Neurofeedback training can modulate task-relevant memory replay rate in rats.

Hippocampal replay - the time-compressed, sequential reactivation of ensembles of neurons related to past experience - is a key neural mechanism of memory consolidation. Replay typically coincides with a characteristic pattern of local field potential activity, the sharp-wave ripple (SWR). Reduced SWR rates are associated with cognitive impairment in multiple models of neurodegenerative disease, suggesting that a clinically viable intervention to promote SWRs and replay would prove beneficial. We therefore developed a neurofeedback paradigm for rat subjects in which SWR detection triggered rapid positive feedback in the context of a memory-dependent task. This training protocol increased the prevalence of task-relevant replay during the targeted neurofeedback period by changing the temporal dynamics of SWR occurrence. This increase was also associated with neural and behavioral forms of compensation after the targeted period. These findings reveal short-timescale regulation of SWR generation and demonstrate that neurofeedback is an effective strategy for modulating hippocampal replay.

Targeting the superior temporal gyrus with real-time fMRI neurofeedback: A pilot study of the indirect effects on self-referential processes in schizophrenia.

BACKGROUND: Individuals with schizophrenia (SZ) and auditory hallucinations (AHs) display a distorted sense of self and self-other boundaries. Alterations of activity in midline cortical structures such as the prefrontal cortex (mPFC) and anterior cingulate cortex (ACC) during self-reference as well as in the superior temporal gyrus (STG) have been proposed as neuromarkers of SZ and AHs. METHODS: In this randomized, participant-blinded, sham-controlled trial, 22 adults (18 males) with SZ spectrum disorders (SZ or schizoaffective disorder) and frequent medication-resistant AHs received one session of real-time fMRI neurofeedback (NFB) either from the STG (n = 11; experimental group) or motor cortex (n = 11; control group). During NFB, participants were instructed to upregulate their STG activity by attending to pre-recorded sentences spoken in their own voice and downregulate it by ignoring unfamiliar voices. Before and after NFB, participants completed a self-reference task where they evaluated if trait adjectives referred to themselves (self condition), Abraham Lincoln (other condition), or whether adjectives had a positive valence (semantic condition). FMRI activation analyses of self-reference task data tested between-group changes after NFB (self>semantic, post>pre-NFB, experimental>control). Analyses were pre-masked within a self-reference network. RESULTS: Activation analyses revealed significantly (p < 0.001) greater activation increase in the experimental, compared to the control group, after NFB within anterior regions of the self-reference network (mPFC, ACC, superior frontal cortex). CONCLUSIONS: STG-NFB was associated with activity increase in the mPFC, ACC, and superior frontal cortex during self-reference. Modulating the STG is associated with activation changes in other, not-directly targeted, regions subserving higher-level cognitive processes associated with self-referential processes and AHs psychopathology in SZ. CLINICALTRIALS: GOV: Rt-fMRI Neurofeedback and AH in Schizophrenia; https://clinicaltrials.gov/study/NCT03504579.

Effects of home-based EEG neurofeedback training as a non-pharmacological intervention for Parkinson's disease.

OBJECTIVES: Aberrant movement-related cortical activity has been linked to impaired motor function in Parkinson's disease (PD). Dopaminergic drug treatment can restore these, but dosages and long-term treatment are limited by adverse side-effects. Effective non-pharmacological treatments could help reduce reliance on drugs. This experiment reports the first study of home-based electroencephalographic (EEG) neurofeedback training as a non-pharmacological candidate treatment for PD. Our primary aim was to test the feasibility of our EEG neurofeedback intervention in a home setting. METHODS: Sixteen people with PD received six home visits comprising symptomology self-reports, a standardised motor assessment, and a precision handgrip force production task while EEG was recorded (visits 1, 2 and 6); and 3 × 1-hr EEG neurofeedback training sessions to supress the EEG mu rhythm before initiating handgrip movements (visits 3 to 5). RESULTS: Participants successfully learned to self-regulate mu activity, and this appeared to expedite the initiation of precision movements (i.e., time to reach target handgrip force off-medication pre-intervention = 628 ms, off-medication post-intervention = 564 ms). There was no evidence of wider symptomology reduction (e.g., Movement Disorder Society Unified Parkinson's Disease Rating Scale Part III Motor Examination, off-medication pre-intervention = 29.00, off-medication post intervention = 30.07). Interviews indicated that the intervention was well-received. CONCLUSION: Based on the significant effect of neurofeedback on movement-related cortical activity, positive qualitative reports from participants, and a suggestive benefit to movement initiation, we conclude that home-based neurofeedback for people with PD is a feasible and promising non-pharmacological treatment that warrants further research.

AttentionCARE: replicability of a BCI for the clinical application of augmented reality-guided EEG-based attention modification for adolescents at high risk for depression.

Affect-biased attention is the phenomenon of prioritizing attention to emotionally salient stimuli and away from goal-directed stimuli. It is thought that affect-biased attention to emotional stimuli is a driving factor in the development of depression. This effect has been well-studied in adults, but research shows that this is also true during adolescence, when the severity of depressive symptoms are correlated with the magnitude of affect-biased attention to negative emotional stimuli. Prior studies have shown that trainings to modify affect-biased attention may ameliorate depression in adults, but this research has also been stymied by concerns about reliability and replicability. This study describes a clinical application of augmented reality-guided EEG-based attention modification ("AttentionCARE") for adolescents who are at highest risk for future depressive disorders (i.e., daughters of depressed mothers). Our results (n = 10) indicated that the AttentionCARE protocol can reliably and accurately provide neurofeedback about adolescent attention to negative emotional distractors that detract from attention to a primary task. Through several within and cross-study replications, our work addresses concerns about the lack of reliability and reproducibility in brain-computer interface applications, offering insights for future interventions to modify affect-biased attention in high-risk adolescents.

EEG subject-dependent neurofeedback training selectively impairs declarative memories consolidation process.

The process of stabilization and storage of memories, known as consolidation, can be modulated by different interventions. Research has shown that self-regulation of brain activity through Neurofeedback (NFB) during the consolidation phase significantly impacts memory stabilization. While some studies have successfully modulated the consolidation phase using traditional EEG-based Neurofeedback (NFB) that focuses on general parameters, such as training a specific frequency band at particular electrodes, they often overlook the unique and complex neurodynamics that underlie each memory content in different individuals, potentially limiting the selective modulation of memories. The main objective of this study is to investigate the effects of a Subject-Dependent NFB (SD-NFB), based on individual models created from the brain activity of each participant, on long-term declarative memories. Participants underwent an experimental protocol involving three sessions. In the first session, they learned images of faces and houses while their brain activity was recorded. This EEG data was used to create individualized models to identify brain patterns related to learning these images. Participants were then divided into three groups, with one group receiving SD-NFB to enhance brain activity linked to faces, another to houses, and a CONTROL SHAM group that did not receive SD-NFB. Memory performance was evaluated 24 h and seven days later using an 'old-new' recognition task, where participants distinguished between 'old' and 'new' images. The results showed that memory contents (faces or houses) whose brain patterns were trained via SD-NFB scored lower in recognition compared to untrained contents, as evidenced 24 h and seven days post-training. In summary, this study demonstrates that SD-NFB can selectively impact the consolidation of specific declarative memories. This technique could hold significant implications for clinical applications, potentially aiding in the modulation of declarative memory strength in neuropsychiatric disorders where memories are pathologically exacerbated.

Is virtual reality-based cognitive training in parallel with functional near-infrared spectroscopy-derived neurofeedback beneficial to improve cognitive function in older adults with mild cognitive impairment?

PURPOSE: Cognitive training in parallel with functional near-infrared spectroscopy (fNIRS)-derived neurofeedback has been identified to be beneficial in enhancing cognitive function in patients with mild cognitive impairment (MCI). However, effects of virtual reality (VR)-based cognitive training ensuring ecological validity in parallel with fNIRS-derived neurofeedback on neural efficiency has received little attention. This study investigated effects of VR-based cognitive training in parallel with fNIRS-derived neurofeedback on cognitive function and neural efficiency in patients with MCI. METHOD: Ninety participants were randomly assigned into the active group (AG) receiving VR-based cognitive training in parallel with fNIRS-derived neurofeedback, the sham group (SG), or wait-list group (CG). The AG and SG group performed each intervention for fifteen minutes a session, for eight sessions. The Trail Making Test Part B and Backward Digit Span Test were used for outcomes. In addition, activity in the dorsolateral prefrontal cortex (DLPFC) during cognitive testing using fNIRS was measured. RESULTS: After the eight sessions, the AG achieved greater improvements in all outcomes than the other groups. In addition, the AG showed a lower DLPFC activity during cognitive testing than the other groups. CONCLUSIONS: VR-based cognitive training in parallel with fNIRS-derived neurofeedback is superior to enhancing cognitive function and neural efficiency.

Virtual reality-based cognitive training in parallel with functional near-infrared spectroscopy-derived neurofeedback might improve cognitive function and neural efficiency in patients with mild cognitive impairmentFunctional near-infrared spectroscopy-derived neurofeedback would be considered as an effective tool for understanding neural efficiency underlying improved cognitive function.Rehabilitation professionals need to integrate virtual reality-based cognitive training and functional near-infrared spectroscopy-derived neurofeedback into their practice to enhance cognitive rehabilitation outcomes for patients with mild cognitive impairment.

A single session of sensorimotor rhythm neurofeedback enhances long-game performance in professional golfers.

Enhanced Sensorimotor Rhythm activity has been linked to increased automation in motor execution. Although existing research demonstrates the positive effects of SMR neurofeedback training on improving golf putting performance, its influence on golf long-game performance remains unexplored. This study sought to address this gap by involving seventeen professional female golfers (Age =24.63 ± 3.24 years, Handicap＝2.06 ± 1.18) in a crossover-designed experiment incorporating both NFT and a no-training control condition. During the study, participants executed 40 150-yard swings while receiving continuous SMR neurofeedback. Pre- and post-testing included visual analog scales to assess psychological processes associated with SMR activities, including attention engagement, conscious motor control, and physical relaxation levels. The results revealed that a single session of NFT effectively heightened SMR power irrespective of T1 (p = .02) or T2 (p = .03), which was observed with improved swing accuracy compared to the control conditions, particularly in "To Pin" (p = .04, the absolute distance to the hole after the ball comes to a stop). Subjective assessments further indicated that SMR NFT contributed to a sense of ease and tranquility during motor preparation for the golf swing (attention engagement: p = .01, conscious motor control: p = .033, physical relaxation: p = .013), and which offered valuable insights into the potential mechanisms underlying the impact of SMR NFT on long-game performance. Additionally, in such practical applications professional athletes can utilize our single-session neurofeedback protocol to train efficiently and cost-effectively before competitions, thereby enhancing their opportunity to achieve a higher rank.

"Your Thoughts are (were) Free!": Brain-Computer-Interfaces, Neurofeedback, Detection of Deception, and the Future of Mind-Reading.

This review describes the historical developement and rationale of clinically relevant research on neurophysiological "mind reading" paradims: Brain- Computer-Interfaces, detection of deception, brain stimulation and neurofeedback and the clinical applications in drug resistant epilepsy, chronic stroke, and communication with paralyzed locked-in persons. The emphasis lies on completely locked-in patients with amyotrophic lateral sclerosis using non-invasive and invasive brain computer interfaces and neurofeedback to restore verbal communication with the social environment. In the second part of the article we argue that success and failure of neurophysiological "mind reading" paradigms may be explained with a motor theory of thinking and emotion in combination with learning theory. The ethical implications of brain computer interface and neurofeedback approaches, particularly for severe chronic paralysis and loss of communication diseases and decisions on hastened death and euthanasia are discussed.

Neurofeedback-enabled beta power control with a fully implanted DBS system in patients with Parkinson's disease.

OBJECTIVE: Parkinsonian motor symptoms are linked to pathologically increased beta oscillations in the basal ganglia. Studies with externalised deep brain stimulation electrodes showed that Parkinson patients were able to rapidly gain control over these pathological basal ganglia signals through neurofeedback. Studies with fully implanted deep brain stimulation systems duplicating these promising results are required to grant transferability to daily application. METHODS: In this study, seven patients with idiopathic Parkinson's disease and one with familial Parkinson's disease were included. In a postoperative setting, beta oscillations from the subthalamic nucleus were recorded with a fully implanted deep brain stimulation system and converted to a real-time visual feedback signal. Participants were instructed to perform bidirectional neurofeedback tasks with the aim to modulate these oscillations. RESULTS: While receiving regular medication and deep brain stimulation, participants were able to significantly improve their neurofeedback ability and achieved a significant decrease of subthalamic beta power (median reduction of 31% in the final neurofeedback block). CONCLUSION: We could demonstrate that a fully implanted deep brain stimulation system can provide visual neurofeedback enabling patients with Parkinson's disease to rapidly control pathological subthalamic beta oscillations. SIGNIFICANCE: Fully-implanted DBS electrode-guided neurofeedback is feasible and can now be explored over extended timespans.

Enhancing Working Memory and Reducing Anxiety in University Students: A Neurofeedback Approach.

(1) Background: Neurofeedback training (NFT) has emerged as a promising approach for enhancing cognitive functions and reducing anxiety, yet its specific impact on university student populations requires further investigation. This study aims to examine the effects of NFT on working memory improvement and anxiety reduction within this demographic. (2) Methods: A total of forty healthy university student volunteers were randomized into two groups: an experimental group that received NFT and a control group. The NFT protocol was administered using a 14-channel Emotiv Epoc X headset (EMOTIV, Inc., San Francisco, CA 94102, USA) and BrainViz software version Brain Visualizer 1.1 (EMOTIV, Inc., San Francisco, CA 94102, USA), focusing on the alpha frequency band to target improvements in working memory and reductions in anxiety. Assessment tools, including the Corsi Block and Memory Span tests for working memory and the State-Trait Anxiety Inventory-2 (STAI-2) for anxiety, were applied pre- and post-intervention. (3) Results: The findings indicated an increase in alpha wave amplitude in the experimental group from the second day of NFT, with statistically significant differences observed on days 2 (p < 0.05) and 8 (p < 0.01). Contrary to expectations based on the previous literature, the study did not observe a concurrent positive impact on working memory. Nonetheless, a significant reduction in state anxiety levels was recorded in the experimental group (p < 0.001), corroborating NFT's potential for anxiety management. (4) Conclusions: While these results suggest some potential of the technique in enhancing neural efficiency, the variability across different days highlights the need for further investigation to fully ascertain its effectiveness. The study confirms the beneficial impact of NFT on reducing state anxiety among university students, underscoring its value in psychological and cognitive performance enhancement. Despite the lack of observed improvements in working memory, these results highlight the need for continued exploration of NFT applications across different populations and settings, emphasizing its potential utility in educational and therapeutic contexts.

EEG decoding with spatiotemporal convolutional neural network for visualization and closed-loop control of sensorimotor activities: A simultaneous EEG-fMRI study.

Closed-loop neurofeedback training utilizes neural signals such as scalp electroencephalograms (EEG) to manipulate specific neural activities and the associated behavioral performance. A spatiotemporal filter for high-density whole-head scalp EEG using a convolutional neural network can overcome the ambiguity of the signaling source because each EEG signal includes information on the remote regions. We simultaneously acquired EEG and functional magnetic resonance images in humans during the brain-computer interface (BCI) based neurofeedback training and compared the reconstructed and modeled hemodynamic responses of the sensorimotor network. Filters constructed with a convolutional neural network captured activities in the targeted network with spatial precision and specificity superior to those of the EEG signals preprocessed with standard pipelines used in BCI-based neurofeedback paradigms. The middle layers of the trained model were examined to characterize the neuronal oscillatory features that contributed to the reconstruction. Analysis of the layers for spatial convolution revealed the contribution of distributed cortical circuitries to reconstruction, including the frontoparietal and sensorimotor areas, and those of temporal convolution layers that successfully reconstructed the hemodynamic response function. Employing a spatiotemporal filter and leveraging the electrophysiological signatures of the sensorimotor excitability identified in our middle layer analysis would contribute to the development of a further effective neurofeedback intervention.

Utilizing Phase Locking Value to Determine Neurofeedback Treatment Responsiveness in Attention Deficit Hyperactivity Disorder.

BACKGROUND: Neurofeedback is a non-invasive brain training technique used to enhance and treat hyperactivity disorder by altering the patterns of brain activity. Nonetheless, the extent of enhancement by neurofeedback varies among individuals/patients and many of them are irresponsive to this treatment technique. Therefore, several studies have been conducted to predict the effectiveness of neurofeedback training including the theta/beta protocol with a specific emphasize on slow cortical potential (SCP) before initiating treatment, as well as examining SCP criteria according to age and sex criteria in diverse populations. While some of these studies failed to make accurate predictions, others have demonstrated low success rates. This study explores functional connections within various brain lobes across different frequency bands of electroencephalogram (EEG) signals and the value of phase locking is used to predict the potential effectiveness of neurofeedback treatment before its initiation. METHODS: This study utilized EEG data from the Mendelian database. In this database, EEG signals were recorded during neurofeedback sessions involving 60 hyperactive students aged 7-14 years, irrespective of sex. These students were categorized into treatable and non-treatable. The proposed method includes a five-step algorithm. Initially, the data underwent preprocessing to reduce noise using a multi-stage filtering process. The second step involved extracting alpha and beta frequency bands from the preprocessed EEG signals, with a particular emphasis on the EEG recorded from sessions 10 to 20 of neurofeedback therapy. In the third step, the method assessed the disparity in brain signals between the two groups by evaluating functional relationships in different brain lobes using the phase lock value, a crucial data characteristic. The fourth step focused on reducing the feature space and identifying the most effective and optimal electrodes for neurofeedback treatment. Two methods, the probability index (p-value) via a t-test and the genetic algorithm, were employed. These methods showed that the optimal electrodes were in the frontal lobe and central cerebral cortex, notably channels C3, FZ, F4, CZ, C4, and F3, as they exhibited significant differences between the two groups. Finally, in the fifth step, machine learning classifiers were applied, and the results were combined to generate treatable and non-treatable labels for each dataset. RESULTS: Among the classifiers, the support vector machine and the boosting method demonstrated the highest accuracy when combined. Consequently, the proposed algorithm successfully predicted the treatability of individuals with hyperactivity in a short time and with limited data, achieving an accuracy of 90.6% in the neurofeedback method. Additionally, it effectively identified key electrodes in neurofeedback treatment, reducing their number from 32 to 6. CONCLUSIONS: This study introduces an algorithm with a 90.6% accuracy for predicting neurofeedback treatment outcomes in hyperactivity disorder, significantly enhancing treatment efficiency by identifying optimal electrodes and reducing their number from 32 to 6. The proposed method enables the prediction of patient responsiveness to neurofeedback therapy without the need for numerous sessions, thus conserving time and financial resources.

Neurofeedback and meditation technology in outpatient offender treatment: a feasibility and usability pilot study.

Introduction: Although Cognitive Behavioral Therapy (CBT) is the most often used intervention in forensic treatment, its effectivity is not consistently supported. Interventions incorporating knowledge from neuroscience could provide for more successful intervention methods. Methods: The current pilot study set out to assess the feasibility and usability of the study protocol of a 4-week neuromeditation training in adult forensic outpatients with impulse control problems. The neuromeditation training, which prompts awareness and control over brain states of restlessness with EEG neurofeedback, was offered in addition to treatment as usual (predominantly CBT). Results: Eight patients completed the neuromeditation training under guidance of their therapists. Despite some emerging obstacles, overall, the training was rated sufficiently usable and feasible by patients and their therapists. Discussion: The provided suggestions for improvement can be used to implement the intervention in treatment and set up future trials to study the effectiveness of neuromeditation in offender treatment.

Functional near-infrared spectroscopy-based neurofeedback training regulates time-on-task effects and enhances sustained cognitive performance.

Time-on-task effect is a common consequence of long-term cognitive demand work, which reflects reduced behavioral performance and increases the risk of accidents. Neurofeedback is a neuromodulation method that can guide individuals to regulate their brain activity and manifest as changes in related symptoms and cognitive behaviors. This study aimed to examine the effects of functional near-infrared spectroscopy-based neurofeedback training on time-on-task effects and sustained cognitive performance. A randomized, single-blind, sham-controlled study was performed: 17 participants received feedback signals of their own dorsolateral prefrontal cortex activity (neurofeedback group), and 16 participants received feedback signals of dorsolateral prefrontal cortex activity from the neurofeedback group (sham-neurofeedback group). All participants received 5 neurofeedback training sessions and completed 2 sustained cognitive tasks, including a 2-back task and a psychomotor vigilance task, to evaluate behavioral performance changes following neurofeedback training. Results showed that neurofeedback relative to the sham-neurofeedback group exhibited increased dorsolateral prefrontal cortex activation, increased accuracy in the 2-back task, and decreased mean response time in the psychomotor vigilance task after neurofeedback training. In addition, the neurofeedback group showed slower decline performance during the sustained 2-back task after neurofeedback training compared with sham-neurofeedback group. These findings demonstrate that neurofeedback training could regulate time-on-task effects on difficult task and enhance performance on sustained cognitive tasks by increasing dorsolateral prefrontal cortex activity.

Musical Neurofeedback Advancements, Feedback Modalities, and Applications: A Systematic Review.

The field of EEG-Neurofeedback (EEG-NF) training has showcased significant promise in treating various mental disorders, while also emerging as a cognitive enhancer across diverse applications. The core principle of EEG-NF involves consciously guiding the brain in desired directions, necessitating active engagement in neurofeedback (NF) tasks over an extended period. Music listening tasks have proven to be effective stimuli for such training, influencing emotions, mood, and brainwave patterns. This has spurred the development of musical NF systems and training protocols. Despite these advancements, there exists a gap in systematic literature that comprehensively explores and discusses the various modalities of feedback mechanisms, its benefits, and the emerging applications. Addressing this gap, our review article presents a thorough literature survey encompassing studies on musical NF conducted over the past decade. This review highlights the several benefits and applications ranging from neurorehabilitation to therapeutic interventions, stress management, diagnostics of neurological disorders, and sports performance enhancement. While acknowledged for advantages and popularity of musical NF, there is an opportunity for growth in the literature in terms of the need for systematic randomized controlled trials to compare its effectiveness with other modalities across different tasks. Addressing this gap will involve developing standardized methodologies for studying protocols and optimizing parameters, presenting an exciting prospect for advancing the field.

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

EEG neurofeedback using frontal alpha asymmetry (FAA) has been widely used for emotion regulation, but its effectiveness is controversial. Studies indicated that individual differences in neurofeedback training can be traced to neuroanatomical and neurofunctional features. However, they only focused on regional brain structure or function and overlooked possible neural correlates of the brain network. Besides, no neuroimaging predictors for FAA neurofeedback protocol have been reported so far. We designed a single-blind pseudo-controlled FAA neurofeedback experiment and collected multimodal neuroimaging data from healthy participants before training. We assessed the learning performance for evoked EEG modulations during training (L1) and at rest (L2), and investigated performance-related predictors based on a combined analysis of multimodal brain networks and graph-theoretical features. The main findings of this study are described below. First, both real and sham groups could increase their FAA during training, but only the real group showed a significant increase in FAA at rest. Second, the predictors during training blocks and at rests were different: L1 was correlated with the graph-theoretical metrics (clustering coefficient and local efficiency) of the right hemispheric gray matter and functional networks, while L2 was correlated with the graph-theoretical metrics (local and global efficiency) of the whole-brain and left the hemispheric functional network. Therefore, the individual differences in FAA neurofeedback learning could be explained by individual variations in structural/functional architecture, and the correlated graph-theoretical metrics of learning performance indices showed different laterality of hemispheric networks. These results provided insight into the neural correlates of inter-individual differences in neurofeedback learning. Supplementary Information: The online version contains supplementary material available at 10.1007/s11571-023-09939-x.

Optimizing spatial specificity and signal quality in fNIRS: an overview of potential challenges and possible options for improving the reliability of real-time applications.

The optical brain imaging method functional near-infrared spectroscopy (fNIRS) is a promising tool for real-time applications such as neurofeedback and brain-computer interfaces. Its combination of spatial specificity and mobility makes it particularly attractive for clinical use, both at the bedside and in patients' homes. Despite these advantages, optimizing fNIRS for real-time use requires careful attention to two key aspects: ensuring good spatial specificity and maintaining high signal quality. While fNIRS detects superficial cortical brain regions, consistently and reliably targeting specific regions of interest can be challenging, particularly in studies that require repeated measurements. Variations in cap placement coupled with limited anatomical information may further reduce this accuracy. Furthermore, it is important to maintain good signal quality in real-time contexts to ensure that they reflect the true underlying brain activity. However, fNIRS signals are susceptible to contamination by cerebral and extracerebral systemic noise as well as motion artifacts. Insufficient real-time preprocessing can therefore cause the system to run on noise instead of brain activity. The aim of this review article is to help advance the progress of fNIRS-based real-time applications. It highlights the potential challenges in improving spatial specificity and signal quality, discusses possible options to overcome these challenges, and addresses further considerations relevant to real-time applications. By addressing these topics, the article aims to help improve the planning and execution of future real-time studies, thereby increasing their reliability and repeatability.

Pretraining alpha rhythm enhancement by neurofeedback facilitates short-term perceptual learning and improves visual acuity by facilitated consolidation.

Introduction: Learning through perceptual training using the Gabor patch (GP) has attracted attention as a new vision restoration technique for myopia and age-related deterioration of visual acuity (VA). However, the task itself is monotonous and painful and requires numerous training sessions and some time before being effective, which has been a challenge for its widespread application. One effective means of facilitating perceptual learning is the empowerment of EEG alpha rhythm in the sensory cortex before neurofeedback (NF) training; however, there is a lack of evidence for VA. Methods: We investigated whether four 30-min sessions of GP training, conducted over 2 weeks with/without EEG NF to increase alpha power (NF and control group, respectively), can improve vision in myopic subjects. Contrast sensitivity (CS) and VA were measured before and after each GP training. Results: The NF group showed an improvement in CS at the fourth training session, not observed in the control group. In addition, VA improved only in the NF group at the third and fourth training sessions, this appears as a consolidation effect (maintenance of the previous training effect). Participants who produced stronger alpha power during the third training session showed greater VA recovery during the fourth training session. Discussion: These results indicate that enhanced pretraining alpha empowerment strengthens the subsequent consolidation of perceptual learning and that even a short period of GP training can have a positive effect on VA recovery. This simple protocol may facilitate use of a training method to easily recover vision.

Uncovering the power of neurofeedback: a meta-analysis of its effectiveness in treating major depressive disorders.

Neurofeedback, a non-invasive intervention, has been increasingly used as a potential treatment for major depressive disorders. However, the effectiveness of neurofeedback in alleviating depressive symptoms remains uncertain. To address this gap, we conducted a comprehensive meta-analysis to evaluate the efficacy of neurofeedback as a treatment for major depressive disorders. We conducted a comprehensive meta-analysis of 22 studies investigating the effects of neurofeedback interventions on depression symptoms, neurophysiological outcomes, and neuropsychological function. Our analysis included the calculation of Hedges' g effect sizes and explored various moderators like intervention settings, study designs, and demographics. Our findings revealed that neurofeedback intervention had a significant impact on depression symptoms (Hedges' g = -0.600) and neurophysiological outcomes (Hedges' g = -0.726). We also observed a moderate effect size for neurofeedback intervention on neuropsychological function (Hedges' g = -0.418). As expected, we observed that longer intervention length was associated with better outcomes for depressive symptoms (ß = -4.36, P < 0.001) and neuropsychological function (ß = -2.89, P = 0.003). Surprisingly, we found that shorter neurofeedback sessions were associated with improvements in neurophysiological outcomes (ß = 3.34, P < 0.001). Our meta-analysis provides compelling evidence that neurofeedback holds promising potential as a non-pharmacological intervention option for effectively improving depressive symptoms, neurophysiological outcomes, and neuropsychological function in individuals with major depressive disorders.

Brain regulation training improves emotional competences in patients with alcohol use disorder.

Alcohol use disorder (AUD) is defined as the impaired ability to stop or control alcohol use despite adverse social, occupational or health consequences and still represents one of the biggest challenges for society regarding health conditions, social consequences, and financial costs, including the high relapse rates after traditional alcohol rehabilitation treatment. Especially the deficient emotional competence in AUD is said to play a key role in the development of AUD and hinders to interrupt the substance compulsion, often leading in a viscous circle of relapse. Although the empirical evidence of a neurophysiological basis of alcohol use disorder is solid and increases even further, clinical interventions based on neurophysiology are still rare for individuals with AUD. This randomized, controlled trial investigates changes in emotional competences and alcohol-related cognitions and drinking behavior before and after an established alcohol rehabilitation treatment (control group, nCG = 29) compared to before and after an optimized, add-on neurofeedback training (experimental group: nEG = 27). Improvements on the clinical-psychological level, i.e., increases in emotional competences as well as life satisfaction were found after the experimental EEG-neurofeedback training. Neurophysiological measurements via resting state EEG indicate decreases in low beta frequency band, while alpha and theta band remained unaffected.