SMR/Theta Neurofeedback Training Improves Cognitive Performance and EEG Activity in Elderly With Mild Cognitive Impairment: A Pilot Study

Systematic review and meta-analysis of the effects of EEG neurofeedback combined with pharmacological treatment on the positive and negative symptoms in patients with schizophrenia

Objective

To evaluate the efficacy of EEG neurofeedback (EEG-NF) combined with pharmacological treatment on positive and negative symptoms in schizophrenia.

Methods

Randomized controlled trials (RCTs) were searched in CNKI, Wanfang, VIP, PubMed, Web of Science, Cochrane, and Embase databases until January 25, 2025. Literature quality was assessed using the PEDro and CRED-NF checklists. Meta-analysis and publication bias tests were performed using RevMan 5.4.1 and Stata 18.0, respectively, with evidence quality evaluated via GRADEpro.

Results

Fourteen studies (1371 patients) were included. EEG-NF combined with pharmacological treatment significantly improved positive (SMD=-0.87) and negative symptoms (SMD=-1.28). Subgroup analysis showed greater improvement in patients aged ≥45 years (positive: SMD=-1.05; negative: SMD=-1.64). For positive symptoms, better outcomes were observed with intervention periods ≥8 weeks, frequency ≥4 times/week, and disease duration ≥5 years (SMD=-1.04, -0.94, -0.94). For negative symptoms, better outcomes were seen with intervention periods ≥8 weeks, frequency ≥4 times/week, and disease duration <5 years (SMD=-1.34, -1.68, -1.26). Mental and emotional disorders treatment regimens targeting sensorimotor rhythm (SMR) and beta waves showed significant improvement in both positive (SMD=-0.98) and negative symptoms (SMD=-1.49).

Conclusion

EEG-NF combined with pharmacological treatment effectively improves schizophrenia symptoms. A regimen of ≥4 sessions/week for ≥8 weeks, targeting SMR and beta waves, is recommended. However, publication bias may limit the generalizability of findings. Future research should prioritize larger-scale, multicenter studies to evaluate long-term efficacy and mechanisms.

Systematic Review Registration

www.crd.york.ac.uk, identifier CRD42024593505.

On the feasibility of an online brain-computer interface-based neurofeedback game for enhancing attention and working memory in stroke and mild cognitive impairment patients

Background. Neurofeedback training (NFT) using Electroencephalogram-based Brain Computer Interface (EEG-BCI) is an emerging therapeutic tool for enhancing cognition.Methods. We developed an EEG-BCI-based NFT game for enhancing attention and working memory of stroke and Mild cognitive impairment (MCI) patients. The game involves a working memory task during which the players memorize locations of images in a matrix and refill them correctly using their attention levels. The proposed NFT was conducted across fifteen participants (6 Stroke, 7 MCI, and 2 non-patients). The effectiveness of the NFT was evaluated using the percentage of correctly filled matrix elements and EEG-based attention score. EEG varitions during working memory tasks were also investigated using EEG topographs and EEG-based indices.Results. The EEG-based attention score showed an enhancement ranging from 4.29-32.18% in the Stroke group from the first session to the third session, while in the MCI group, the improvement ranged from 4.32% to 48.25%. We observed significant differences in EEG band powers during working memory operation between the stroke and MCI groups.Significance. The proposed neurofeedback game operates based on attention and aims to improve multiple cognitive functions, including attention and working memory, in patients with stroke and MCI.Conclusions. The experimental results on the effect of NFT in patient groups demonstrated that the proposed neurofeedback game has the potential to enhance attention and memory skills in patients with neurological disorders. A large-scale study is needed in the future to prove the efficacy on a wider population.

Brain computer interfaces for cognitive enhancement in older people - challenges and applications: a systematic review

BACKGROUND

Brain-computer interface (BCI) offers promising solutions to cognitive enhancement in older people. Despite the clear progress received, there is limited evidence of BCI implementation for rehabilitation. This systematic review addresses BCI applications and challenges in the standard practice of EEG-based neurofeedback (NF) training in healthy older people or older people with mild cognitive impairment (MCI).

METHODS

Articles were searched via MEDLINE, PubMed, SCOPUS, SpringerLink, and Web of Science. 16 studies between 1st January 2010 to 1st November 2024 are included after screening using PRISMA. The risk of bias, system design, and neurofeedback protocols are reviewed.

RESULTS

The successful BCI applications in NF trials in older people were biased by the randomisation process and outcome measurement. Although the studies demonstrate promising results in effectiveness of research-grade BCI for cognitive enhancement in older people, it is premature to make definitive claims about widespread BCI usability and applicability.

SIGNIFICANCE

This review highlights the common issues in the field of EEG-based BCI for older people. Future BCI research could focus on trial design and BCI performance gaps between the old and the young to develop a robust BCI system that compensates for age-related declines in cognitive and motor functions.

Diagnosis of Cognitive and Mental Disorders: A New Approach Based on Spectral-Spatiotemporal Analysis and Local Graph Structures of Electroencephalogram Signals

BACKGROUND/OBJECTIVES

The classification of psychological disorders has gained significant importance due to recent advancements in signal processing techniques. Traditionally, research in this domain has focused primarily on binary classifications of disorders. This study aims to classify five distinct states, including one control group and four categories of psychological disorders.

METHODS

Our investigation will utilize algorithms based on Granger causality and local graph structures to improve classification accuracy. Feature extraction from connectivity matrices was performed using local structure graphs. The extracted features were subsequently classified employing K-Nearest Neighbors (KNN), Support Vector Machine (SVM), AdaBoost, and Naïve Bayes classifiers.

RESULTS

The KNN classifier demonstrated the highest accuracy in the gamma band for the depression category, achieving an accuracy of 89.36%, a sensitivity of 89.57%, an F1 score of 94.30%, and a precision of 99.90%. Furthermore, the SVM classifier surpassed the other machine learning algorithms when all features were integrated, attaining an accuracy of 89.06%, a sensitivity of 88.97%, an F1 score of 94.16%, and a precision of 100% for the discrimination of depression in the gamma band.

CONCLUSIONS

The proposed methodology provides a novel approach for analyzing EEG signals and holds potential applications in the classification of psychological disorders.

Exploring neurofeedback as a therapeutic intervention for subjective cognitive decline

IMPACT STATEMENT

This study addresses the pressing issue of subjective cognitive decline in aging populations by investigating neurofeedback (NFB) as a potential early therapeutic intervention. By evaluating the efficacy of individualised NFB training compared to standard protocols, tailored to each participant's EEG profile, it provides novel insights into personalised treatment approaches. The incorporation of innovative elements and rigorous analytical techniques contributes to advancing our understanding of NFB's modulatory effects on EEG frequencies and cognitive function in aging individuals.

ABSTRACT

In the context of an aging population, concerns surrounding memory function become increasingly prevalent, particularly as individuals transition into middle age and beyond. This study investigated neurofeedback (NFB) as a potential early therapeutic intervention to address subjective cognitive decline (SCD) in aging populations. NFB, a biofeedback technique utilising a brain-computer interface, has demonstrated promise in the treatment of various neurological and psychological conditions. Here, we evaluated the efficacy of individualised NFB training, tailored to each participant's EEG profile, compared to a standard NFB training protocol aimed at increasing peak alpha frequency power, in enhancing cognitive function among individuals experiencing SCD. Our NFB protocol incorporated innovative elements, including the implementation of a criterion for learning success to ensure consistent achievement levels by the conclusion of the training sessions. Additionally, we introduced a non-learner group to account for individuals who do not demonstrate the expected proficiency in NFB regulation. Analysis of electroencephalographic (EEG) signals during NFB sessions, as well as before and after training, provides insights into the modulatory effects of NFB on EEG frequencies. Contrary to expectations, our rigorous analysis revealed that the ability of individuals with SCD to modulate EEG signal power and duration at specific frequencies was not exclusive to the intended frequency target. Furthermore, examination of EEG signals recorded using a high-density EEG showed no discernible alteration in signal power between pre- and post-NFB training sessions. Similarly, no significant effects were observed on questionnaire scores when comparing pre- and post-NFB training assessments.

Longitudinal trajectories of general cognitive and daily functions in data-driven subtypes of MCI: A longitudinal cohort analysis of older adults

OBJECTIVES

To derive data-driven subtypes of mild cognitive impairment (MCI) and characterize the complicated changes of general cognitive and daily functions over time in MCI subtypes.

METHODS

A total of 813 subjects diagnosed as MCI at baseline from the Alzheimer's Disease Neuroimaging Initiative (ADNI) were included. Data-driven MCI subtypes were derived from group-based multi-trajectory modeling (GBMTM) analyses using longitudinal measurement scores in the cognitive domains of visuospatial function, language, and executive function. General cognitive and daily functions were measured by the Mini-Mental State Examination (MMSE) and the Functional Assessment Questionnaire (FAQ), respectively, whose longitudinal trajectory changes were depicted by Linear mixed models.

RESULTS

Three MCI subtypes were derived, which were defined as "Cognitive decline group", "Mild cognitive decline group" and "No cognitive decline group". The "Mild cognitive decline group" had the highest percentage in the sample (46.2 %), followed by the "No cognitive decline group" (35.2 %). Patients in the "Cognitive decline group" had the highest mean age (74.69 years) at baseline, the highest APOE ε4 carriers (63.2 %), and the greatest dementia conversion rate (77.0 %). The changes in MMSE and FAQ score trajectories were fastest in the "Cognitive decline group" in the first 36 months and most slowly in the "No cognitive decline group".

CONCLUSION

MCI individuals could be subdivided into more fine-grained cognitive subtypes, and identifying these distinct MCI subtypes and their different trajectories of cognitive decline may have important prognostic value for improving clinical course prediction.

Differential roles of brain oscillations in numerical processing: evidence from resting-state EEG and mental number line

Recent works point to the importance of emotions in special-numerical associations. There remains a notable gap in understanding the electrophysiological underpinnings of such associations. Exploring resting-state (rs) EEG, particularly in frontal regions, could elucidate emotional aspects, while other EEG measures might offer insights into the cognitive dimensions correlating with behavioral performance. The present work investigated the relationship between rs-EEG measures (emotional and cognitive traits) and performance in the mental number line (MNL). EEG activity in theta (3-7 Hz), alpha (8-12 Hz, further subdivided into low-alpha and high-alpha), sensorimotor rhythm (SMR, 13-15 Hz), beta (16-25 Hz), and high-beta/gamma (28-40 Hz) bands was assessed. 76 university students participated in the study, undergoing EEG recordings at rest before engaging in a computerized number-to-position (CNP) task. Analysis revealed significant associations between frontal asymmetry, specific EEG frequencies, and MNL performance metrics (i.e., mean direction bias, mean absolute error, and mean reaction time). Notably, theta and beta asymmetries correlated with direction bias, while alpha peak frequency (APF) and beta activity related to absolute errors in numerical estimation. Moreover, the study identified significant correlations between relative amplitude indices (i.e., theta/beta ratio, theta/SMR ratio) and both absolute errors and reaction times (RTs). Our findings offer novel insights into the emotional and cognitive aspects of EEG patterns and their links to MNL performance.

Network meta-analysis of the effects of different cognitive trainings on the cognitive function of patients with mild cognitive impairment

OBJECTIVE

Examining the relationship between the responses of a number of different cognitive trainings on cognitive functioning in middle-aged and elderly patients with mild cognitive impairment.

METHODS

Randomized controlled experimental studies published publicly from the time of inception to October 30, 2023 were searched through Web of Science, PubMed, Embase, and Cochrane library databases. Traditional and network meta-analyses were performed using Stata 17.0 software.

RESULTS

Fifty papers on 4 types of cognitive training were included. Traditional meta-analysis showed that virtual reality training (SMD = 0.53, 95%CI: [0.36,0.70], P = 0.00), neuropsychological training (SMD = 0.44, 95%CI: [0.18,0.70], P = 0.00), cognitive strategy training (SMD = 0.26, 95%CI: [0.16,0.36], P = 0.00), and cognitive behavioral therapy (SMD = 0.25, 95%CI: [0.08,0.41], P = 0.00) all had significant improvement effects on the cognitive function of middle-aged and elderly patients with mild cognitive impairment. Network meta-analysis revealed neuropsychological training as the best cognitive training, and subgroup analysis of cognitive function subdimensions showed that neuropsychological training had the best effects on working memory, lobal cognitive function, memory, and cognitive flexibility improvement. Meanwhile, virtual reality training had the best effects on processing speed, verbal ability, overall executive function, spatial cognitive ability, and attention improvement.

CONCLUSION

Cognitive training can significantly improve the cognitive function of middle-aged and elderly patients with mild cognitive impairment, and neuropsychological training is the best intervention, most effective in interventions lasting more than 8 weeks.

Mapping the evolution of neurofeedback research: a bibliometric analysis of trends and future directions

Introduction

This study conducts a bibliometric analysis on neurofeedback research to assess its current state and potential future developments.

Methods

It examined 3,626 journal articles from the Web of Science (WoS) using co-citation and co-word methods.

Results

The co-citation analysis identified three major clusters: "Real-Time fMRI Neurofeedback and Self-Regulation of Brain Activity," "EEG Neurofeedback and Cognitive Performance Enhancement," and "Treatment of ADHD Using Neurofeedback." The co-word analysis highlighted four key clusters: "Neurofeedback in Mental Health Research," "Brain-Computer Interfaces for Stroke Rehabilitation," "Neurofeedback for ADHD in Youth," and "Neural Mechanisms of Emotion and Self-Regulation with Advanced Neuroimaging.

Discussion

This in-depth bibliometric study significantly enhances our understanding of the dynamic field of neurofeedback, indicating its potential in treating ADHD and improving performance. It offers non-invasive, ethical alternatives to conventional psychopharmacology and aligns with the trend toward personalized medicine, suggesting specialized solutions for mental health and rehabilitation as a growing focus in medical practice.

Accelerating P300-based neurofeedback training for attention enhancement using iterative learning control: a randomised controlled trial

Objective. Neurofeedback (NFB) training through brain-computer interfacing has demonstrated efficacy in treating neurological deficits and diseases, and enhancing cognitive abilities in healthy individuals. It was previously shown that event-related potential (ERP)-based NFB training using a P300 speller can improve attention in healthy adults by incrementally increasing the difficulty of the spelling task. This study aims to assess the impact of task difficulty adaptation on ERP-based attention training in healthy adults. To achieve this, we introduce a novel adaptation employing iterative learning control (ILC) and compare it against an existing method and a control group with random task difficulty variation.Approach. The study involved 45 healthy participants in a single-blind, three-arm randomised controlled trial. Each group underwent one NFB training session, using different methods to adapt task difficulty in a P300 spelling task: two groups with personalised difficulty adjustments (our proposed ILC and an existing approach) and one group with random difficulty. Cognitive performance was evaluated before and after the training session using a visual spatial attention task and we gathered participant feedback through questionnaires.Main results. All groups demonstrated a significant performance improvement in the spatial attention task post-training, with an average increase of 12.63%. Notably, the group using the proposed iterative learning controller achieved a 22% increase in P300 amplitude during training and a 17% reduction in post-training alpha power, all while significantly accelerating the training process compared to other groups.Significance. Our results suggest that ERP-based NFB training using a P300 speller effectively enhances attention in healthy adults, with significant improvements observed after a single session. Personalised task difficulty adaptation using ILC not only accelerates the training but also enhances ERPs during the training. Accelerating NFB training, while maintaining its effectiveness, is vital for its acceptability by both end-users and clinicians.

Effectiveness of Electroencephalography Neurofeedback for Improving Working Memory and Episodic Memory in the Elderly: A Meta-Analysis

Background and Objective: Existing evidence indicates the potential benefits of electroencephalography neurofeedback (NFB) training for cognitive function. This study aims to comprehensively review all available evidence investigating the effectiveness of NFB on working memory (WM) and episodic memory (EM) in the elderly population. Material and Methods: A systematic search was conducted across five databases to identify clinical trials examining the impact of NFB on memory function in healthy elderly individuals or those with mild cognitive impairment (MCI). The co-primary outcomes focused on changes in WM and EM. Data synthesis was performed using a random-effects meta-analysis. Results: Fourteen clinical trials (n = 284) were included in the analysis. The findings revealed that NFB was associated with improved WM (k = 11, reported as Hedges' g = 0.665, 95% confidence [CI] = 0.473 to 0.858, p < 0.001) and EM (k = 12, 0.595, 0.333 to 0.856, p < 0.001) in the elderly, with moderate effect sizes. Subgroup analyses demonstrated that NFB had a positive impact on both WM and EM, not only in the healthy population (WM: k = 7, 0.495, 0.213 to 0.778, p = 0.001; EM: k = 6, 0.729, 0.483 to 0.976, p < 0.001) but also in those with MCI (WM: k = 6, 0.812, 0.549 to 1.074, p < 0.001; EM: k = 6, 0.503, 0.088 to 0.919, p = 0.018). Additionally, sufficient training time (totaling more than 300 min) was associated with a significant improvement in WM (k = 6, 0.743, 0.510 to 0.976, p < 0.001) and EM (k = 7, 0.516, 0.156 to 0.876, p = 0.005); however, such benefits were not observed in groups with inadequate training time. Conclusions: The results suggest that NFB is associated with enhancement of both WM and EM in both healthy and MCI elderly individuals, particularly when adequate training time (exceeding 300 min) is provided. These findings underscore the potential of NFB in dementia prevention or rehabilitation.

The efficacy of electroencephalography neurofeedback for enhancing episodic memory in healthy and clinical participants: A systematic qualitative review and meta-analysis

Several studies have examined whether electroencephalography neurofeedback (EEG-NF), a self-regulatory technique where an individual receives real-time feedback on a pattern of brain activity that is theoretically linked to a target behaviour, can enhance episodic memory. The aim of this research was to i) provide a qualitative overview of the literature, and ii) conduct a meta-analysis of appropriately controlled studies to determine whether EEG-NF can enhance episodic memory. The literature search returned 46 studies, with 21 studies (44 effect sizes) meeting the inclusion criteria for the meta-analysis. The qualitative overview revealed that, across EEG-NF studies on both healthy and clinical populations, procedures and protocols vary considerably and many studies were insufficiently powered with inadequate design features. The meta-analysis, conducted on studies with an active control, revealed a small-size, significant positive effect of EEG-NF on episodic memory performance (g = 0.31, p = 0.003), moderated by memory modality and EEG-NF self-regulation success. These results are discussed with a view towards optimising EEG-NF training and subsequent benefits to episodic memory.

Clinical applications of neurofeedback based on sensorimotor rhythm: a systematic review and meta-analysis

Background

Among the brain-machine interfaces, neurofeedback is a non-invasive technique that uses sensorimotor rhythm (SMR) as a clinical intervention protocol. This study aimed to investigate the clinical applications of SMR neurofeedback to understand its clinical effectiveness in different pathologies or symptoms.

Methods

A systematic review study with meta-analysis of the clinical applications of EEG-based SMR neurofeedback performed using pre-selected publication databases. A qualitative analysis of these studies was performed using the Consensus tool on the Reporting and Experimental Design of Neurofeedback studies (CRED-nf). The Meta-analysis of clinical efficacy was carried out using Review Manager software, version 5.4.1 (RevMan 5; Cochrane Collaboration, Oxford, UK).

Results

The qualitative analysis includes 44 studies, of which only 27 studies had some kind of control condition, five studies were double-blinded, and only three reported a blind follow-up throughout the intervention. The meta-analysis included a total sample of 203 individuals between stroke and fibromyalgia. Studies on multiple sclerosis, insomnia, quadriplegia, paraplegia, and mild cognitive impairment were excluded due to the absence of a control group or results based only on post-intervention scales. Statistical analysis indicated that stroke patients did not benefit from neurofeedback interventions when compared to other therapies (Std. mean. dif. 0.31, 95% CI 0.03-0.60, p = 0.03), and there was no significant heterogeneity among stroke studies, classified as moderate I2 = 46% p-value = 0.06. Patients diagnosed with fibromyalgia showed, by means of quantitative analysis, a better benefit for the group that used neurofeedback (Std. mean. dif. -0.73, 95% CI -1.22 to -0.24, p = 0.001). Thus, on performing the pooled analysis between conditions, no significant differences were observed between the neurofeedback intervention and standard therapy (0.05, CI 95%, -0.20 to -0.30, p = 0.69), with the presence of substantial heterogeneity I2 = 92.2%, p-value < 0.001.

Conclusion

We conclude that although neurofeedback based on electrophysiological patterns of SMR contemplates the interest of numerous researchers and the existence of research that presents promising results, it is currently not possible to point out the clinical benefits of the technique as a form of clinical intervention. Therefore, it is necessary to develop more robust studies with a greater sample of a more rigorous methodology to understand the benefits that the technique can provide to the population.

Feasibility of a novel neurofeedback system: a parallel randomized single-blinded pilot study

Neurocognitive assessment tools have been proposed to optimize, maintain, and improve perceptual-cognitive performance. Here, we investigated the feasibility and efficacy of a novel neurofeedback system, neuroMoon (nM), on cognitive abilities compared with one of the most popular perceptual-cognitive training (PCT) tools both in sports and rehabilitation called NeuroTracker (NT). Thirty-one young athletes performed a comprehensive battery of cognitive tests from the Vienna Test System before and after a 12-session computer-based cognitive training program using nM (n = 11, age 22.6 ± 3.8 years), nM sham (CON, n = 10, age 20.3 ± 1.2 years) or NT (n = 10, age 20.5 ± 1.7 years) device. A series of repeated-measures ANOVA was performed to detect changes in cognitive abilities in response to the training. Participants had faster median reaction time in both the color-naming and word-reading conditions of the Stroop test (all p < 0.005), regardless of group. Regarding the task switching test, statistical analysis indicated faster working time and mean reaction time of the incongruent stimuli, repetition task, and shifting task (all p < 0.005), nevertheless, these changes were also regardless of group. In addition, we found fewer omitted (pre: 17.5 ± 8.3, post: 6.4 ± 1.5, d = 1.311) and more correct (pre: 261.6 ± 36.1, post: 278.6 ± 38.7, d = - 1.020) post-intervention answers in the determination test, regardless of group. Finally, participants in each group performed the digit span backward test with larger post (6.42 ± 1.54) vs. pre (5.55 ± 1.43) scores following the PCT (d = - 0.801). Overall, PCT with nM as compared with NT induced similar results in cognitive abilities suggesting its potential to be used to achieve and maintain better mental performance. However, considering that the sham stimulation also induced similar improvements in cognitive abilities, future studies should clearly determine the cognitive measures that could benefit from NF training.

Training the brain to time: the effect of neurofeedback of SMR-Beta1 rhythm on time perception in healthy adults

The timing ability plays an important role in everyday activities and is influenced by several factors such as the attention and arousal levels of the individuals. The effects of these factors on time perception have been interpreted through psychological models of time, including Attentional Gate Model (AGM). On the other hand, research has indicated that neurofeedback (NFB) training improves attention and increases arousal levels in the clinical and healthy population. Regarding the link between attentional processing and arousal levels and NFB and their relation to time perception, this study is a pilot demonstration of the influence of SMR-Beta1 (12-18 Hz) NFB training on time production and reproduction performance in healthy adults. To this end, 12 (9 female and 3 males; M = 26.3, SD = 3.8) and 12 participants (7 female and 5 males; M = 26.9, SD = 3.1) were randomly assigned into the experimental (with SMR-Beta1 NFB) and control groups (without any NFB training), respectively. The experimental group underwent intensive 10 sessions (3 days a week) of the 12-18 Hz up-training. Time production and reproduction performance were assessed pre and post NFB training for all participants. Three-way mixed ANOVA was carried out on T-corrected scores of reproduction and production tasks. Correlation analysis was also performed between SMR-Beta1 and time perception. While NFB training significantly influenced time production (P < 0.01), no such effect was observed for the time reproduction task. The results of the study are finally discussed within the frameworks of AGM, dual-process and cognitive aspects of time perception. Overall, our results contribute to disentangling the underlying mechanisms of temporal performance in healthy individuals.

Effects of combined cognitive and physical intervention on enhancing cognition in older adults with and without mild cognitive impairment: A systematic review and meta-analysis

Background

Combined cognitive and physical intervention is commonly used as a non-pharmacological therapy to improve cognitive function in older adults, but it is uncertain whether combined intervention can produce stronger cognitive gains than either single cognitive or sham intervention. To address this uncertainty, we performed a systematic review and meta-analysis to evaluate the effects of combined intervention on cognition in older adults with and without mild cognitive impairment (MCI).

Methods

We systematically searched eight databases for relevant articles published from inception to November 1, 2021. Randomized controlled trials (RCTs) and non-randomized controlled trials (NRCTs) were used to compare the effects of the combined intervention with a single cognitive or sham intervention on cognition in older adults with and without MCI aged ≥ 50 years. We also searched Google Scholar, references of the included articles, and relevant reviews. Two independent reviewers performed the article screening, data extraction, and bias assessment. GRADEpro was used to rate the strength of evidence, and RevMan software was used to perform the meta-analysis.

Results

Seventeen studies were included in the analysis, comprising eight studies of cognitively healthy older adults and nine studies of older adults with MCI. The meta-analysis showed that the combined intervention significantly improved most cognitive functions and depression (SMD = 0.99, 95% CI 0.54-1.43, p < 0.0001) in older adults compared to the control groups, but the intervention effects varied by cognition domains. However, there was no statistically significant difference in the maintenance between the combined and sham interventions (SMD = 1.34, 95% CI -0.58-3.27, p = 0.17). The subgroup analysis also showed that there was no statistical difference in the combined intervention to improve global cognition, memory, attention, and executive function between cognitive healthy older adults and older adults with MCI.

Conclusions

Combined intervention improves cognitive functions in older adults with and without MCI, especially in global cognition, memory, and executive function. However, there was no statistical difference in the efficacy of the combined intervention to improve cognition between cognitive healthy older adults and older adults with MCI. Moreover, the maintenance of the combined intervention remains unclear due to the limited follow-up data and high heterogeneity. In the future, more stringent study designs with more follow-ups are needed further to explore the effects of combined intervention in older adults.

Systematic review registration

https://www.crd.york.ac.uk/PROSPERO/#recordDetails, identifier: CRD42021292490.

Changes in Human Electroencephalographic Activity in Response to Agastache rugosa Essential Oil Exposure

Agastache rugosa (Korean mint) is an important medicinal and aromatic plant and its aerial parts have a pleasant fragrance. A. rugosa leaves are used as an ingredient in salads and soups for enhancing the aroma and taste of foods in Korea. However, there is no report on the influence of the aroma of A. rugosa on human psychophysiological activity. Therefore, the present study aimed to investigate the effect of exposure to the essential oil of Korean A. rugosa on human electroencephalographic (EEG) activity. The essential oil of A. rugosa was isolated using steam distillation extraction and its composition was determined by gas chromatography and mass spectrometry (GC-MS) analysis. In the EEG study, 38 healthy volunteers (19 men and 19 women) participated. The EEG readings were analyzed for 25 EEG indices from 29 electrodes placed on the scalp according to the international 10-20 system. The major component in the essential oil of A. rugosa was estragole (89.49%) followed by D-limonene (3.40%), menthone (1.80%), and pulegone (1.86%). In the EEG study, significant decreases in absolute theta (AT) and relative theta (RT) power spectra were observed during the exposure to A. rugosa essential oil when compared to that of no odor exposure. Whereas relative alpha (RA), relative slow alpha (RSA), spectral edge frequency 50% (SEF50), and spectral edge frequency 50% of alpha (ASEF) power spectra values significantly increased. These results reveal that the EEG power spectra changes incurred during the exposure to the essential oil of A. rugosa may be associated with the enhancement of freshness and concentration states of the human brain.

Sharpening Working Memory With Real-Time Electrophysiological Brain Signals: Which Neurofeedback Paradigms Work?

Growing evidence supports the idea that the ultimate biofeedback is to reward sensory pleasure (e.g., enhanced visual clarity) in real-time to neural circuits that are associated with a desired performance, such as excellent memory retrieval. Neurofeedback is biofeedback that uses real-time sensory reward to brain activity associated with a certain performance (e.g., accurate and fast recall). Working memory is a key component of human intelligence. The challenges are in our current limited understanding of neurocognitive dysfunctions as well as in technical difficulties for closed-loop feedback in true real-time. Here we review recent advancements of real time neurofeedback to improve memory training in healthy young and older adults. With new advancements in neuromarkers of specific neurophysiological functions, neurofeedback training should be better targeted beyond a single frequency approach to include frequency interactions and event-related potentials. Our review confirms the positive trend that neurofeedback training mostly works to improve memory and cognition to some extent in most studies. Yet, the training typically takes multiple weeks with 2-3 sessions per week. We review various neurofeedback reward strategies and outcome measures. A well-known issue in such training is that some people simply do not respond to neurofeedback. Thus, we also review the literature of individual differences in psychological factors e.g., placebo effects and so-called "BCI illiteracy" (Brain Computer Interface illiteracy). We recommend the use of Neural modulation sensitivity or BCI insensitivity in the neurofeedback literature. Future directions include much needed research in mild cognitive impairment, in non-Alzheimer's dementia populations, and neurofeedback using EEG features during resting and sleep for memory enhancement and as sensitive outcome measures.

Emotion Recognition Using Electroencephalography Signals of Older People for Reminiscence Therapy

Objective: Numerous communication support systems based on reminiscence therapy have been developed. However, when using communication support systems, the emotional assessment of older people is generally conducted using verbal feedback or questionnaires. The purpose of this study is to investigate the feasibility of using Electroencephalography (EEG) signals for automatic emotion recognition during RT for older people. Participants: Eleven older people (mean 71.25, SD 4.66) and seven young people (mean 22.4, SD 1.51) participated in the experiment. Methods: Old public photographs were used as material for reminiscence therapy. The EEG signals of the older people were collected while the older people and young people were talking about the contents of the photos. Since emotions change slowly and responses are characterized by delayed effects in EEG, the depth models LSTM and Bi-LSTM were selected to extract complex emotional features from EEG signals for automatic recognition of emotions. Results: The EEG data of 8 channels were inputted into the LSTM and Bi-LSTM models to classify positive and negative emotions. The recognition highest accuracy rate of the two models were 90.8% and 95.8% respectively. The four-channel EEG data based Bi-LSTM also reached 94.4%. Conclusion: Since the Bi-LSTM model could tap into the influence of "past" and "future" emotional states on the current emotional state in the EEG signal, we found that it can help improve the ability to recognize positive and negative emotions in older people. In particular, it is feasible to use EEG signals without the necessity of multimodal physiological signals for emotion recognition in the communication support systems for reminiscence therapy when using this model.

One-Year Follow-Up of Healthy Older Adults with Electroencephalographic Risk for Neurocognitive Disorder After Neurofeedback Training

Background:

In healthy older adults, excess theta activity is an electroencephalographic (EEG) predictor of cognitive impairment. In a previous study, neurofeedback (NFB) treatment reinforcing reductions theta activity resulted in EEG reorganization and cognitive improvement.

Objective:

To explore the clinical applicability of this NFB treatment, the present study performed a 1-year follow-up to determine its lasting effects.

Methods:

Twenty seniors with excessive theta activity in their EEG were randomly assigned to the experimental or control group. The experimental group received an auditory reward when the theta absolute power (AP) was reduced. The control group received the reward randomly.

Results:

Both groups showed a significant decrease in theta activity at the training electrode. However, the EEG results showed that only the experimental group underwent global changes after treatment. These changes consisted of delta and theta decreases and beta increases. Although no changes were found in any group during the period between the posttreatment evaluation and follow-up, more pronounced theta decreases and beta increases were observed in the experimental group when the follow-up and pretreatment measures were compared. Executive functions showed a tendency to improve two months after treatment which became significant one year later.

Conclusion:

These results suggest that the EEG and behavioral benefits of this NFB treatment persist for at least one year, which adds up to the available evidence contributing to identifying factors that increase its efficacy level. The relevance of this study lies in its prophylactic features of addressing a clinically healthy population with EEG risk of cognitive decline.

Neurofeedback Training Based on Motor Imagery Strategies Increases EEG Complexity in Elderly Population

Neurofeedback training (NFT) has shown promising results in recent years as a tool to address the effects of age-related cognitive decline in the elderly. Since previous studies have linked reduced complexity of electroencephalography (EEG) signal to the process of cognitive decline, we propose the use of non-linear methods to characterise changes in EEG complexity induced by NFT. In this study, we analyse the pre- and post-training EEG from 11 elderly subjects who performed an NFT based on motor imagery (MI-NFT). Spectral changes were studied using relative power (RP) from classical frequency bands (delta, theta, alpha, and beta), whilst multiscale entropy (MSE) was applied to assess EEG-induced complexity changes. Furthermore, we analysed the subject's scores from Luria tests performed before and after MI-NFT. We found that MI-NFT induced a power shift towards rapid frequencies, as well as an increase of EEG complexity in all channels, except for C3. These improvements were most evident in frontal channels. Moreover, results from cognitive tests showed significant enhancement in intellectual and memory functions. Therefore, our findings suggest the usefulness of MI-NFT to improve cognitive functions in the elderly and encourage future studies to use MSE as a metric to characterise EEG changes induced by MI-NFT.

Investigation of combined treatment of acupuncture and neurofeedback for improving cognitive function in mild neurocognitive disorder: A randomized, assessor-blind, pilot study

BACKGROUND

Mild neurocognitive disorder (MND) is an intermediate state that can progress to dementia, and the cognitive reserve of MND is an important task in preventing dementia. Acupuncture and neurofeedback (NF) training have been used to improve cognitive function and treat MND or dementia, but their effectiveness remains controversial. In this trial, we will evaluate the efficacy and safety of combined NF-acupuncture treatment in comparison with single acupuncture treatment.

METHODS AND DESIGN

This study is a randomized, assessor-blind, pilot trial. It is designed in accordance with the Standards for Reporting Interventions in Controlled Trials of Acupuncture. A total of 44 MND participants who meet the inclusion and exclusion criteria will be enrolled, and each will be randomly assigned to 1 of 2 groups of 22 subjects. Each subject will visit 24 times over 12 weeks and receive either acupuncture or NF-acupuncture combined treatment. At visit 25 (week 13), a follow-up evaluation will be performed, and then the investigator will analyze the results. The primary outcome is defined by the Korean version of the Montreal Cognitive Assessment score from screening to visit 25. The secondary outcome includes the following: change in Alzheimer Disease Assessment Scale-Cognitive, the Korean version of the Beck Depression Inventory, Body Awareness Questionnaire, delayed matching to sample task scores, and functional near-infrared spectroscopy values, from visit 1 to visit 25; heart rate variability values from visit 1 to visit 5, visit 9, visit 13, visit 21, visit 25; breath per minute values from visit 1 to visit 1 to 25.

DISCUSSION

We will evaluate the effectiveness and safety of combined NF-acupuncture therapy, and expect that it will serve as the basis for the use of NF together with acupuncture in the clinical setting.

TRIAL REGISTRATION NUMBER

KCT0004972 (registered in Clinical Research Information Service of the Republic of Korea, https://cris.nih.go.kr/cris/search/detailSearch.do/16239).

Evaluation of the Brain Function State During Mild Cognitive Impairment Based on Weighted Multiple Multiscale Entropy

The mild cognitive impairment (MCI) stage plays an essential role in preventing the progression of older adults to Alzheimer's disease. In this study, neurofeedback training (NFT) is applied to improve MCI brain cognitive function. To assess the improvement effect, a novel algorithm called Weighted Multiple Multiscale Entropy (WMMSE) is proposed to extract and analyze the electroencephalogram (EEG) features of patients with MCI. To overcome the information loss problem of traditional multiscale entropy (MSE), WMMSE fully considered the correlation of the sequence and the contribution of each sequence to the total entropy. The experimental group composed of 39 patients with MCI was subjected to NFT for 10 days during two sessions. The control group included 21 patients with MCI without any intervention. The Lempel-Ziv complexity (LZC) was used for primary assessment, and WMMSE was used to accurately analyze the effect of NFT. The results show that the WMMSE values of F4, C3, C4, O1, and T5 channels post-NFT are higher compared with pre-NFT and significant differences (P < 0.05). Moreover, the cognitive subscale of the Montreal Cognitive Assessment (MoCA) results shows that the post-NFT score is higher than the pre-NFT in the vast majority of the patients with MCI and significant differences (P < 0.05). When compared with the control group, the WMMSE values of the experimental group increased in each channel. Therefore, the NFT intervention method contributes to brain cognitive functional recovery, and WMMSE can be used as a biomarker to evaluate the state of MCI brain cognitive function.

Neurofeedback and the Aging Brain: A Systematic Review of Training Protocols for Dementia and Mild Cognitive Impairment

Dementia describes a set of symptoms that occur in neurodegenerative disorders and that is characterized by gradual loss of cognitive and behavioral functions. Recently, non-invasive neurofeedback training has been explored as a potential complementary treatment for patients suffering from dementia or mild cognitive impairment. Here we systematically reviewed studies that explored neurofeedback training protocols based on electroencephalography or functional magnetic resonance imaging for these groups of patients. From a total of 1,912 screened studies, 10 were included in our final sample (N = 208 independent participants in experimental and N = 81 in the control groups completing the primary endpoint). We compared the clinical efficacy across studies, and evaluated their experimental designs and reporting quality. In most studies, patients showed improved scores in different cognitive tests. However, data from randomized controlled trials remains scarce, and clinical evidence based on standardized metrics is still inconclusive. In light of recent meta-research developments in the neurofeedback field and beyond, quality and reporting practices of individual studies are reviewed. We conclude with recommendations on best practices for future studies that investigate the effects of neurofeedback training in dementia and cognitive impairment.

A Study on Resting EEG Effective Connectivity Difference before and after Neurofeedback for Children with ADHD

Altered functional networks in attention deficit/hyperactivity disorder (ADHD) have been frequently reported, but effective connectivity has hardly been studied. Especially the differences of effective connectivity in children with ADHD after receiving neurofeedback (NF) training have been merely reported. Therefore, this study aimed to explore the effective networks of ADHD and the positive influence of NF on the effective networks. Electroencephalogram (EEG) data were recorded from 22 children with ADHD (including data from children pretraining and posttraining) and 15 age-matched healthy controls during an eyes-closed resting state. Phase transfer entropy (PTE) was used to construct the effective connectivity. The topological properties of networks and flow gain were measured separately in four bands (delta, theta, alpha, and beta). Results revealed the following: pretraining children with ADHD manifested a higher clustering coefficient and lower characteristic path length in the delta band than healthy controls; weakened anterior-to-posterior flow gain in the delta band, strengthened posterior-to-anterior flow gain in the alpha band and strengthened anterior-to-posterior flow gain in the beta band were observed in pretraining children with ADHD; The topological properties and flow gain in posttraining children with ADHD were close to those of healthy controls. Moreover, parent's SWAN presented significant improvements of ADHD symptoms after NF. Our findings revealed that the effective connectivity of ADHD was altered and that NF could improve the brain function of ADHD. The present study provided the first evidence that children with ADHD differed from healthy children in phase-based effective connectivity and that NF could reduce the differences.