Arns, M., Kenemans, JL. (2012). Neurofeedback in ADHD and insomnia: Vigilance stabilization through sleep spindles and circadian networks. Neuroscience Biobehavioral Review.
In this review article an overview of the history and current status of neurofeedback for the treatment of ADHD and insomnia is provided. Recent insights suggest a central role of circadian phase delay, resulting in sleep onset insomnia (SOI) in a sub-group of ADHD patients. Chronobiological treatments, such as melatonin and early morning bright light, affect the suprachiasmatic nucleus. This nucleus has been shown to project to the noradrenergic locus coeruleus (LC) thereby explaining the vigilance stabilizing effects of such treatments in ADHD. It is hypothesized that both Sensori-Motor Rhythm (SMR) and Slow-Cortical Potential (SCP) neurofeedback impact on the sleep spindle circuitry resulting in increased sleep spindle density, normalization of SOI and thereby affect the noradrenergic LC, resulting in vigilance stabilization. After SOI is normalized, improvements on ADHD symptoms will occur with a delayed onset of effect. Therefore, clinical trials investigating new treatments in ADHD should include assessments at follow-up as their primary endpoint rather than assessments at outtake. Furthermore, an implication requiring further study is that neurofeedback could be stopped when SOI is normalized, which might result in fewer sessions.
Bell, J. S. (1979). The use of EEG theta biofeedback in the treatment of a patient with sleep-onset insomnia. Biofeedback & Self Regulation , 4(3), 229-236.
In this report, the treatment of a 42-year-old female with a complaint of chronic sleep-onset insomnia is described. Following the unsuccessful use of relaxation training, treatment consisted of 11 sessions of EEG theta rhythm (4--7 Hz) biofeedback. Theta density and five sleepindices were monitored throughout baseline, placebo, and treatment sessions. A significant increase in theta density was accompanied by reports of a decrease in sleep latency and an increase in total sleep time. This improvement was maintained after withdrawal of medication and at 3-month follow-up.
Coursey RD, Frankel BL, Gaarder KR, Mott DE. (1980). A comparison of relaxation techniques with electrosleep therapy for chronic, sleep-onset insomnia a sleep EEG study. Biofeedback and Self-Regulation. Mar;5(1):57-73.
Two methods of relaxation therapy, electromyograph biofeedback and autogenic training, were compared to a nonrelaxation treatment, electrosleep therapy, in reducing sleep latency among 22 chronic, sleep-onset insomniacs. While none of the electrosleep patients improved on all-night laboratory electroencephalographic sleep records or daily home sleep logs, approximately one-halfof the relaxation-treated patients showed marked improvement, which was sustained over a 1-month follow-up period. Although some sleep and treatment variables differentiated relaxation therapy responders from nonresponders, external stress appeared to be the most salient factor. Successful and unsuccessful patients could not be differentiated on any of the psychological variables studied.
Hammer, BU., Colbert, AP., Brown, KA., Llioi, EC. (2011). Neurofeedback for insomnia: a pilot study of Z-score SMR and individualized protocols. Applied Psychophysiology and Biofeedback, 36(4): 251-264.
Insomnia is an epidemic in the US. Neurofeedback (NFB) is a little used, psychophysiological treatment with demonstrated usefulness for treating insomnia. Our objective was to assess whether two distinct Z-Score NFB protocols, a modified sensorimotor (SMR) protocol and a sequential, quantitative EEG (sQEEG)-guided, individually designed (IND) protocol, would alleviate sleep and associated daytime dysfunctions of participants with insomnia. Both protocols used instantaneous Z scores to determine reward condition administered when awake. Twelve adults with insomnia, free of other mental and uncontrolled physical illnesses, were randomly assigned to the SMR or IND group. Eight completed this randomized, parallel group, single-blind study. Both groups received fifteen 20-min sessions of Z-Score NFB. Pre-post assessments included sQEEG, mental health, quality of life, and insomnia status. ANOVA yielded significant post-treatment improvement for the combined group on all primary insomnia scores: Insomnia Severity Index (ISI p<.005), Pittsburgh Sleep Quality Inventory (PSQI p<.0001), PSQI Sleep Efficiency (p<.007), and Quality of Life Inventory (p<.02). Binomial tests of baseline EEGs indicated a significant proportion of excessively high levels of Delta and Beta power (p<.001) which were lowered post-treatment (paired z tests p<.001). Baseline EEGs showed excessive sleepiness and hyperarousal, which improved post-treatment. Both ZScore NFB groups improved in sleep and daytime functioning. Post-treatment, all participants were normal sleepers. Because there were no significant differences in the findings between the two groups, our future large scale studies will utilize the less burdensome to administer Z-Score SMR protocol.
Kinreich, S., Podipsky, I., Jamshy, S., Intrator, N. & Hendler, T. (2014). Neural dynamics necessary and sufficient for transition into pre-sleep induced by EEG neurofeedback. NeuroImage: Aug15(97). 19-28.
The transition from being fully awake to pre-sleep occurs daily just before falling asleep; thus its disturbance might be detrimental. Yet, the neuronal correlates of the transition remain unclear, mainly due to the difficulty in capturing its inherent dynamics. We used an EEG theta/alpha neurofeedback to rapidly induce the transition into pre-sleep and simultaneous fMRI to reveal state-dependent neural activity. The relaxed mental state was verified by the corresponding enhancement in the parasympathetic response. Neurofeedback sessions were categorized as successful or unsuccessful, based on the known EEG signature of theta power increases over alpha, temporally marked as a distinct "crossover" point. The fMRI activation was considered before and after this point. During successful transition into pre-sleep the period before the crossover was signified by alpha modulation that corresponded to decreased fMRI activity mainly in sensory gating related regions (e.g. medial thalamus). In parallel, although not sufficient for the transition, theta modulation corresponded with increased activity in limbic and autonomic control regions (e.g. hippocampus, cerebellum vermis, respectively). The post-crossover period was designated by alpha modulation further corresponding to reduced fMRI activity within the anterior salience network (e.g. anterior cingulate cortex, anterior insula), and in contrast theta modulation corresponded to the increased variance in the posterior salience network (e.g. posterior insula, posterior cingulate cortex). Our findings portray multi -level neural dynamics underlying the mental transition from awake to pre-sleep. To initiate the transition, decreased activity was required in external monitoring regions, and to sustain the transition, opposition between the anterior and posterior parts of the salience network was needed, reflecting shifting from extra- to intrapersonal based processing,respectively.
Reiner, M., Rozengurt, R. & Barnea, A. (2014). Better than sleep: Theta neurofeedback training accelerates memory consolidation. Biological Psychology:Jan;95(45). 45-53.
Consistent empirical results showed that both night and day sleep enhanced memory consolidation. In this study we explore processes of consolidation of memory during awake hours. Since theta oscillations have been shown to play a central role in exchange of information, we hypothesized that elevated theta during awake hours will enhance memory consolidation. We used a neurofeedback protocol, to enhance the relative power of theta or beta oscillations. Participants trained on a tapping task, were divided into three groups: neurofeedback theta; neurofeedback beta; control. We found a significant improvement in performance in the theta group, relative to the beta and control groups, immediately after neurofeedback. Performance was further improved after night sleep in all groups, with a significant advantage favouring the theta group. Theta power during training was correlated with the level of improvement, indicating a clear relationship between memory consolidation, and theta neurofeedback.
Schabus, M., Heib DP., Lechinger J., Griessenberger H., Klimesch W., Pawlizki A., Kunz AB., Sterman BM. & Hoedlmoser K. (2014). Enhancing sleep quality and memory in insomnia using instrumental sensorimotor rhythm conditioning. Biological Psychology Jan;95. 126-134.
EEG recordings over the sensorimotor cortex show a prominent oscillatory pattern in a frequency range between 12 and 15 Hz (sensorimotor rhythm, SMR) under quiet but alert wakefulness. This frequency range is also abundant during sleep, and overlaps with the sleep spindle frequency band. In the present pilot study we tested whether instrumental conditioning of SMR during wakefulness can enhance sleep and cognitive performance in insomnia. Twenty -four subjects with clinical symptoms of primary insomnia were tested in a counterbalanced within-subjects-design. Each patient participated in a SMR- as well as a sham-conditioning training block. Polysomnographic sleep recordings were scheduled before and after the training blocks. Results indicate a significant increase of 12-15 Hz activity over the course of ten SMR training sessions. Concomitantly, the number of awakenings decreased and slow-wave sleep as well as subjective sleep quality increased. Interestingly, SMR training enhancement was also found to be associated with overnight memory consolidation and sleep spindle changes indicating a beneficial cognitive effect of the SMR training protocol for SMR "responders" (16 out of 24 participants). Although results are promising it has to be concluded that current results are of a preliminary nature and await further proof before SMR-training can be promoted as a non pharmacological approach for improving sleep quality and memory performance.
Sterman, MB., Shouse, MN. (1980). Quantitative analysis of training, sleep EEG and clinical response to EEG operant conditioning in epileptics. Electroencephalography and Clinical Neurophysiology, 49(5-6): 558-579. This report is a follow-up to a previous paper which described seizure rate changes with central cortical EEG feedback training in 8 poorly controlled epileptic subjects. Data examined here include associated training compliance and performance, sleep EEG spectra, clinical EEG and anticonvulsant blood levels. The study employed a double cross-over, single blind ABA design applied to two subgroups of epileptic patients. Both groups had in common two training periods (A1,A2) in which either 12--15 c/sec (subgroup I, n = 4) or 18--23 c/sec (subgroup II, n = 4) was reinforced in the absence of 6--9 c/sec, movement or epileptiform discharge, and one training period (B) in which 6--9 c/sec was reinforced in the absence of 12--15 or 18--23 c/sec as well as movement and epileptiform discharge. Training periods occurred primarily in the home and lasted 3 months. Compliance with training instructions and response acquisition were demonstrated. Overall anticonvulsant blood levels were low and unrelated to EEG or seizure changes. Clinical EEG findings corresponded to sleep EEG and seizure rate outcomes. Power spectral analysis of sampled non-REM sleep from all-night EEG recordings obtained after each training phase indicated contingency specific changes which were limited to sensorimotor recordings in subgroup I and corresponded to the pattern of seizure rate changes in this group. EEG changes were also limited to sensorimotor cortex in subgroup II, but were linear and paralleled a progressive decrease in seizure rate. Both groups, however, showed the same pattern of EEG changes with seizure reductions; low and high frequencies were reduced and intermediate, rhythmic frequencies increased. Correlational analysis confirmed this relationship. The pattern, duration and topographic specificity of these changes suggested a normalization of sensorimotor EEG substrates related to the EEG feedback training.
​
Arns, M., Kenemans, JL. (2012). Neurofeedback in ADHD and insomnia: Vigilance stabilization through sleep spindles and circadian networks. Neuroscience Biobehavioral Review. In this review article an overview of the history and current status of neurofeedback for the treatment of ADHD and insomnia is provided. Recent insights suggest a central role of circadian phase delay, resulting in sleep onset insomnia (SOI) in a sub- group of ADHD patients. Chronobiological treatments, such as melatonin and early morning bright light, affect the suprachiasmatic nucleus. This nucleus has been shown to project to the noradrenergic locus coeruleus (LC) thereby explaining the vigilance stabilizing effects of such treatments in ADHD. It is hypothesized that both Sensori-Motor Rhythm (SMR) and Slow-Cortical Potential (SCP) neurofeedback impact on the sleep spindle circuitry resulting in increased sleep spindle density, normalization of SOI and thereby affect the noradrenergic LC, resulting in vigilance stabilization. After SOI is normalized, improvements on ADHD symptoms will occur with a delayed onset of effect. Therefore, clinical trials investigating new treatments in ADHD should include assessments at follow-up as their primary endpoint rather than assessments at outtake. Furthermore, an implication requiring further study is that neurofeedback could be stopped when SOI is normalized, which might result in fewer sessions.
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Berner, I., Schabus, M., Wienerroither, T., & Klimesch, W. (2006). The significance of Sigma neurofeedback Training on Sleep spindles and aspects of declarative memory. Applied Psychophysiology & Biofeedback, 31(2), 97-114. The functional significance of sleep spindles for overnight memory consolidation and general learning aptitude as well as the effect of four 10-minute sessions of spindle frequency (11.6-16 Hz, sigma) neurofeedback-training on subsequent sleep spindle activity and overnight performance change was investigated. Before sleep, subjects were trained on a paired-associate word list task after having received either neurofeedback training (NFT) or pseudofeedback training (PFT). Although NFT had no significant impact on subsequent spindle activity and behavioral outcomes, there was a trend for enhanced sigma band-power during NREM (stage 2 to 4) sleep after NFT as compared to PFT. Furthermore, a significant positive correlation between spindle activity during slow wave sleep (in the first night half) and overall memory performance was revealed. The results support the view that the considerable inter- individual variance in sleep spindle activity can at least be partly explained by differences in the ability to acquire new declarative information. We conclude that the short NFT before sleep was not sufficient to efficiently enhance phasic spindle activity and/or to influence memory processing. NFT was, however, successful in increasing sigma power, presumably because sigma NFT effects become more easily evident in actually trained frequency bands than in associated phasic spindle activity.
Hammer, BU., Colbert, AP., Brown, KA., Llioi, EC. (2011). Neurofeedback for insomnia: a pilot study of Z-score SMR and individualized protocols. Applied Psychophysiology and Biofeedback, 36(4): 251-264. Insomnia is an epidemic in the US. Neurofeedback (NFB) is a little used, psychophysiological treatment with demonstrated usefulness for treating insomnia. Our objective was to assess whether two distinct Z-Score NFB protocols, a modified sensorimotor (SMR) protocol and a sequential, quantitative EEG (sQEEG)-guided, individually designed (IND) protocol, would alleviate sleep and associated daytime dysfunctions of participants with insomnia. Both protocols used instantaneous Z scores to determine reward condition administered when awake. Twelve adults with insomnia, free of other mental and uncontrolled physical illnesses, were randomly assigned to the SMR or IND group. Eight completed this randomized, parallel group, single-blind study. Both groups received fifteen 20-min sessions of Z-Score NFB. Pre-post assessments included sQEEG, mental health, quality of life, and insomnia status. ANOVA yielded significant post-treatment improvement for the combined group on all primary insomnia scores: Insomnia Severity Index (ISI p<.005), Pittsburgh Sleep Quality Inventory (PSQI p<.0001), PSQI Sleep Efficiency (p<.007), and Quality of Life Inventory (p<.02). Binomial tests of baseline EEGs indicated a significant proportion of excessively high levels of Delta and Beta power (p<.001) which were lowered post-treatment (paired z-tests p<.001). Baseline EEGs showed excessive sleepiness and hyperarousal, which improved post-treatment. Both Z- Score NFB groups improved in sleep and daytime functioning. Post- treatment, all participants were normal sleepers. Because there were no significant differences in the findings between the two groups, our future large scale studies will utilize the less burdensome to administer Z-Score SMR protocol.
​
Reiner, M., Rozengurt, R. & Barnea, A. (2014). Better than sleep: Theta neurofeedback training accelerates memory consolidation. Biological Psychology:Jan;95(45). 45-53. Consistent empirical results showed that both night and day sleep enhanced memory consolidation. In this study we explore processes of consolidation of memory during awake hours. Since theta oscillations have been shown to play a central role in exchange of information, we hypothesized that elevated theta during awake hours will enhance memory consolidation. We used a neurofeedback protocol, to enhance the relative power of theta or beta oscillations. Participants trained on a tapping task, were divided into three groups: neurofeedback theta; neurofeedback beta; control. We found a significant improvement in performance in the theta group, relative to the beta and control groups, immediately after neurofeedback. Performance was further improved after night sleep in all groups, with a significant advantage favoring the theta group. Theta power during training was correlated with the level of improvement, indicating a clear relationship between memory consolidation, and theta neurofeedback.
​
Schabus, M., Heib DP., Lechinger J., Griessenberger H., Klimesch W., Pawlizki A., Kunz AB., Sterman BM. & Hoedlmoser K. (2014). Enhancing sleep quality and memory in insomnia using instrumental sensorimotor rhythm conditioning. Biological Psychology Jan;95. 126-134. EEG recordings over the sensorimotor cortex show a prominent oscillatory pattern in a frequency range between 12 and 15 Hz (sensorimotor rhythm, SMR) under quiet but alert wakefulness. This frequency range is also abundant during sleep, and overlaps with the sleep spindle frequency band. In the present pilot study we tested whether instrumental conditioning of SMR during wakefulness can enhance sleep and cognitive performance in insomnia. Twenty-four subjects with clinical symptoms of primary insomnia were tested in a counterbalanced within-subjects-design. Each patient participated in a SMR- as well as a sham-conditioning training block. Polysomnographic sleep recordings were scheduled before and after the training blocks. Results indicate a significant increase of 12-15 Hz activity over the course of ten SMR training sessions. Concomitantly, the number of awakenings decreased and slow-wave sleep as well as subjective sleep quality increased. Interestingly, SMR- training enhancement was also found to be associated with overnight memory consolidation and sleep spindle changes indicating a beneficial cognitive effect of the SMR training protocol for SMR “responders” (16 out of 24 participants). Although results are promising it has to be concluded that current results are of a preliminary nature and await further proof before SMR- training can be promoted as a non- pharmacological approach for improving sleep quality and memory performance.
Sterman, MB., Shouse, MN. (1980). Quantitative analysis of training, sleep EEG and clinical response to EEG operant conditioning in epileptics. Electroencephalography and Clinical Neurophysiology, 49(5-6): 558-579. This report is a follow-up to a previous paper which described seizure rate changes with central cortical EEG feedback training in 8 poorly controlled epileptic subjects. Data examined here include associated training compliance and performance, sleep EEG spectra, clinical EEG and anticonvulsant blood levels. The study employed a double-cross- over, single blind ABA design applied to two subgroups of epileptic patients. Both groups had in common two training periods (A1, A2) in which either 12–15 c/sec (subgroup I, n = 4) or 18–23 c/sec (subgroup II, n = 4) was reinforced in the absence of 6–9 c/sec, movement or epileptiform discharge, and one training period (B) in which 6–9 c/sec was reinforced in the absence of 12–15 or 18–23 c/sec as well as movement and epileptiform discharge. Training periods occurred primarily in the home and lasted 3 months. Compliance with training instructions and response acquisition were demonstrated. Overall anticonvulsant blood levels were low and unrelated to EEG or seizure changes. Clinical EEG findings corresponded to sleep EEG and seizure rate outcomes. Power spectral analysis of sampled non-REM sleep from all-night EEG recordings obtained after each training phase indicated contingency specific changes which were limited to sensorimotor recordings in subgroup I and corresponded to the pattern of seizure rate changes in this group. EEG changes were also limited to sensorimotor cortex in subgroup II, but were linear and paralleled a progressive decrease in seizure rate. Both groups, however, showed the same pattern of EEG changes with seizure reductions; low and high frequencies were reduced and intermediate, rhythmic frequencies increased. Correlational analysis confirmed this relationship. The pattern, duration and topographic specificity of these changes suggested a normalization of sensorimotor EEG substrates related to the EEG feedback training.