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Effects of SMR Neurofeedback on Cognitive Functions in an Adult Population with Sleep Problems: A Tele-neurofeedback Study

Kolken, Ylka, Bouny, Pierre, Arns, Martijn (2023) · Applied Psychophysiology and Biofeedback

A good night's sleep is vital for normal human cognitive performance. We earlier reported that a home-based tele-neurofeedback program effectively reduced sleep problems (Krepel et al. in Appl Psychophysiol Biofeedback, https://doi.org/10.1007/s10484-021-09525-z , 2021). The present article presents a follow-up on this earlier study and investigates improvements in cognitive functions after sensory-motor rhythm (SMR) neurofeedback. Thirty-seven participants reporting sleep problems received SMR neurofeedback. Cognitive measures were assessed pre- and post-treatment. Measurements included a continuous performance/working memory (CPT/WM) task, Stroop task, and Trailmaking A and B test (from the IntegNeuro cognitive test battery). For neurofeedback-Learners relative to non-Learners significantly improved CPT/WM response time (d = 0.50), omission errors (d = 0.67), and Stroop incongruent performance (d = 0.72) were found. A significant time effect for both groups were found for the Stroop, the Trailmaking test part B (d = 0.52), and the Stroop interference score (d = 0.55). No significant correlations between changes in sleep and changes in cognition (p > 0.05) were found for the sample. SMR neurofeedback specifically improved measures of attention (response time and omission errors in a CPT/WM test) and working memory (Stroop incongruent) for SMR Learners compared to non-Learners with medium effect sizes. Furthermore, overall improvements for the whole sample were found on measures of executive function and visual attention, possibly reflecting non-specific or practice effects. Future better powered randomized control trials are needed to investigate if cognitive improvements are a direct effect of SMR neurofeedback or mediated by sleep improvements.

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The Effectiveness of a Neurofeedback-Assisted Mindfulness Training Program Using a Mobile App on Stress Reduction in Employees: Randomized Controlled Trial

Min, Beomjun, Park, Heyeon, Kim, Johanna Inhyang, Lee, Sungmin, Back, Soyoung, Lee, Eunhwa, Oh, Sohee, Yun, Je-Yeon, Kim, Bung-Nyun, Kim, Yonghoon, Hwang, JungHyun, Lee, Sanghyop, Kim, Jeong-Hyun (2023) · JMIR mHealth and uHealth

BACKGROUND: Mindfulness-based training programs have consistently shown efficacy in stress reduction. However, questions regarding the optimal duration and most effective delivery methods remain. OBJECTIVE: This research explores a 4-week neurofeedback-assisted mindfulness training for employees via a mobile app. The study's core query is whether incorporating neurofeedback can amplify the benefits on stress reduction and related metrics compared with conventional mindfulness training. METHODS: A total of 92 full-time employees were randomized into 3 groups: group 1 received mobile mindfulness training with neurofeedback assistance (n=29, mean age 39.72 years); group 2 received mobile mindfulness training without neurofeedback (n=32, mean age 37.66 years); and group 3 were given self-learning paper materials on stress management during their first visit (n=31, mean age 38.65 years). The primary outcomes were perceived stress and resilience scales. The secondary outcomes were mindfulness awareness, emotional labor, occupational stress, insomnia, and depression. Heart rate variability and electroencephalography were measured for physiological outcomes. These measurements were collected at 3 different times, namely, at baseline, immediately after training, and at a 4-week follow-up. The generalized estimating equation model was used for data analysis. RESULTS: The 4-week program showed significant stress reduction (Wald χ22=107.167, P<.001) and improvements in psychological indices including resilience, emotional labor, insomnia, and depression. A significant interaction was observed in resilience (time × group, Wald χ42=10.846, P=.02). The post hoc analysis showed a statistically significant difference between groups 1 (least squares mean [LSM] 21.62, SE 0.55) and 3 (LSM 19.90, SE 0.61) at the posttraining assessment (P=.008). Group 1 showed a significant improvement (P<.001) at the posttraining assessment, with continued improvements through the 1-month follow-up assessment period (LSM 21.55, SE 0.61). Physiological indices were analyzed only for data of 67 participants (22 in group 1, 22 in group 2, and 23 in group 3) due to the data quality. The relaxation index (ratio of alpha to high beta power) from the right electroencephalography channel showed a significant interaction (time × group, Wald χ22=6.947, P=.03), with group 1 revealing the highest improvement (LSM 0.43, SE 0.15) compared with groups 2 (LSM -0.11, SE 0.10) and 3 (LSM 0.12, SE 0.10) at the 1-month follow-up assessment. CONCLUSIONS: The study demonstrated that the neurofeedback-assisted group achieved superior outcomes in resilience and relaxation during the 4-week mobile mindfulness program. Further research with larger samples and long-term follow-up is warranted. TRIAL REGISTRATION: ClinicalTrials.gov NCT03787407; https://clinicaltrials.gov/ct2/show/NCT03787407.

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A Randomized Controlled Trial Comparing Neurofeedback and Cognitive-Behavioral Therapy for Insomnia Patients: Pilot Study

Kwan, Yunna, Yoon, Soyoung, Suh, Sooyeon, Choi, Sungwon (2022) · Applied Psychophysiology and Biofeedback

Insomnia is a common disease that negatively affects patients both mentally and physically. While insomnia disorder is mainly characterized by hyperarousal, a few studies that have directly intervened with cortical arousal. This study was conducted to investigate the effect of a neurofeedback protocol for reducing cortical arousal on insomnia compared to cognitive-behavioral treatment for insomnia (CBT-I). Seventeen adults with insomnia, free of other psychiatric illnesses, were randomly assigned to neurofeedback or CBT-I. All participants completed questionnaires on insomnia [Insomnia Severity Index (ISI)], sleep quality [Pittsburgh Sleep Quality Index (PSQI)], and dysfunctional cognition [Dysfunctional Beliefs and Attitudes about Sleep Scale (DBAS-16)]. The neurofeedback group showed decreases in beta waves and increases in theta and alpha waves in various areas of the electroencephalogram (EEG), indicating lowered cortical arousal. The ISI and PSQI scores were significantly decreased, and sleep efficiency and sleep satisfaction were increased compared to the pre-treatment scores in both groups. DBAS scores decreased only in the CBT-I group (NF p = 0.173; CBT-I p = 0.012). This study confirmed that neurofeedback training could alleviate the symptoms of insomnia by reducing cortical hyperarousal in patients, despite the limited effect in reducing cognitive dysfunction compared to CBT-I.

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Automatized online prediction of slow-wave peaks during non-rapid eye movement sleep in young and old individuals: Why we should not always rely on amplitude thresholds

Wunderlin, Marina, Koenig, Thomas, Zeller, Céline, Nissen, Christoph, Züst, Marc Alain (2022) · Journal of Sleep Research

Brain-state-dependent stimulation during slow-wave sleep is a promising tool for the treatment of psychiatric and neurodegenerative diseases. A widely used slow-wave prediction algorithm required for brain-state-dependent stimulation is based on a specific amplitude threshold in the electroencephalogram. However, due to decreased slow-wave amplitudes in aging and psychiatric conditions, this approach might miss many slow-waves because they do not fulfill the amplitude criterion. Here, we compared slow-wave peaks predicted via an amplitude-based versus a multidimensional approach using a topographical template of slow-wave peaks in 21 young and 21 older healthy adults. We validate predictions against the gold-standard of offline detected peaks. Multidimensionally predicted peaks resemble the gold-standard regarding spatiotemporal dynamics but exhibit lower peak amplitudes. Amplitude-based prediction, by contrast, is less sensitive, less precise and - especially in the older group - predicts peaks that differ from the gold-standard regarding spatiotemporal dynamics. Our results suggest that amplitude-based slow-wave peak prediction might not always be the ideal choice. This is particularly the case in populations with reduced slow-wave amplitudes, like older adults or psychiatric patients. We recommend the use of multidimensional prediction, especially in studies targeted at populations other than young and healthy individuals.

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Evaluation of the URGOnight Tele-neurofeedback Device: An Open-label Feasibility Study with Follow-up

Krepel, Noralie, Egtberts, Tommy, Touré-Cuq, Emma, Bouny, Pierre, Arns, Martijn (2022) · Applied Psychophysiology and Biofeedback

SMR neurofeedback shows potential as a therapeutic tool for reducing sleep problems. It is hypothesized that SMR neurofeedback trains the reticulo-thalamocortical-cortical circuit involved in sleep-spindle generation. As such, strengthening this circuit is hypothesized to reduce sleep problems. The current study aims to investigate the effectiveness of a home-based device that uses SMR neurofeedback to help reduce sleep problems. Thirty-seven participants reporting sleep problems received the SMR neurofeedback-based program for 40 (n = 21) or 60 (n = 16) sessions. The Pittsburgh Sleep Quality Index (PSQI) and Holland Sleep Disorders Questionnaire (HSDQ) were assessed at baseline, session 20, outtake, and follow-up (FU). Actigraphy measurements were taken at baseline, session 20, and outtake. Significant improvements were observed in PSQI Total (d = 0.78), PSQI Sleep Duration (d = 0.52), HSDQ Total (d = 0.80), and HSDQ Insomnia (d = 0.79). Sleep duration (based on PSQI) increased from 5.3 h at baseline to 5.8 after treatment and 6.0 h. at FU. No effects of number of sessions were found. Participants qualified as successful SMR-learners demonstrated a significantly larger gain in sleep duration (d = 0.86 pre-post; average gain = 1.0 h.) compared to non-learners. The home-based SMR tele-neurofeedback device shows the potential to effectively reduce sleep problems, with SMR-learners demonstrating significantly better improvement. Although randomized controlled trials (RCTs) are needed to further elucidate the specific effect of this device on sleep problems, this is the first home-based SMR neurofeedback device using dry electrodes demonstrating effectiveness and feasibility.

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Functional connectome mediates the association between sleep disturbance and mental health in preadolescence: A longitudinal mediation study

Yang, Fan Nils, Liu, Tina Tong, Wang, Ze (2022) · Human Brain Mapping

Sleep disturbance is known to be associated with various mental disorders and often precedes the onset of mental disorders in youth. Given the increasingly acknowledged bidirectional influence between sleep disturbance and mental disorders, we aim to identify a shared neural mechanism that underlies sleep disturbance and mental disorders in preadolescents. We analyzed a dataset of 9,350 9-10 year-old children, among whom 8,845 had 1-year follow-up data, from the Adolescent Brain Cognitive Development (ABCD) study. Linear mixed-effects models, mediation analysis, and longitudinal mediation analysis were used to investigate the relationship between sleep disturbance, mental disorders, and resting-state network connectivity. Out of 186 unique connectivities, the effect of total sleep disturbance (TSP, from Sleep Disturbance Scale) and mental problems (MP, from Child Behavior Checklist) converged in the default mode network (DMN) and the dorsal attention network (DAN). Within- and between-network connectivities (DMN-DAN, DMN-DMN, DAN-DAN) mediated the relationship between baseline TSD and MP at 1-year follow-up and the relationship between baseline MP and TSD at 1-year follow-up. The pathway model in which sleep disturbance and mental problems affect each other through two anticorrelated brain networks (DMN and DAN) suggests a common neural mechanism between them. Longitudinally, a less segregated DMN and DAN is associated with negative outcomes on mental well-being and sleep disturbance a year later. These findings have important implications for the design of prevention and neurofeedback intervention for mental disorders and sleep problems.

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