophysiological regulation have cast doubt on the validity of control systems theory, the principal framework traditionally used to characterize NFT. The present article reviews the theoretical and empirical aspects of NFT and proposes a predictive framework based on the concept of allostasis. Specifically, we conceptualize NFT as an adaptation to changing contingencies. In an allostasis four-stage model, NFT involves (a) perceiving relations between demands and set-points, (b) learning to apply collected patterns (experience) to predict future output, (c) determining efficient set-points, and (d) adapting brain activity to the desired ("set") state. This model also identifies boundaries for what changes can be expected from a neurofeedback intervention and outlines a time frame for such changes to occur.

Hard Boundary-Based Neurofeedback Training Procedure: A Modified Fixed Thresholding Method for More Accurate Guidance of Subjects Within Target Areas During Neurofeedback Training

In nearly all studies within the domain of neurofeedback, a threshold has been defined for each training feature in a way that subjects' status can be evaluated during training according to the given value. In this study, a hard boundary-based neurofeedback training (HBNFT) method based on the determination of decision boundary using support vector machine (SVM) classifier was proposed in which subjects' status were clarified considering a decision boundary and they could also be encouraged once entering a target area. In this method, a scoring index (SI) was similarly defined whose value was determined in accordance with subject performance during training. The results revealed that employing a classifier and determining a decision boundary instead of using a threshold could prove more successful in accurately guiding them towards a target area and also meet no needs to choose a basis for determining a threshold. Moreover, it was likely that the proposed method could be more efficient in controlling features and preventing extreme changes compared to those using variable thresholds.

Theta Neurofeedback Training Supports Motor Performance and Flow Experience

Flow is defined as a cognitive state that is associated with a feeling of automatic and effortless control, enabling peak performance in highly challenging situations. In sports, flow can be enhanced by mindfulness training, which has been associated with frontal theta activity (4-8 Hz). Moreover, frontal-midline theta oscillations were shown to subserve control processes in a large variety of cognitive tasks. Based on previous theta neurofeedback training studies, which revealed that one training session is sufficient to enhance motor performance, the present study investigated whether one 30-minute session of frontal-midline theta neurofeedback training (1) enhances flow experience additionally to motor performance in a finger tapping task, and (2) transfers to cognitive control processes in an n-back task. Participants, who were able to successfully upregulate their theta activity during neurofeedback training (responders), showed better motor performance and flow experience after training than participants, who did not enhance their theta activity (non-responders). Across all participants, increase of theta activity during training was associated with motor performance enhancement from pretest to posttest irrespective of pre-training performance. Interestingly, theta training gains were also linked to the increase of flow experience, even when corresponding increases in motor performance were controlled for. Results for the n-back task were not significant. Even though these findings are mainly correlational in nature and additional flow-promoting influences need to be investigated, the present findings suggest that frontal-midline theta neurofeedback training is a promising tool to support flow experience with additional relevance for performance enhancement.

The impact of psychological theory on the treatment of Attention Deficit Hyperactivity Disorder (ADHD) in adults: A scoping review

Psychological theory and interpretation of research are key elements influencing clinical treatment development and design in Attention Deficit Hyperactivity Disorder (ADHD). Research-based treatment recommendations primarily support Cognitive Behavioural Therapy (CBT), an extension of the cognitive behavioural theory, which promotes a deficit-focused characterisation of ADHD and prioritises symptom reduction and cognitive control of self-regulation as treatment outcomes. A wide variety of approaches have developed to improve ADHD outcomes in adults, and this review aimed to map the theoretical foundations of treatment design to understand their impact. A scoping review and analysis were performed on 221 documents to compare the theoretical influences in research, treatment approach, and theoretical citations. Results showed that despite variation in the application, current treatments characterise ADHD from a single paradigm of cognitive behavioural theory. A single theoretical perspective is limiting research for effective treatments for ADHD to address ongoing issues such as accommodating context variability and heterogeneity. Research into alternative theoretical characterisations of ADHD is recommended to provide treatment design opportunities to better understand and address symptoms.

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.

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

Neurofeedback training (NFT) is a technique often proposed to train brain activity SR with promising results. However, some criticism has been raised due to the lack of evaluation, reliability, and validation of its learning effects. The current work evaluates the hypothesis that SR learning may be improved by priming the subject before NFT with guided mindfulness meditation (MM). The proposed framework was tested in a two-way parallel-group randomized controlled intervention with a single session alpha NFT, in a simplistic serious game design. Sixty-two healthy naïve subjects, aged between 18 and 43 years, were divided into MM priming and no-priming groups. Although both the EG and CG successfully attained the up-regulation of alpha rhythms (F(1,59) = 20.67, p < 0.001, ηp2 = 0.26), the EG showed a significantly enhanced ability (t(29) = 4.38, p < 0.001) to control brain activity, compared to the CG (t(29) = 1.18, p > 0.1). Furthermore, EG superior performance on NFT seems to be explained by the subject’s lack of awareness at pre-intervention, less vigour at post-intervention, increased task engagement, and a relaxed non-judgemental attitude towards the NFT tasks. This study is a preliminary validation of the proposed assisted priming framework, advancing some implicit and explicit metrics about its efficacy on NFT performance, and a promising tool for improving naïve “users” self-regulation ability.

Neurofeedback Training of the Control Network Improves Children's Performance with an SSVEP-based BCI

In the past 20 years, neural engineering has made unprecedented progress in the interpretation of brain information (e.g., brain-computer interfaces) and in neuromodulation (e.g., electromagnetic stimulation and neurofeedback). However, there has been little research aiming to improve the performance of brain-computer interfaces (BCIs) using neuromodulation. The present study presents a novel design for a neurofeedback training (NFT) method to improve the operation of a steady-state visual evoked potential (SSVEP)-based BCI and further explores its underlying mechanisms. The use of NFT to upregulate alpha-band power in the user's parietal lobe is presented in this study as a new neuromodulation method to improve SSVEP-based BCI in this study. After users completed this NFT intervention, the signal-to-noise ratio (SNR), accuracy, and information transfer rate (ITR) of the SSVEP-based BCI were increased by 5.8%, 4.7%, and 15.6%, respectively. However, no improvement was observed in the control group in which the subjects did not participate in NFT. Moreover, a general reinforcement of the information flow from the parietal lobe to the occipital lobe was observed. Evidence from a network analysis and an attention test further indicates that NFT improves attention by developing the control capacity of the parietal lobe and then enhances the above SSVEP indicators. Upregulating the amplitude of parietal alpha oscillations using NFT significantly improves the SSVEP-based BCI performance by modulating the control network. The study validates an effective neuromodulation method and possibly contributes to explaining the function of the parietal lobe in the control network.

A new neurofeedback training method based on feature space clustering to control EEG features within target clusters

BACKGROUND

Within the most commonly used neurofeedback training methods, a threshold has been defined for each EEG feature wherein subjects' status during training can be assessed according to the given value. In the present study, a neurofeedback training method based on feature-space clustering was proposed in order to assess subjects' status more accurately.

NEW METHOD

Neural gas algorithm was employed for feature space clustering. Then, the clusters were labeled as initial clusters (where the EEG features were placed prior to training) and target (where the EEG features should be shifted towards during training) ones. A scoring index was defined whose value was determined according to subjects' brain activity. This method was simulated in two versions: soft-boundary and hard-boundary based methods.

RESULTS

The results of the present simulation showed that the proposed hard-boundary based version could guide the subjects towards the boundaries of the target clusters and even their status would be stabilized in case of too many changes in subjects' EEG features. In the proposed soft-boundary based version, in case of too many changes in training features, the subjects would not be encouraged and they could be guided towards the target boundaries.

CONCLUSION

The proposed hard-boundary based version could be effective in guiding a subject towards being placed within the boundaries of target clusters and even beyond them if no specific limits exited for EEG features. As well, the soft-boundary based version could be useful when controlling EEG features within a limit.

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.

A Review of Neurofeedback Training for Improving Sport Performance From the Perspective of User Experience

Neurofeedback training (NFT) is a non-invasive, safe, and effective method of regulating the nerve state of the brain. Presently, NFT is widely used to prevent and rehabilitate brain diseases and improve an individual's external performance. Among the various NFT methods, NFT to improve sport performance (SP-NFT) has become an important research and application focus worldwide. Several studies have shown that the method is effective in improving brain function and motor control performance. However, appropriate reviews and prospective directions for this technology are lacking. This paper proposes an SP-NFT classification method based on user experience, classifies and discusses various SP-NFT research schemes reported in the existing literature, and reviews the technical principles, application scenarios, and usage characteristics of different SP-NFT schemes. Several key issues in SP-NFT development, including the factors involved in neural mechanisms, scheme selection, learning basis, and experimental implementation, are discussed. Finally, directions for the future development of SP-NFT, including SP-NFT based on other electroencephalograph characteristics, SP-NFT integrated with other technologies, and SP-NFT commercialization, are suggested. These discussions are expected to provide some valuable ideas to researchers in related fields.

Application of Latent Growth Curve modeling to predict individual trajectories during neurofeedback treatment for tinnitus

Tinnitus is a heterogeneous phenomenon indexed by various EEG oscillatory profiles. Applying neurofeedback (NFB) with the aim of changing these oscillatory patterns not only provides help for those who suffer from the phantom percept, but a promising foundation from which to probe influential factors. The reliable attribution of influential factors that potentially predict oscillatory changes during the course of NFB training may lead to the identification of subgroups of individuals that are more or less responsive to NFB training. The present study investigated oscillatory trajectories of delta (3-4Hz) and individual alpha (8.5-12Hz) during 15 NFB training sessions, based on a Latent Growth Curve framework. First, we found the desired enhancement of alpha, while delta was stable throughout the NFB training. Individual differences in tinnitus-specific variables and general-, as well as health-related quality of life predictors were largely unrelated to oscillatory change prior to and across the training. Only the predictors age and sex at baseline were clearly related to slow-wave delta, particularly so for older female individuals who showed higher delta power values from the start. Second, we confirmed a hierarchical cross-frequency association between the two frequency bands; however, in opposing directions to those anticipated in tinnitus. The establishment of individually tailored NFB protocols would boost this therapy's effectiveness in the treatment of tinnitus. In our analysis, we propose a conceptual groundwork toward this goal of developing more targeted treatment.

Real-Time Decoding of Attentional States Using Closed-Loop EEG Neurofeedback

Sustained attention is a cognitive ability to maintain task focus over extended periods of time (Mackworth, 1948; Chun, Golomb, & Turk-Browne, 2011). In this study, scalp electroencephalography (EEG) signals were processed in real time using a 32 dry-electrode system during a sustained visual attention task. An attention training paradigm was implemented, as designed in DeBettencourt, Cohen, Lee, Norman, and Turk-Browne (2015) in which the composition of a sequence of blended images is updated based on the participant's decoded attentional level to a primed image category. It was hypothesized that a single neurofeedback training session would improve sustained attention abilities. Twenty-two participants were trained on a single neurofeedback session with behavioral pretraining and posttraining sessions within three consecutive days. Half of the participants functioned as controls in a double-blinded design and received sham neurofeedback. During the neurofeedback session, attentional states to primed categories were decoded in real time and used to provide a continuous feedback signal customized to each participant in a closed-loop approach. We report a mean classifier decoding error rate of 34.3% (chance = 50%). Within the neurofeedback group, there was a greater level of task-relevant attentional information decoded in the participant's brain before making a correct behavioral response than before an incorrect response. This effect was not visible in the control group (interaction p=7.23e-4), which strongly indicates that we were able to achieve a meaningful measure of subjective attentional state in real time and control participants' behavior during the neurofeedback session. We do not provide conclusive evidence whether the single neurofeedback session per se provided lasting effects in sustained attention abilities. We developed a portable EEG neurofeedback system capable of decoding attentional states and predicting behavioral choices in the attention task at hand. The neurofeedback code framework is Python based and open source, and it allows users to actively engage in the development of neurofeedback tools for scientific and translational use.

Advances in biofeedback and neurofeedback studies on smoking

Smoking is a leading cause of morbidity and premature death constituting a global health challenge. Although, pharmacological and behavioral approaches comprise the mainstay of smoking cessation interventions, the efficacy and safety of pharmacotherapy is not demonstrated for some populations. Non-pharmacological approaches, such as biofeedback (BF) and neurofeedback (NF) could facilitate self-regulation of predisposing factors of relapse such as craving and stress. The current review aims to aggregate the existing evidence regarding the effects of BF and NF training on smokers. Relevant studies were identified through searching in Scopus, PubMed and Cochrane Library, and through hand-searching the references of screened articles. Peer-reviewed controlled and uncontrolled studies, where BF and/or NF training was administered, were included and evaluated according to PICOS framework. Narrative qualitative synthesis of ten eligible studies was performed, aggregated into three categories according to training provided. BF outcomes seem to be affected by smoking behavior prior to training; individualized EEG NF training holds promise for modulating craving-related response while minimizing the required number of sessions. Real-time fMRI NF studies concluded that nicotine-dependent individuals could modulate craving-related brain responses, while mixed results were revealed regarding smokers' ability to modulate brain responses related to resistance towards the urge to smoke. BF and NF training seem to facilitate modulation of autonomous and/or central nervous system activity while also transferring this learned self-regulation to behavioral outcomes. BF and NF training should a) address remaining issues on specificity and scientific validity, b) target diverse demographics, and c) produce robust reproducible methodologies and clinical guidelines for relevant health care providers, in order to be considered as viable complementary tools to standard smoking cessation care.

Effect of Simulation-Based Training and Neurofeedback Interventions on Radiation Technologists' Workload, Situation Awareness, and Performance

PURPOSE

Our purpose was to assess the effect of a combined intervention - simulation-based training supported by neurofeedback sessions - on radiation technologists' (RTs') workload, situation awareness, and performance during routine quality assurance and treatment delivery tasks.

METHODS AND MATERIALS

As part of a prospective institutional review board approved study, 32 RTs previously randomized to receive versus not receive simulation-based training focused on patient safety were again randomized to receive versus not receive a 3-week neurofeedback intervention (8 sessions of alpha-theta protocol) focused on stress reduction as well as conscious precision, strong focus, and ability to solve arising problems. Perceived workload was quantified using the NASA Task Load Index. Situation awareness was quantified using the situation awareness rating technique. Performance score was calculated using procedural compliance with time-out components and error detection.

RESULTS

RTs randomized to simulation-based training followed by neurofeedback sessions demonstrated no significant changes in perceived workload or situation awareness scores, but did have better performance compared with other study groups (P < .01).

CONCLUSIONS

This finding is encouraging and provides basis for using neurofeedback as means to possibly augment performance improvements gained during simulation-based training.

Modulation of frontal gamma oscillations improves working memory in schizophrenia

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Cognitive deficits, a core symptom of schizophrenia, are difficult to treat with available therapies.

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Abnormal neural dynamics of frontal gamma oscillations contribute to these deficits.

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Neurofeedback has been used previously to alter brain oscillations.

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Gamma band neurofeedback can impact brain and behavioral markers of cognition.

Schizophrenia is a debilitating mental disorder that is associated with cognitive deficits. Impairments in cognition occur early in the course of illness and are associated with poor functional outcome, but have been difficult to treat with conventional treatments. Recent studies have implicated abnormal neural network dynamics and impaired connectivity in frontal brain regions as possible causes of cognitive deficits. For example, high-frequency, dorsal-lateral prefrontal oscillatory activity in the gamma range (30–50 Hz) is associated with impaired working memory in individuals with schizophrenia. In light of these findings, it may be possible to use EEG neurofeedback (EEG-NFB) to train individuals with schizophrenia to enhance frontal gamma activity to improve working memory and cognition. In a single-group, proof-of-concept study, 31 individuals with schizophrenia received 12 weeks of twice weekly EEG-NFB to enhance frontal gamma band response. EEG-NFB was well-tolerated, associated with increased gamma training threshold, and significant increases in frontal gamma power during an n-back working memory task. Additionally, EEG-NFB was associated with significant improvements in n-back performance and working memory, speed of processing, and reasoning and problem solving on neuropsychological tests. Change in gamma power was associated with change in cognition. Significant improvements in psychiatric symptoms were also found. These encouraging findings suggest EEG-NFB targeting frontal gamma activity may provide a novel effective approach to cognitive remediation in schizophrenia, although placebo-controlled trials are needed to assess the effects of non-treatment related factors.

The Analysis of Electroencephalography Changes Before and After a Single Neurofeedback Alpha/Theta Training Session in University Students

The underlying mechanisms of alpha/theta neurofeedback training have not been fully determined. Therefore, this study aimed to test the changes in the brain state feedback during the alpha/theta training. Twenty-seven healthy participants were trained during a single session of the alpha/theta protocol, and the resting quantitative electroencephalography (QEEG) was assessed before and after training. QEEG was recorded at eight scalp locations (F3, F4, C3, C4, T3, T4, O1, and O2), and the absolute power, relative power, ratio of sensory-motor rhythm beta (SMR) to theta (RST), ratio of SMR-mid beta to theta (RSMT), ratio of mid beta to theta (RMT), ratio of alpha to high beta (RAHB), and scaling exponent of detrended fluctuation analysis by each band were measured. The results indicated a significant increase of absolute alpha power, especially the slow alpha band, at all electrodes except T3 and T4. Moreover, the relative alpha power, especially the slow alpha band, showed a significant increase at all electrodes. The relative theta power showed a significant decrease at all electrodes, except T3. A significant decrease in relative beta power, relative lower beta power and relative mid beta power was observed at O1. RST (at C4, O1, and O2), RSMT and RMT (at F4, C4, O1 and O2), and RAHB (at all electrodes) showed significant increase. Scaling exponents at all electrodes except T3 showed a significant decrease. These findings indicate that a one-time session of alpha/theta training might have the possibility to enhance both vigilance and concentration, thus stabilizing the overall brain function.

Soft boundary-based neurofeedback training based on fuzzy similarity measures: A method for learning how to control EEG Signal features during neurofeedback training

BACKGROUND

Most commonly used neurofeedback training (NFT) methods are able to assist subjects towards an increase/decrease in EEG features. So, it is possible that the enhancement/inhabitation in a subject's EEG features exceed normal limits if the process of changes in brain activity in the subject is very successful. This issue may also bring about a reduction in the effectiveness of NFT.

NEW METHOD

A soft boundary-based NFT method was proposed for learning how to control the EEG features during training. According to this method, an initial group was defined within which the training features of subjects' EEG signals were placed prior to training and a target group was considered referring to what the features of the EEG signals should be shifted towards during training. In the course of training, the fuzzy similarity of EEG features of subject towards the target group center was measured and the subject's score was increased if their fuzzy similarity was higher than a threshold. Within this method, an adaptive scoring index (the scores assigned to subjects for each achievement) was defined whose value was determined according to brain activity of the subject.

RESULTS

Increase/decrease in large amounts in the training features of subject's EEG could lead to a descending trend in the scores received using the proposed method.

COMPARISON WITH EXISTING METHODS

The proposed method may assist subjects to control their EEG signal features within the target group range.

CONCLUSION

The proposed method may be able to prevent the side effects of neurofeedback.

Predictors of neurofeedback training outcome: A systematic review

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Best available evidence exists for neurophysiological baseline parameters.

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No substantial effect of age and intelligence on training outcome in most cases.

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Neurofeedback learning success predicts treatment outcome.

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To date, a reliable selection of participants based on predictors is not possible.

Neurofeedback (NF), a training tool aimed at enhancing neural self-regulation, has been suggested as a complementary treatment option for neuropsychiatric disorders. Despite its potential as a neurobiological intervention directly targeting neural alterations underlying clinical symptoms, the efficacy of NF for the treatment of mental disorders has been questioned recently by negative findings obtained in randomized controlled trials (e.g., Cortese et al., 2016). A possible reason for insufficient group effects of NF trainings vs. placebo could be related to the high rate of participants who fail to self-regulate brain activity by NF (“non-learners”). Another reason could be the application of standardized NF protocols not adjusted to individual differences in pathophysiology. Against this background, we have summarized information on factors determining training and treatment success to provide a basis for the development of individualized training protocols and/or clinical indications.

The present systematic review included 25 reports investigating predictors for the outcome of NF trainings in healthy individuals as well as patients affected by mental disorders or epilepsy. We selected these studies based on searches in EBSCOhost using combinations of the keywords “neurofeedback” and “predictor/predictors”. As “NF training” we defined all NF applications with at least two sessions.

The best available evidence exists for neurophysiological baseline parameters. Among them, the target parameters of the respective training seem to be of particular importance. However, particularities of the different experimental designs and outcome criteria restrict the interpretability of some of the information we extracted. Therefore, further research is needed to gain more profound knowledge about predictors of NF outcome.

Neuroenhancement for sale: assessing the website claims of neurofeedback providers in the United States

Although electroencephalographic (EEG) neurofeedback is a technique that has been in existence for many decades, it has remained controversial, largely due to questions about efficacy. Yet neurofeedback is being widely offered to the public, often at great expense. To date, however, there has not been empirical data on which providers are utilizing neurofeedback, what they are offering it for, and how they are advertising the technique. The present study aimed to fill that gap by systematically analyzing the websites of neurofeedback practitioners in the United States. To that end, we obtained data from four directories of neurofeedback providers, extracting practitioner names, geographical locations, professional training, and website URLs. Only websites offering neurofeedback services (N=371) were included in the next step, wherein two coders independently coded the websites based on a codebook developed from preliminary analyses. We found that nearly all websites (97.0%) contained claims about at least one clinical indication, most commonly anxiety, ADHD/ADD, and depression; however, only 36.0% of providers had either a medical degree (MD) or a doctoral-level degree in psychology. The majority of websites advertised neurofeedback for cognitive (90.0%) or performance (67.9%) enhancement, and roughly three-quarters utilized language related to complementary and alternative medicine (CAM). In sum, there is a considerable divergence between the scientific literature on neurofeedback and the marketing of neurofeedback services to the general public, raising concerns regarding the misrepresentation of services and misleading advertising claims.

Effects of Motor Imagery and Visual Neurofeedback on Activation in the Swallowing Network: A Real-Time fMRI Study

Motor imagery of movements is used as mental strategy in neurofeedback applications to gain voluntary control over activity in motor areas of the brain. In the present functional magnetic resonance imaging (fMRI) study, we first addressed the question whether motor imagery and execution of swallowing activate comparable brain areas, which has been already proven for hand and foot movements. Prior near-infrared spectroscopy (NIRS) studies provide evidence that this is the case in the outer layer of the cortex. With the present fMRI study, we want to expand these prior NIRS findings to the whole brain. Second, we used motor imagery of swallowing as mental strategy during visual neurofeedback to investigate whether one can learn to modulate voluntarily activity in brain regions, which are associated with active swallowing, using real-time fMRI. Eleven healthy adults performed one offline session, in which they executed swallowing movements and imagined swallowing on command during fMRI scanning. Based on this functional localizer task, we identified brain areas active during both tasks and defined individually regions for feedback. During the second session, participants performed two real-time fMRI neurofeedback runs (each run comprised 10 motor imagery trials), in which they should increase voluntarily the activity in the left precentral gyrus by means of motor imagery of swallowing while receiving visual feedback (the visual feedback depicted one's own fMRI signal changes in real-time). Motor execution and imagery of swallowing activated a comparable network of brain areas including the bilateral pre- and postcentral gyrus, inferior frontal gyrus, basal ganglia, insula, SMA, and the cerebellum compared to a resting condition. During neurofeedback training, participants were able to increase the activity in the feedback region (left lateral precentral gyrus) but also in other brain regions, which are generally active during swallowing, compared to the motor imagery offline task. Our results indicate that motor imagery of swallowing is an adequate mental strategy to activate the swallowing network of the whole brain, which might be useful for future treatments of swallowing disorders.

Human enhancement through the lens of experimental and speculative neurotechnologies

Human enhancement deals with improving on and overcoming limitations of the human body and mind. Pharmaceutical compounds that alter consciousness and cognitive performance have been used and discussed for a long time. The prospect of neurotechnological applications such as brain-steered devices or using invasive and noninvasive electromagnetic stimulations of the human brain, however, has received less attention-especially outside of therapeutic practices-and remains relatively unexplored. Reflection and debates about neurotechnology for human enhancement are limited and remain predominantly with neurotech engineers, science-fiction enthusiasts and a small circle of academics in the field of neuroethics. It is well known, and described as the Collingridge dilemma, that at an early stage of development, changes can easily be enacted, but the need for changes can hardly be foreseen. Once the technology is entrenched, opportunities and risks start to materialize, and the need to adapt and change is clearly visible. However, carrying out these changes at such a late stage, in turn, becomes very difficult, tremendously expensive, and sometimes practically impossible. In this manuscript, we compile and categorize an overview of existing experimental and speculative applications of neurotechnologies, with the aim to find out, if these real or diegetic prototypes could be used to better understand the paths these applications are forging. In particular, we will investigate what kind of tools, motivations, and normative goals underpin experimental implementations by neurohackers, speculative designers and artists.

Neurofeedback training with a low-priced EEG device leads to faster alpha enhancement but shows no effect on cognitive performance: A single-blind, sham-feedback study

INTRODUCTION

Findings of recent studies indicate that it is possible to enhance cognitive capacities of healthy individuals by means of individual upper alpha neurofeedback training (NFT). Although these results are promising, most of this research was conducted based on high-priced EEG systems developed for clinical and research purposes. This study addresses the question whether such effects can also be shown with an easy to use and comparably low-priced Emotiv Epoc EEG headset available for the average consumer. In addition, critical voices were raised regarding the control group designs of studies addressing the link between neurofeedback training and cognitive performance. Based on an extensive literature review revealing considerable methodological issues in an important part of the existing research, the present study addressed the question whether individual upper alpha neurofeedback has a positive effect on alpha amplitudes (i.e. increases alpha amplitudes) and short-term memory performance focussing on a methodologically sound, single-blinded, sham controlled design.

METHOD

Participants (N = 33) took part in four test sessions over four consecutive days of either neurofeedback training (NFT group) or sham feedback (SF group). In the NFT group, five three-minute periods of visual neurofeedback training were administered each day whereas in the SF group (control group), the same amount of sham feedback was presented. Performance on eight digit-span tests as well as participants' affective states were assessed before and after each of the daily training sessions.

RESULTS

NFT did not show an effect on individual upper alpha and cognitive performance. While performance increased in both groups over the course of time, this effect could not be explained by changes in individual upper alpha. Additional analyses however revealed that participants in the NFT group showed faster and larger increase in alpha compared to the SF group. Surprisingly, exploratory analyses showed a significant correlation between the initial alpha level and the alpha improvement during the course of the study. This finding suggests that participants with high initial alpha levels benefit more from alpha NFT interventions. In the discussion, the appearance of the alpha enhancement in the SF group and possible reasons for the absence of a connection between NFT and short-term memory are addressed.

Review of the therapeutic neurofeedback method using electroencephalography: EEG Neurofeedback

Electroencephalographic neurofeedback (EEG-NFB) represents a broadly used method that involves a real-time EEG signal measurement, immediate data processing with the extraction of the parameter(s) of interest, and feedback to the individual in a real-time. Using such a feedback loop, the individual may gain better control over the neurophysiological parameters, by inducing changes in brain functioning and, consequently, behavior. It is used as a complementary treatment for a variety of neuropsychological disorders and improvement of cognitive capabilities, creativity or relaxation in healthy subjects. In this review, various types of EEG-NFB training are described, including training of slow cortical potentials (SCPs) and frequency and coherence training, with their main results and potential limitations. Furthermore, some general concerns about EEG-NFB methodology are presented, which still need to be addressed by the NFB community. Due to the heterogeneity of research designs in EEG-NFB protocols, clear conclusions on the effectiveness of this method are difficult to draw. Despite that, there seems to be a well-defined path for the EEG-NFB research in the future, opening up possibilities for improvement.

Neuromodulating Attention and Mind-Wandering Processes with a Single Session Real Time EEG

Our minds are continuously alternating between external attention (EA) and mind wandering (MW). An appropriate balance between EA and MW is important for promoting efficient perceptual processing, executive functioning, decision-making, auto-biographical memory, and creativity. There is evidence that EA processes are associated with increased activity in high-frequency EEG bands (e.g., SMR), contrasting with the dominance of low-frequency bands during MW (e.g., Theta). The aim of the present study was to test the effects of two distinct single session real-time EEG (rtEEG) protocols (SMR up-training/Theta down-training-SMR⇑Theta⇓; Theta up-training/SMR down-training-Theta⇑SMR⇓) on EA and MW processes. Thirty healthy volunteers were randomly assigned to one of two rtEEG training protocols (SMR⇑Theta⇓; Theta⇑SMR⇓). Before and after the rtEEG training, participants completed the attention network task (ANT) along with several MW measures. Both training protocols were effective in increasing SMR (SMR⇑Theta⇓) and theta (Theta⇑SMR⇓) amplitudes but not in decreasing the amplitude of down-trained bands. There were no significant effects of the rtEEG training in either EA or MW measures. However, there was a significant positive correlation between post-training SMR increases and the use of deliberate MW (rather than spontaneous) strategies. Additionally, for the Theta⇑SMR⇓ protocol, increase in post-training Theta amplitude was significantly associated with a decreased efficiency in the orientation network.

The effects of psychiatric history and age on self-regulation of the default mode network

Real-time neurofeedback enables human subjects to learn to regulate their brain activity, effecting behavioral changes and improvements of psychiatric symptomatology. Neurofeedback up-regulation and down-regulation have been assumed to share common neural correlates. Neuropsychiatric pathology and aging incur suboptimal functioning of the default mode network. Despite the exponential increase in real-time neuroimaging studies, the effects of aging, pathology and the direction of regulation on neurofeedback performance remain largely unknown. Using real-time fMRI data shared through the Rockland Sample Real-Time Neurofeedback project (N = 136) and open-access analyses, we first modeled neurofeedback performance and learning in a group of subjects with psychiatric history (n_a = 74) and a healthy control group (n_b = 62). Subsequently, we examined the relationship between up-regulation and down-regulation learning, the relationship between age and neurofeedback performance in each group and differences in neurofeedback performance between the two groups. For interpretative purposes, we also investigated functional connectomics prior to neurofeedback. Results show that in an initial session of default mode network neurofeedback with real-time fMRI, up-regulation and down-regulation learning scores are negatively correlated. This finding is related to resting state differences in the eigenvector centrality of the posterior cingulate cortex. Moreover, age correlates negatively with default mode network neurofeedback performance, only in absence of psychiatric history. Finally, adults with psychiatric history outperform healthy controls in default mode network up-regulation. Interestingly, the performance difference is related to no up-regulation learning in controls. This finding is supported by marginally higher default mode network centrality during resting state, in the presence of psychiatric history.

Design and Implementation of a Novel Subject-Specific Neurofeedback Evaluation and Treatment System

Electroencephalography (EEG)-based neurofeedback (NF) is a safe, non-invasive, non-painful method for treating various conditions. Current NF systems enable the selection of only one NF parameter, so that two parameters cannot be feedback simultaneously. Consequently, the ability to individually-tailor the treatment to a patient is limited, and treatment efficiency may therefore be compromised. We aimed to design, implement and test an all-in-one, novel, computerized platform for closed-loop NF treatment, based on principles from learning theories. Our prototype performs numeric evaluation based on quantifying resting EEG and event-related EEG responses to various sensory stimuli. The NF treatment was designed according to principles of efficient learning, and implemented as a gradual, patient-adaptive 1D or 2D computer game, that utilizes automatic EEG feature extraction. Verification was performed as we compared the mean area under curve (AUC) of the theta band of a dozen subjects staring at a wall or performing the NF. Most of the subjects (75%) increased their theta band AUC during the NF session compared with the trial staring at the wall (p = 0.041). Our system enables multiple feature selection and its machine learning capabilities allow an accurate discovery of patient-specific biomarkers and treatment targets. Its novel characteristics may allow for improved evaluation of patients and treatment outcomes.

Feedback-Based Treatments for Eating Disorders and Related Symptoms: A Systematic Review of the Literature

The effectiveness of biofeedback and neurofeedback has been investigated in a range of psychiatric disorders. However, to date, there are few studies on the clinical usefulness of feedback-based techniques for eating disorders (EDs) and EDs-related symptoms (e.g., food craving). A systematic search of PubMed, Scopus and PsychINFO identified 162 articles. Among these, thirteen studies exploring the therapeutic use of biofeedback and neurofeedback in EDs or EDs-related symptoms were included. Biofeedback and neurofeedback were implemented respectively in five and eight of all reviewed articles. No studies incorporated different feedback modalities or both biofeedback and neurofeedback. The considered studies provide preliminary data of the usefulness of feedback-based techniques in the treatment of several dysfunctional eating behaviors (e.g., food craving, rumination). Although no significant effect has been reported for other important EDs-related symptoms (i.e., body image disturbance), feedback-based techniques are also associated with significant modifications of both sympathetic reaction to food-related stimuli and brain activity in several regions of the reward system (e.g., insula). Taken together the results of the present review suggest that feedback-based treatments may be useful in the treatment of several dysfunctional eating behaviors operating both on top-down and bottom-up individual coping strategies. Methodological and clinical issues are also discussed.

Eyes-Closed Resting EEG Predicts the Learning of Alpha Down-Regulation in Neurofeedback Training

Neurofeedback training, which enables the trainee to learn self-control of the EEG activity of interest based on online feedback, has demonstrated benefits on cognitive and behavioral performance. Nevertheless, as a core mechanism of neurofeedback, learning of EEG regulation (i.e., EEG learning) has not been well understood. Moreover, a substantial number of non-learners who fail to achieve successful EEG learning have often been reported. This study investigated the EEG learning in alpha down-regulation neurofeedback, aiming to better understand the alpha learning and to early predict learner/non-learner. Twenty-nine participants received neurofeedback training to down-regulate alpha in two days, while eight of them were identified as non-learners who failed to reduce their alpha within sessions. Through a stepwise linear discriminant analysis, a prediction model was built based on participant's eyes-closed resting EEG activities in broad frequency bands including lower alpha, theta, sigma and beta 1 measured before training, which was validated in predicting learners/non-learners. The findings would assist in the early identification of the individuals who would not likely reduce their alpha during neurofeedback.

Affective science and avoidant end-of-life communication: Can the science of emotion help physicians talk with their patients about the end of life?

Despite believing end-of-life (EOL) discussions with patients are important, doctors often do not have them. Multiple factors contribute to this shortfall, which interventions including reimbursement changes and communication skills training have not significantly improved to date. One commonly cited but under-researched reason for physician avoidance of EOL discussion is emotional difficulty. High occupational demand for frequent difficult discussions may overload physicians' normal emotional functioning, leading to avoidance or failure. We propose that cognitive, behavioral, and neuroscience evidence from affective science may offer helpful insights into this problem. Data from other populations show that strong emotion impairs cognitive performance and multiple demands can overload cognitive resources. We discuss several affective processes that may apply to physicians attempting EOL discussions. We then discuss selected interventions that have been shown to modify some of these processes and associated behavioral outcomes. Evidence for change in behavioral outcomes of interest includes performance and mood enhancement in healthy populations. We suggest that such mechanistically-targeted interventions may be hypothesized to help decrease physician avoidance of EOL discussion. Physicians may be motivated to adopt such interventions in order to enhance normal emotional functioning to meet supra-normal occupational demand. We propose this as a promising area of future study.