Sleep Wake Disorders
Research Papers
Effects of SMR Neurofeedback on Cognitive Functions in an Adult Population with Sleep Problems: A Tele-neurofeedback Study
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.
View Full Paper →Functional connectome mediates the association between sleep disturbance and mental health in preadolescence: A longitudinal mediation study
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.
View Full Paper →Volitional limbic neuromodulation exerts a beneficial clinical effect on Fibromyalgia
Volitional neural modulation using neurofeedback has been indicated as a potential treatment for chronic conditions that involve peripheral and central neural dysregulation. Here we utilized neurofeedback in patients suffering from Fibromyalgia - a chronic pain syndrome that involves sleep disturbance and emotion dysregulation. These ancillary symptoms, which have an amplificating effect on pain, are known to be mediated by heightened limbic activity. In order to reliably probe limbic activity in a scalable manner fit for EEG-neurofeedback training, we utilized an Electrical Finger Print (EFP) model of amygdala-BOLD signal (termed Amyg-EFP), that has been successfully validated in our lab in the context of volitional neuromodulation. We anticipated that Amyg-EFP-neurofeedback training aimed at limbic down modulation would improve chronic pain in patients suffering from Fibromyalgia, by reducing sleep disorder improving emotion regulation. We further expected that improved clinical status would correspond with successful training as indicated by improved down modulation of the Amygdala-EFP signal. Thirty-Four Fibromyalgia patients (31F; age 35.6 ± 11.82) participated in a randomized placebo-controlled trial with biweekly Amyg-EFP-neurofeedback sessions or sham neurofeedback (n = 9) for a total duration of five consecutive weeks. Following training, participants in the real-neurofeedback group were divided into good (n = 13) or poor (n = 12) modulators according to their success in the neurofeedback training. Before and after treatment, self-reports on pain, depression, anxiety, fatigue and sleep quality were obtained, as well as objective sleep indices. Long-term clinical follow-up was made available, within up to three years of the neurofeedback training completion. REM latency and objective sleep quality index were robustly improved following the treatment course only in the real-neurofeedback group (time × group p < 0.05) and to a greater extent among good modulators (time × sub-group p < 0.05). In contrast, self-report measures did not reveal a treatment-specific response at the end of the neurofeedback training. However, the follow-up assessment revealed a delayed improvement in chronic pain and subjective sleep experience, evident only in the real-neurofeedback group (time × group p < 0.05). Moderation analysis showed that the enduring clinical effects on pain evident in the follow-up assessment were predicted by the immediate improvements following training in objective sleep and subjective affect measures. Our findings suggest that Amyg-EFP-neurofeedback that specifically targets limbic activity down modulation offers a successful principled approach for volitional EEG based neuromodulation treatment in Fibromyalgia patients. Importantly, it seems that via its immediate sleep improving effect, the neurofeedback training induced a delayed reduction in the target subjective symptom of chronic pain, far and beyond the immediate placebo effect. This indirect approach to chronic pain management reflects the substantial link between somatic and affective dysregulation that can be successfully targeted using neurofeedback.
View Full Paper →The effect of EEG biofeedback on reducing postcancer cognitive impairment
BACKGROUND AND HYPOTHESES: Postcancer cognitive impairment (PCCI) is observed in a substantial number of breast cancer survivors, persisting for as long as 20 years in some subgroups. Although compensatory strategies are frequently suggested, no restorative interventions have yet been identified. This study examined the feasibility of EEG biofeedback ("neurofeedback") and its potential effectiveness in reducing PCCI as well as the fatigue, sleep disturbance, and psychological symptoms that frequently accompany PCCI. STUDY DESIGN: This was a 6-month prospective study with a waitlist control period followed by an active intervention. Participants were female breast cancer survivors (n = 23), 6 to 60 months postchemotherapy, with self-reported cognitive impairment. METHODS: Four self-report outcome measures (Functional Assessment of Cancer Therapy-Cognitive Function [FACT-Cog], Functional Assessment of Chronic Illness Therapy-Fatigue [FACIT-Fatigue], Pittsburgh Sleep Quality Index [PSQI], and Brief Symptom Inventory [BSI]-18) were administered 3 times during a 10-week waitlist control period, 3 times during a 10-week (20-session) neurofeedback training regimen, and once at 4 weeks postneurofeedback. RESULTS: All 23 participants completed the study, demonstrating the feasibility of EEG biofeedback in this population. Initially, the sample demonstrated significant dysfunction on all measures compared with general population norms. Repeated-measures ANOVAs revealed strongly significant improvements (P < .001) on all 4 cognitive measures (perceived cognitive impairment, comments from others, perceived cognitive abilities, and impact on quality of life [QOL]), the fatigue scale, and the 4 psychological scales (somatization, depression, anxiety and global severity index) as well as on 3 of 8 sleep scales (quality, daytime dysfunction, and global). Two of the other sleep scales (latency and disturbance) were significant at P < .01, and 1 (use of medication) at P < .05; 2 were not significant. Improvements were generally linear across the course of training, and were maintained at the follow-up testing. At the follow-up testing, the sample no longer differed significantly from normative populations on 3 of the 4 FACT-Cog measures (impairment, impact on QOL, and comments), FACIT-Fatigue, PSQI sleep quality and habitual efficiency, or any of the BSI-18 measures of psychological disturbance. CONCLUSIONS: Data from this limited study suggest that EEG biofeedback has potential for reducing the negative cognitive and emotional sequelae of cancer treatment as well as improving fatigue and sleep patterns.
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