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Enhancing sleep quality and memory in insomnia using instrumental sensorimotor rhythm conditioning
Abstract
EEG recordings over the sensorimotor cortex show a prominent oscillatory pattern in a frequency range between 12-15Hz (sensorimotor rhythm, SMR) under quiet but alert wakefulness. This frequency range is also abundant during sleep, and is overlapping 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 12-15Hz activity over the course of ten SMR training sessions. Concomitant 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 preliminary nature and await further proof before SMR-training can be promoted as non-pharmacological approach for improving sleep quality and memory performance.
... Most controlled neurofeedback studies have followed the between-subject control approach: participants in an experimental group are provided with a neurofeedback signal based on neuronal activity of interest (active neurofeedback), while participants in a control group are provided, without their knowledge, with a sham (neuro)feedback signal, unrelated to that activity (e.g., Chiasson et al. 2023). A promising alternative is the within-subject control approach: each participant undergoes equal numbers of training runs with an active neurofeedback and a sham (neuro)feedback, and the order of such runs is randomized across all participants (Schabus et al. 2014;Zotev et al. 2024). Implementation of this approach in what we refer to as counterbalanced active-sham study design makes it possible to directly compare the effects of an active neurofeedback to those of a sham (neuro)feedback for each participant within the same imaging session. ...
... The counterbalanced active-sham design was originally used by Schabus and colleagues in their EEG-nf study targeting sensorimotor EEG rhythm for treatment of insomnia (Schabus et al. 2014). The study included 10 training sessions with the active EEG-nf, counterbalanced with 5 sessions with a pseudofeedback (Schabus et al. 2014). ...
... The counterbalanced active-sham design was originally used by Schabus and colleagues in their EEG-nf study targeting sensorimotor EEG rhythm for treatment of insomnia (Schabus et al. 2014). The study included 10 training sessions with the active EEG-nf, counterbalanced with 5 sessions with a pseudofeedback (Schabus et al. 2014). Recently, we reported the first study in which this approach was used to control a rtfMRI-nf procedure (Zotev et al. 2024). ...
Evaluation of mechanisms of action of EEG neurofeedback (EEG‐nf) using simultaneous fMRI is highly desirable to ensure its effective application for clinical rehabilitation and therapy. Counterbalancing training runs with active neurofeedback and sham (neuro)feedback for each participant is a promising approach to demonstrate specificity of training effects to the active neurofeedback. We report the first study in which EEG‐nf procedure is both evaluated using simultaneous fMRI and controlled via the counterbalanced active‐sham study design. Healthy volunteers (n = 18) used EEG‐nf to upregulate frontal theta EEG asymmetry (FTA) during fMRI while performing tasks that involved mental generation of a random numerical sequence and serial summation of numbers in the sequence. The FTA was defined as power asymmetry for channels F3 and F4 in [4–7] Hz band. Sham feedback was provided based on asymmetry of motion‐related artifacts. The experimental procedure included two training runs with the active EEG‐nf and two training runs with the sham feedback, in a randomized order. The participants showed significantly more positive FTA changes during the active EEG‐nf conditions compared to the sham conditions, associated with significantly higher theta EEG power changes for channel F3. Temporal correlations between the FTA and fMRI activities of prefrontal, parietal, and occipital brain regions were significantly enhanced during the active EEG‐nf conditions compared to the sham conditions. Temporal correlation between theta EEG power for channel F3 and fMRI activity of the left dorsolateral prefrontal cortex (DLPFC) was also significantly enhanced. Significant active‐vs‐sham difference in fMRI activations was observed for the left DLPFC. Our results demonstrate that mechanisms of EEG‐nf training can be reliably evaluated using the counterbalanced active‐sham study design and simultaneous fMRI.
... Another single-blind RCT used sham E-NFT as a placebo-controlled condition in insomnia patients [54]. During sham E-NFT, five random frequency bands in the beta range except for SMR frequencies were used as rewarded frequency bands. ...
... No sleep improvements were found after the SMR as compared to sham neurofeedback sessions. Only a significant improvement after both SMR and sham E-NFT was found on sleep quality and physical quality of life, irrespective of type of E-NFT, which is in line with the results of Schabus et al. [54]. No difference after E-NFT was found for other sleep parameters measured with PSG and questionnaires. ...
... Also no relationship between more relaxed and less tense insomnia patients and better objective sleep quality after specifically SMR E-NFT was found. Lastly, SMR power was enhanced within the neurofeedback sessions across all 12 sessions, but was not higher after E-NFT as compared to before E-NFT as in contrast to Schabus et al. [54]. Absence of increased SMR power after SMR E-NFT was also found in healthy young adults that received the same E-NFT protocol, and is therefore probably not due to learning impairments that can be found in insomnia patients because of their disease. ...
Electroencephalography-Neurofeedbacktraining (E-NFT) is a method to support subjects in learning to self-regulate their own brain activity. Besides that E-NFT may improve cognitive functions in healthy people, it may improve symptoms in different disorders, such as Attention Deficit and Hyperactivity Disorder (ADHD) and insomnia. The evidence of E-NFT for the treatment of attention problems in ADHD is still under debate, just as the suggested efficacy of E-NFT for reducing sleep problems in individuals suffering from insomnia and for improving attention and sleep in the general population. Therefore, this review examines the efficacy of E-NFT on attention and sleep in patients and healthy individuals. The reviewed literature provides evidence that standard E-NFT protocols may have a positive long-lasting effect on the inattention and hyperactivity/impulsivity symptoms in children with ADHD. In healthy children and young adults, E-NFT has been found to improve different aspects of attention and to reduce impulsivity. In addition, positive effects of E-NFT have been documented on sleep onset latency and on tiredness in healthy individuals. Sleep improvements have also been found in insomnia patients after standard E-NFT, although these subjective sleep improvements may likely depend on unspecific E-NFT training effects.
... NFS is a type of closed-loop NF that uses only two to four electrodes and targets a reduced number of cortical regions as well as a reduced number of brainwaves [40]. During NFS, the client will be presented with his/her own EEG activity, at a specific region, in the form of visual and/or auditory stimuli. ...
... The main difference is that the LZT is not based on the power spectral analysis of specific brain waves but on its comparison to the population average. To do this, EEG activity is compared in real time to a normative database that accounts for age, gender and handedness to provide a score (Z-score) representing the position of the client related to the population average [40,52]. The purpose of LZT is to bring this score closer to the population average (Z = 0). ...
... At initial assessment, all participants had higher absolute power for high-beta (21-34 Hz) and gamma waves (35)(36)(37)(38)(39)(40)(41)(42)(43)(44)(45) Hz) than the database. After the experimental session, participants in the AVE group had a significant increase in the absolute power of delta waves on all 19 EEG channels, while participants of the placebo group had no significant EEG power change in any band frequency. ...
Background:
Chronic insomnia affects about 6%-13% of the Canadian population. Although treatments already exist, they each have their own issues. Neurofeedback is a neuromodulation technique that specifically targets abnormal brain activity and is gaining attention as a possible insomnia treatment.
Aim:
To review the latest studies pertaining to the use of neurofeedback in the treatment of insomnia.
Methods:
In this non-systematic review, only experimental studies assessing the effects of neurofeedback on patients with insomnia were targeted across four bibliographic databases.
Results:
A total of 12 studies were retained. All neurofeedback studies included in this study showed a clear improvement of subjective sleep. However, data concerning objective improvement are contradictory. Most studies regarding surface and z-score neurofeedback show that neurofeedback targeting the sensorimotor rhythm in the sensorimotor cortex may help improve subjective sleep. A placebo effect seems also to be present in some studies. Several limitations were present in each study.
Conclusion:
While studies concerning neurofeedback as a treatment for insomnia are encouraging, many methodological barriers remain to be resolved to prove its efficacy unequivocally. More studies using robust design parameters, as well as the replication of existing studies, are necessary to support neurofeedback as an effective treatment for insomnia.
... Attention is a brain function related to the capacity of concentration in a particular task or selection of specific elements of external or internal stimuli (Raz & Buhle, 2006). Apart from attention training, previous studies also reported improvement on working memory; WM (Nan et al., 2012;Vernon et al., 2003;Wang & Hsieh, 2013), mood (Raymond et al., 2005), executive functions (Enriquez-Geppert et al., 2013), and sleep quality (Schabus et al., 2014). On the other hand, the evaluation of the efficacy of NFT to improve microsurgical skills was only conducted by the study of Ros et al. (2009) which provided SMR-Theta neurofeedback training on 20 healthy microsurgeons. ...
... Despite showing changes in EEG signals and behavioral tests, these studies present limited samples that prevent statistically significant sleep quality results. This data contradicts the study of Schabus et al. (2014) on adults that found a significant increase of subjective sleep quality (12-15 Hz) activity and slow-wave sleep over ten sessions. The study of Schabus et al. (2014) reached statistical significance because 24 participants were recruited, representing the double amount of samples compared to the studies in athletes identified in this review (Dekker, van den Berg, et al., 2014;Rijken et al., 2016). ...
... This data contradicts the study of Schabus et al. (2014) on adults that found a significant increase of subjective sleep quality (12-15 Hz) activity and slow-wave sleep over ten sessions. The study of Schabus et al. (2014) reached statistical significance because 24 participants were recruited, representing the double amount of samples compared to the studies in athletes identified in this review (Dekker, van den Berg, et al., 2014;Rijken et al., 2016). ...
Background: Neurofeedback (NFB) is a technique based on the principle of operant conditioning. It consists of modeling brain activity patterns to those considered to be deleterious to the organism to improve cognitive performance. Objective: This systematic review aims to present the neurofeedback field overview and results of empirical studies that tested the effects of neurofeedback training on cognitive performance in healthy subjects. Method: A systematic review of neurofeedback studies to increase cognitive performance in healthy subjects available on the Web of Science, BVSalud, PsycINFO, Redalyc, and Scielo databases, published between 2014 and 2020, was carried out. Initially, 192 articles were localized, of which 47 articles were included in order to present the general field overview, 34 empirical studies were included to discuss protocols and outcomes, and 18 trials were included to describe between-subjects effect size. Results: A contemporary trend toward the use of neurofeedback as a tool to improve cognition besides rehabilitation in healthy young adults, older adults, athletes, and the elderly was observed. Neurofeedback training had a large effect on working memory (WM), mood, and sleep quality; a medium to large effect on executive functions; a general medium effect size alongside a wider variation from low to large effect on attention. Conclusions: Although neurofeedback training studies showed promising results, not all studies found significant changes in electroencephalogram (EEG) signals that seemed to be linked to behavioral tests. This raises the question of causality relation between changes in brain activity and behavioral outcomes.
... Brain wave recordings over the sensorimotor cortex (involving both the sensory and motor cortical areas) revealed a markedly distinctive oscillatory pattern in a frequency range of 12-15 Hz, which is termed sensorimotor rhythm (SMR) (Chiang & Kang, 2012;Howe & Sterman, 1972;Sterman & Wyrwicka, 1967). SMR training significantly improves sleep, cognitive function, learning, and memory in healthy individuals and patients with insomnia (Hoedlmoser et al., 2008;Schabus et al., 2014). A previous randomized controlled trial (RCT) reported significant improvements in pain, fatigue, depression, anxiety, fibromyalgia symptom severity, and health-related quality of life following SMR neurofeedback among women with fibromyalgia (Kayıran et al., 2010). ...
... Alpha waves are beneficial for relaxation and self-regulation (Chiang & Kang, 2012). Studies have reported that SMR neurofeedback was efficacious for reducing the frequency of headaches among patients prone to migraines (Stokes & Lappin, 2010) and in improving sleep and cognitive function among patients with chronic pain (Chiang & Kang, 2012;Hoedlmoser et al., 2008;Schabus et al., 2014). The pathophysiologic mechanisms of fibromyalgia include CNS dysregulation and central sensitization involving the HPA axis (Desmeules et al., 2003). ...
... Impairments in cognitive performance associated with fibromyalgia have been identified in several domains, including executive function, learning memory, working memory, attention, and psychomotor speed (Wu et al., 2018). SMR neurofeedback training enhancement had an association with improved overnight memory, determined using the Wechsler memory scale, in healthy participants (Schabus et al., 2014). SMR neurofeedback training has also exhibited positive effects in the attention domain of cognitive function in individuals with attention-deficit/hyperactivity disorder (Bink, van Nieuwenhuizen, Popma, Bongers, & van Boxtel, 2015). ...
Background
Fibromyalgia is a chronic widespread pain condition that is associated with sleep disturbances and cognitive impairments. Neurofeedback has been demonstrated to improve pain, sleep quality, and fatigue. However, few studies have examined the effect of neurofeedback for patients with fibromyalgia.
Aim
To determine the effects of neurofeedback on pain intensity, symptom severity, sleep quality, and cognitive function in patients with fibromyalgia.
Design
This study was a randomized controlled trial.
Method
Eighty participants were randomized to a neurofeedback group (N = 60), receiving sensorimotor and alpha rhythm feedback for 8 weeks, or a telephone support group (N = 20).
Results
Results from the generalized estimating equation modelling revealed significant group-by-time interactions for Brief Pain Inventory pain severity (B = −1.35, SE = 0.46, p = .003) and pain interference (B = −1.75, SE = 0.41, p < .001), Revised Fibromyalgia Impact Questionnaire total scores (B = −16.41, SE = 3.76, p < .001), sleep onset latency (B = −25.33, SE = 9.02, p = .005), and Psychomotor Vigilance Test error (B = −1.38, SE = 0.55, p = .013) after adjustments for age, sex, duration of illness, and group differences at baseline.
Conclusions
An 8-week neurofeedback training regimen of sensorimotor rhythm and alpha brain waves significantly improved pain severity and interference, fibromyalgia symptom severity, sleep latency, and sustained attention in patients with fibromyalgia.
... The SMR target may be relevant for paretic after stroke, as it was found that SMR is related to motor imagery [72] and that motor imagery could have a positive effect on stroke rehabilitation [13]. Sleep targets are relevant for insomnia that is linked to poor sleep quality [81]. (For summary see Table 1.) ...
... Chronic insomnia was studied with two randomized blinded trials with respectively 16 and 12 patients treated with EEG NF (versus 11 and 12 subjects treated with ''placebo neurofeedback''). These studies were in favour of superior efficacy for EEG NF [42,81]. The effect of EEG NF on sleep could also improve memory function [81]. ...
... These studies were in favour of superior efficacy for EEG NF [42,81]. The effect of EEG NF on sleep could also improve memory function [81]. ...
Summary The technique of electroencephalographic neurofeedback (EEG NF) emerged in the 1970s and is a technique that measures a subject’s EEG signal, processes it in real time, extracts a parameter of interest and presents this information in visual or auditory form. The goal is to effectuate a behavioural modification by modulating brain activity. The EEG NF opens new therapeutic possibilities in the fields of psychiatry and neurology. However, the development of EEG NF in clinical practice requires (i) a good level of evidence of therapeutic efficacy of this technique, (ii) a good practice guide for this technique. Firstly, this article investi- gates selected trials with the following criteria: study design with controlled, randomized, and open or blind protocol, primary endpoint related to the mental and brain disorders treated and assessed with standardized measurement tools, identifiable EEG neurophysiological tar- gets, underpinned by pathophysiological relevance. Trials were found for: epilepsies, migraine, stroke, chronic insomnia, attentional-deficit/hyperactivity disorder (ADHD), autism spectrum disorder, major depressive disorder, anxiety disorders, addictive disorders, psychotic disorders. Secondly, this article investigates the principles of neurofeedback therapy in line with learn- ing theory. Different underlying therapeutic models are presented didactically between two continua: a continuum between implicit and explicit learning and a continuum between the biomedical model (centred on ‘‘the disease’’) and integrative biopsychosocial model of health (centred on ‘‘the illness’’). The main relevant learning model is to link neurofeedback therapy with the field of cognitive remediation techniques. The methodological specificity of neuro- feedback is to be guided by biologically relevant neurophysiological parameters. Guidelines for good clinical practice of EEG NF concerning technical issues of electrophysiology and of learn- ing are suggested. These require validation by institutional structures for the clinical practice of EEG NF.
... Previous studies have shown that the application of NF has beneficial effects in patients with sleep problems (Arns, Feddema, & Kenemans, 2014;Halson, 2017;Hammer et al., 2011;Schabus et al., 2014), while others have not shown superior effects compared to placebo (Schabus et al., 2017). However, an important limitation related to the NF protocol is found across these studies. ...
... However, an important limitation related to the NF protocol is found across these studies. The works by , , Halson et al. (2017), and Schabus et al. (2017Schabus et al. ( , 2014 assessed the effects of NF on the sensorimotor rhythm (SMR), a brain wave with a frequency in the range of 13 to 15 Hz that is recorded over the sensorimotor cortex (Arroyo et al., 1993). The SMR protocol was developed in the first place for the treatment of epilepsy and was later applied as a one-size-fits-all procedure for other conditions including attention-deficit/hyperactivity disorder (ADHD) or insomnia. ...
... In the SMR protocol, brain waves are recorded in C3 or Cz sites, and reinforcement are provided when SMR amplitude is increased irrespective of other brain waves in other sites. This means that the SMR protocol is not administered based on the individual's qEEG profile (Cortoos et al., 2010;Hoedlmoser et al., 2008;Schabus et al., 2017Schabus et al., , 2014, as waves at different brain sites are not trained. Hammer et al. (2011) compared a group receiving Z-score training guided by qEEG with a group receiving Z-score SMR training. ...
Objective/Background: Insomnia is the most common sleep disorder in the general population. Pharmacological treatments have shown efficacy in the short term, yet the symptoms return once the treatment has been withdrawn. In the search for treatment options with long-lasting effects, neurofeedback (NF) has arisen as a therapeutic option. Neurofeedback is the application of operant conditioning to brain activity. The aim of this work is to show the effectiveness of Live Z-Score NF training (LZT), a paradigm within the field of NF, in a case of insomnia. Participants: A 32-year-old male with chronic insomnia since his adolescence. Methods: Thirty 35-min sessions of qEEG-guided LZT using patient's highly preferred feedback. The main outcomes of this study were the patient's qEEG metrics and a visual analog scale of sleep quality throughout the intervention. Results: qEEG-guided LZT showed an improvement of 90.63% of the patient's qEEG metrics and an 82.55% relief of the clinical symptoms after 30 NF sessions. Conclusions: Although more research is needed to establish that NF based on Live Z-Score is effective for insomnia, our results suggest that NF might be a therapeutic alternative for the treatment of insomnia.
... Pour le trouble insomnie, quatre essais cliniques randomisés (3 en ouvert et 1 en simple insu) [16,[27][28][29], ont été publiés avant l'essai clinique randomisé contrôlé en double insu de 2017 qui sera discuté plus loin [30]. Les deux premiers dans les années 1980 sont ceux de Peter Hauri [16,27] et représentent dans le domaine général du neurofeedback les premiers essais cliniques d'efficacité de grande envergure. ...
... Ces études d'intérêt ont été réalisées par l'équipe de Schabus et al. (Autriche) [29,30,38], en utilisant un groupe neurofeedback placebo basé sur le renforcement de fréquence aléatoire du signal EEG enregistré chez le sujet. Le protocole de neurofeedback SMR était similaire entre les 3 études. ...
... Le protocole de neurofeedback SMR était similaire entre les 3 études. Enfin, l'absence de privation du sommeil était contrôlée tout au long des essais par agenda du sommeil [38] et actimétrie [29,30]. ...
Résumé
Le neurofeedback est une technique particulière de biofeedback qui utilise comme paramètre l’activité cérébrale, le plus souvent électroencéphalographique (EEG), dans le but de permettre, par des récompenses lors de la modification du paramètre dans le sens désiré, un entraînement et apprentissage de la régulation d’une fonction neurophysiologique qui, normalement, n’est ni perçue ni contrôlée consciemment. Parmi les paramètres de l’activité cérébrale, l’activité EEG la plus fréquemment utilisée, est l’entraînement au renforcement des rythmes sensorimoteurs (SMR). L’entraînement de l’augmentation du SMR serait relié à une activité cognitive de type « éveillé et attentif » avec inhibition accrue de l’activité motrice. Cet entraînement pourrait permettre de diminuer l’hyperéveil cortical relié à certains troubles, notamment dans le trouble insomnie chronique. Cet article présente les premières études chez l’animal dans les années 1970 ayant suggéré un effet bénéfique du neurofeedback SMR sur la qualité et la quantité du sommeil et des mécanismes d’action passant par les boucles de régulation thalamo-corticales de régulation de l’éveil et du sommeil. Il évalue ensuite les essais cliniques d’efficacité sur le sommeil à la fois chez les sujets avec trouble insomnie et sans trouble insomnie, afin de souligner les enjeux de recherche futurs du neurofeedback en médecine du sommeil. Il reste en effet nécessaire de réaliser des études contrôlées, randomisées, en double insu et des évaluations à long terme des plaintes d’insomnie et la qualité et quantité de sommeil, afin d’asseoir définitivement l’efficacité du neurofeedback et sa place dans le champ des thérapeutiques non pharmacologiques de l’insomnie. Ces études devront permettre non seulement de répondre à la question de l’efficacité, mais aussi de permettre d’avancer dans le domaine de la mise en place optimale des protocoles de neurofeedback et de la fixation des seuils de récompenses pendant l’entraînement, de la mesure de l’effet d’apprentissage et du paramètre cérébral impacté et du sous-groupe de trouble insomnie chronique ciblé en fonction de ce paramètre, et enfin des variables non spécifiques influençant l’entraînement, l’apprentissage et l’efficacité de la thérapeutique.
... A minimum reward incidence of 5 per 3-min session was given to maintain appropriate motivation in the PFT group. Both groups underwent standard PSG at baseline and post-treatment (Schabus et al., 2014). ...
... The data also indicated that PFT had negative consequences on sleep. A more recent study by Schabus et al. (2017) concluded that neurofeedback had no effect on insomnia patients compared to placebo despite their earlier works that reached other conclusions (Berner et al., 2006;Hoedlmoser et al., 2008;Schabus et al., 2014). The latest work had a similar design but failed to include inhibit training despite ostensibly following their earlier efforts. ...
This paper will review what is conventionally known of sleep homeostasis and focus on insomnia as a primary manifestation of brain dysregulation, whether as a solitary symptom or as part of a larger syndrome such as post-traumatic stress disorder, PTSD. It will discuss in brief behavioral/mindfulness treatments that have been used to treat neurologic diseases, as this is germane to the phenomenology of neurofeedback (NF). It will explore how neurofeedback may work at the subconscious level and cover the current clinical experience of the effectiveness of this technique in the treatment of insomnia. It will conclude with a case presentation.
... Activation is then preprocessed in real-time and fed back to the user [15]. Modulating brain activation patterns in a desired direction using NF is used to improve cognitive or motoric performances in the context of neurorehabilitation and neuropsychological training [17], sports [33], acting performance [6], or improving sleeping quality [23]. ...
... After filling out questionnaires and having the EEG and VR montage done, participants had to undergo seven feedback-runs of 3 min each with short breaks in-between. The first run was a baseline run where they were told to just watch the target objects without trying to alter their brain activation in order to identify individual frequency-band thresholds for SMR (12)(13)(14)(15), Theta (4-7 Hz) and Beta (16)(17)(18)(19)(20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30). SMR had to be kept high, whereas Theta and Beta should be held as low as possible, to avoid artifacts such as blinks or movements [28] as target objects would turn red and stop moving when they were too high. ...
In brain-computer interface applications such as neurofeedback (NF), traditional 2D visual feedback has been replaced frequently by more sophisticated 3D virtual reality (VR) scenarios. VR is considered to be more motivating and to increase NF training success. However, hard evidence on user experience in set-ups combining VR-EEG NF has been scarcely reported. Hence, we evaluated user experience on cybersickness, discomfort/pain, technology acceptance and motivational factors and compared them between a 3D and a 2D VR scenario. Additionally, we focused on possible sex differences. 68 subjects received one VR-neurofeedback session with either a 3D or 2D VR paradigm. Statistical analyses showed that sickness was higher after the VR-NF training than before, and women experienced higher sickness values than men. Further, women reported more subjective pressure sensations on the head, eye burning and headache, as well as higher technology anxiety, less perceived usefulness of the used technology and less perceived technology accessibility. No dimensionality or sex differences regarding subjective feeling of flow and presence were found. Moreover, no differences between the 3D and 2D VR scenarios were observed. Our results indicate sex differences in user experience in VR-based NF paradigms, which should be considered when using VR as feedback modality in future NF applications. In contrast, 3D or 2D presentation of the VR scenario did not affect user experience, indicating that more immersive 3D VR scenarios do not cause more negative side effects than the less immersive 2D VR scenario.
... Studies involving humans have reported that SMR neurofeedback resulted in significant sleep improvements in individuals with insomnia after an average of 25 sessions (Hauri, 1981;Hauri et al., 1982) as well as increased sleep spindle density and decreased sleep onset latency (SOL) in students (Hoedlmoser et al., 2008). As a follow-up to this latter study, Schabus et al. (2014) later investigated SMR neurofeedback in patients with primary insomnia and reported a reduced number of awakenings, a decreased SOL (trend-level), and an increase in slow-wave sleep after SMR neurofeedback. However, a double-blind placebo-controlled follow-up study demonstrated that sham stimulation reduced subjective sleep problems similarly to active stimulation (suggesting non-specific training effects) and a lack of improvements in objective measurements of sleep (Schabus et al., 2017). ...
... Finally, actigraphy data numerically supported the improvements although these effects were not significant. SMR neurofeedback has previously been associated with decreased SOL and longer sleep duration (Arns et al., 2014a(Arns et al., , 2014bCortoos et al., 2010;Hoedlmoser et al., 2008;Schabus et al., 2014), partly in line with the results reported here. One study failed to find such effects (Schabus et al., 2017), possibly due to the low number of 12 sessions. ...
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.
... Two studies were not evaluated because they did not clearly describe whether the participants were randomized (Coursey et al. 1980;Cortoos et al. 2010b). Therefore, seven studies were included (Freedman and Papsdorf 1976;Haynes et al. 1977;Hauri 1981;Nicassio et al. 1982;Sanavio et al. 1990;Schabus et al. 2014;Schabus et al. 2017), and their detailed characteristics are summarized in Table S3 in Supplementary material. ...
... Study 6 (Schabus et al. 2014) was a crossover randomized trial. The randomization method (computer generated) was considered adequate, but outcome evaluators were not blinded. ...
The treatment of insomnia is still a challenge in clinical practice. This systematic review of randomized and quasi-randomized clinical trials aims to summarize the evidence for the use of biofeedback techniques in the treatment of chronic insomnia. Studies that compared biofeedback with other techniques of cognitive behavioral therapy, placebo, or absence of treatment were selected. The outcomes evaluated included sleep onset latency, total sleep time, sleep fragmentation, sleep efficiency and subjective sleep quality. Comparing to placebo and absence of treatment, some studies suggest possible benefits from the use of biofeedback for chronic insomnia in decreasing sleep onset latency and number of awakenings; however, there was marked divergence among included studies. There was no evidence of improvement in total sleep time, sleep efficiency and subjective sleep quality. Moreover, the maintenance of long-term benefits lacks evidence for any outcome. In the majority of outcomes evaluated, no significant differences in the effectiveness of biofeedback compared with other cognitive behavioral therapy techniques were observed. This systematic review found conflicting evidence for the effectiveness of biofeedback techniques in the treatment of chronic insomnia. Inter- and intra-group clinical heterogeneity among studies could be a reasonable explanation for the divergent results. These findings emphasize the need of performing further randomized clinical trials of higher methodological quality in order to better delineate the effectiveness of biofeedback on chronic insomnia treatment.
... Brain rhythmic oscillations can be easily triggered through various non-invasive rhythmic stimuli. For example, sensorimotor stimulation has been shown to synchronize brain oscillations with external rhythms [46,47] through rhythmic musical stimuli [48] and more generally rhythmic sensory stimulation [27,49]. Auditory stimulation, such as rhythmic sound patterns, similarly triggers neural entrainment by aligning brain activity with the timing of sensory inputs [50]. ...
Background: The human sensorimotor system can naturally synchronize with environmental rhythms, such as light pulses or sound beats. Several studies showed that different styles and tempos of music, or other rhythmic stimuli, have an impact on physiological rhythms, including electrocortical brain activity, heart rate, and motor coordination. Such synchronization, also known as the “entrainment effect”, has been identified as a crucial mechanism impacting cognitive, motor, and affective functioning. Objectives: This review examines theoretical and empirical contributions to the literature on entrainment, with a particular focus on the physiological mechanisms underlying this phenomenon and its role in cognitive, motor, and affective functions. We also address the inconsistent terminology used in the literature and evaluate the range of measurement approaches used to assess entrainment phenomena. Finally, we propose a definition of “physiological entrainment” that emphasizes its role as a fundamental mechanism that encompasses rhythmic interactions between the body and its environment, to support information processing across bodily systems and to sustain adaptive motor responses. Methods: We reviewed the recent literature through the lens of the “embodied cognition” framework, offering a unified perspective on the phenomenon of physiological entrainment. Results: Evidence from the current literature suggests that physiological entrainment produces measurable effects, especially on neural oscillations, heart rate variability, and motor synchronization. Eventually, such physiological changes can impact cognitive processing, affective functioning, and motor coordination. Conclusions: Physiological entrainment emerges as a fundamental mechanism underlying the mind–body connection. Entrainment-based interventions may be used to promote well-being by enhancing cognitive, motor, and affective functions, suggesting potential rehabilitative approaches to enhancing mental health.
... The NFT group focused on increasing activity in the 12-15 Hz SMR range, while the PFT group targeted random frequency ranges between 7 and 20 Hz, excluding the 12-15 Hz SMR range. The protocol was based on the approach used by Hoedlmoser et al. (2008) and Schabus et al. (2014Schabus et al. ( , 2017. To assess the neurocognitive impact of this neurofeedback training procedure on inhibitory control, participants completed a Go-NoGo task while EEG recording was performed. ...
Background/Objective
Inhibition is crucial for controlling behavior and is impaired in various psychopathologies. Neurofeedback holds promise in addressing cognitive deficits, and experimental research is essential for identifying its functional benefits. This study aimed to investigate whether boosting sensorimotor activity (SMR) improves inhibitory control in a final sample of healthy individuals (N = 53), while exploring the underlying neurophysiological mechanism.
Method
Participants were randomly divided into two groups: one receiving SMR neurofeedback training to enhance sensorimotor activity within the 12–15 Hz frequency range, and the other receiving sham feedback. Inhibition performance and neural correlates were evaluated with a Go-NoGo task before (T0) and after (T1) 10 neurofeedback sessions using event-related potentials. Data were analyzed via ANOVAs and regression analyses.
Results
Compared to placebo, the active group demonstrated higher absolute SMR power (p = 0.040) and improvements in inhibitory control, including faster response times and fewer inhibition errors (p < 0.001, d = 6.06), associated with a larger NoGoP3d amplitude (p < 0.001, d = 3.35). A positive correlation between the increase in SMR power and the rise in NoGoP3d amplitude (β=0.46, p = 0.015) explains 21 % of the observed variance.
Conclusions
Uptraining SMR power is linked to heightened utilization of neural resources for executing optimal inhibition responses. These results uphold its effectiveness in cognitive rehabilitation.
... For example, Kübler et al. [58] found that healthy subjects reached a learning plateau after 3 sessions, while in patients with Amyotrophic Lateral Sclerosis, no learning plateau was reached after 12 sessions. In a neurofeedback study on patients with primary insomnia, participants showed fluctuating learning, which, interrupted by stagnation sessions, increased over the sessions [59]. In anxious patients, Hardt and Kamiya [60] hypothesized a fifth-order learning curve, starting with an initial increase, followed by a decline, a second increase, and a final exponential increase for the learning of alpha-neurofeedback. ...
(1) Background: Neurofeedback training (NFT) has emerged as a promising approach for enhancing cognitive functions and reducing anxiety, yet its specific impact on university student populations requires further investigation. This study aims to examine the effects of NFT on working memory improvement and anxiety reduction within this demographic. (2) Methods: A total of forty healthy university student volunteers were randomized into two groups: an experimental group that received NFT and a control group. The NFT protocol was administered using a 14-channel Emotiv Epoc X headset (EMOTIV, Inc., San Francisco, CA 94102, USA) and BrainViz software version Brain Visualizer 1.1 (EMOTIV, Inc., San Francisco, CA 94102, USA), focusing on the alpha frequency band to target improvements in working memory and reductions in anxiety. Assessment tools, including the Corsi Block and Memory Span tests for working memory and the State-Trait Anxiety Inventory-2 (STAI-2) for anxiety, were applied pre- and post-intervention. (3) Results: The findings indicated an increase in alpha wave amplitude in the experimental group from the second day of NFT, with statistically significant differences observed on days 2 (p < 0.05) and 8 (p < 0.01). Contrary to expectations based on the previous literature, the study did not observe a concurrent positive impact on working memory. Nonetheless, a significant reduction in state anxiety levels was recorded in the experimental group (p < 0.001), corroborating NFT’s potential for anxiety management. (4) Conclusions: While these results suggest some potential of the technique in enhancing neural efficiency, the variability across different days highlights the need for further investigation to fully ascertain its effectiveness. The study confirms the beneficial impact of NFT on reducing state anxiety among university students, underscoring its value in psychological and cognitive performance enhancement. Despite the lack of observed improvements in working memory, these results highlight the need for continued exploration of NFT applications across different populations and settings, emphasizing its potential utility in educational and therapeutic contexts.
... The sensorimotor cortex's electroencephalogram recordings showed the presence of unique oscillating waves in the 12-15 Hz range, or sensorimotor rhythm (SMR). Improved sleep quality was a result of elevated SMR, which was connected to decreased nocturnal waking and greater slow-wave sleep in primary insomnia (Schabus et al., 2014). An earlier study using neuroimaging discovered that patients with chronic primary insomnia have a higher level of amplitude of low-frequency fluctuations (ALFF) in the posterior central gyrus/subparietal lobules, which is associated with poor sleep (Zhou et al., 2017). ...
Objectives
This study aimed to investigate local and remote functional connectivity in mild Alzheimer’s disease patients with sleep disturbances (ADSD) and those without sleep disturbances (ADNSD).
Methods
Thirty eight mild AD patients with sleep disturbances and 21 mild AD patients without sleep disturbances participated in this study. All subjects underwent neuropsychological assessments and 3.0 Tesla magnetic resonance scanning. Static and dynamic regional homogeneity (ReHo) were used to represent the local functional connectivity. Seed-based whole-brain functional connectivity was used to represent the remote functional connectivity. The seed was chosen based on the results of ReHo.
Results
Compared to ADNSD, ADSD showed decreased static ReHo in the left posterior central gyrus and the right cuneus and increased dynamic ReHo in the left posterior central gyrus. As for the remote functional connectivity, comparing ADSD to ADNSD, it was found that there was a decreased functional connection between the left posterior central gyrus and the left cuneus as well as the left calcarine.
Conclusion
The current study demonstrated that, compared with ADNSD, ADSD is impaired in both local and remote functional connectivity, manifested as reduced functional connectivity involving the primary sensory network and the primary visual network. The abnormality of the above functional connectivity is one of the reasons why sleep disorders promote cognitive impairment in AD. Moreover, sleep disorders change the temporal sequence of AD pathological damage to brain functional networks, but more evidence is needed to support this conclusion.
... Similar positive findings are apparent in healthy and diseased populations, with short-term HRV-BF training reducing perceived fatigue and negative mood states (Windthorst et al., 2017), which also occurs alongside sleep benefits in patients with anxiety disorders (Reiner, 2008). Likewise, preliminary results suggest that 10 EEG-BF training sessions decreases the number of awakenings, as well as increases deep sleep and subjective sleep quality (Schabus et al., 2014). Pre-sleep EEG-BF may promote sleep by stimulating alpha waves that occur when an individual is in a deeply relaxed awake state (Marzbani et al., 2016). ...
The current study compared the effects of heart rate variability biofeedback (HRV-BF) and electroencephalographic biofeedback (EEG-BF) on sleep, mood, and reaction time. Fourteen highly trained male athletes with sleep disturbances participated in this randomised crossover study. Participants took part in HRV-BF and EEG-BF training, with each condition consisting of eight sessions over 15 days. Polysomnography (PSG) and the Pittsburgh sleep quality index (PSQI) were used to assess sleep quality, the profile of mood states (POMS) questionnaire to monitor mood, and reaction time to measure performance pre and post intervention. HRV-BF training improved PSG sleep efficiency (SE) (P = 0.022, d = 0.35, 95% CI 0.01 to 0.16) and subjective sleep duration (P = 0.011, ES = 0.40) when compared to EEG-BF. Only HRV-BF reduced reaction time pre to post biofeedback training (P = 0.020, d = 0.75, 95% CI 0.006 to 0.059). The PSQI showed that both HRV-BF (P = 0.025, ES = 0.31) and EEG-BF (P = 0.003, ES = 0.32) resulted in improved global PSQI scores. Total mood disturbance was also reduced though HRV-BF (P = 0.001, ES = 0.40) and EEG-BF (P = 0.001, ES = 0.30). HRV-BF and EEG-BF enhanced some subjective parameters of sleep and mood. HRV-BF increased PSG SE and subjective sleep duration more than EEG-BF in highly trained athletes with sleep disturbances.
... Double-blind sham control groups are still relatively sparse in the literature (Ramos-Murguialday et al., 2013;Park et al., 2014;Schabus et al., 2014;Kober et al., 2015), but discussions on possible placebo effects have been quite extensive and revealed some interesting explanations on why such effects might emerge. Thibault et al. (2017) suggested that very specific NF-behavior, such as SMR power increase, can be driven by unspecific factors. ...
Electroencephalography-neurofeedback (EEG-NF) has become a valuable tool in the field of psychology, e.g., to improve cognitive function. Nevertheless, a large percentage of NF users seem to be unable to control their own brain activation. Therefore, the aim of this study was to examine whether a different kind of visual feedback could positively influence NF performance after one training session. Virtual reality (VR) seems to have beneficial training effects and has already been reported to increase motivational training aspects. In the present study, we tested 61 young healthy adults (mean age: 23.48 years; 28 female) to investigate, whether 3D VR-based NF training has a more beneficial effect on the sensorimotor rhythm (SMR, 12–15 Hz) power increase than a mere 2D conventional NF paradigm. In the 3D group, participants had to roll a ball along a predefined path in an immersive virtual environment, whereas the 2D group had to increase the height of a bar. Both paradigms were presented using VR goggles. Participants completed one baseline and six feedback runs with 3 min each, in which they should try to increase SMR power over Cz. Half of the participants received real feedback whereas the other half received sham feedback. Participants receiving 3D VR-based feedback showed a linear increase in SMR power over the feedback runs within one training session. This was the case for the real as well as for the sham 3D feedback group and might be related to more general VR-related effects. The 2D group receiving the conventional bar feedback showed no changes in SMR power over the feedback runs. The present study underlines that the visual feedback modality has differential effects on the NF training performance and that 3D VR-based feedback has advantages over conventional 2D feedback.
... SMR is of particular interest with respect to ADHD treatment because high amplitudes of this frequency have been associated with relaxed attentiveness and decreased impulsivity [18,21,22]. Apart from that, it plays a role in sleep onset latency [23,24]. Thus, SMR training has been shown to shorten sleep onset and improve sleep quality, a factor that has received increasing attention in ADHD research lately [25,26,27]. ...
Background:
EEG Neurofeedback training is an accepted non-pharmacological therapy for attention deficit/ hyperactivity disorder (ADHD). Although stimulant medication is known to decrease ADHD symptoms, possible adverse effects, concerns about prolonged drug use on neural development, and problems related to the compliance with the medications are often reported. In Indonesia, research on the feasibility of EEG Neurofeedback to treat ADHD is still lacking. The current study aimed to investigate whether setting up an EEG neurofeedback training program for children with ADHD would be feasible in Indonesia.
Methods:
Nine children (aged 6-12 years) participated in the study. ADHD was diagnosed using the Vanderbilt ADHD Diagnostic Rating Scale (VADRS). Children received twenty-five sessions of sensorimotor rhythm (SMR) neurofeedback training twice a week. Each session consisted of a 3-minute baseline, followed by 5*3 minutes of training. IQ scores and VADRS scores were collected at baseline, after completion of the intervention, and at 3 months follow-up, while school reports were provided by the schools. The EEG spectral content was determined for all 25 training sessions. In addition, a Go/No-Go Task, was administered at the first 5 training sessions, and at session 10, 15, 20 and 25.
Results and conclusion:
An overview of all the collected data is provided descriptively, given the small group size. One child dropped-out during the training because of parental request, but the remaining eight children completed the full intervention program. Descriptive data suggested improvement with respect to both the ADHD symptomatology and performance IQ. These findings are in line with previous studies. Although a control arm was not included, we propose that the abovementioned SMR neurofeedback protocol may still be offered as a suitable non-pharmacological intervention for children with ADHD in Indonesia and deserves further research.
... Although the beta increase has been related to motor performance [28], the motor component is absent during this phase of the task. Moreover, such beta increase has been observed as a result of anxiety-reducing therapeutic interventions [84], i.e., forms of meditation including mindfulness training, which could share some positive effects with biofeedback and NFB treatments [85,86]. Yet, there is conflicting evidence of beta power changes after meditation programs, with some studies reporting increases and others decreases in beta power [87,88]. ...
Learning disorders (LDs) are diagnosed in children impaired in the academic skills of reading, writing and/or mathematics. Children with LDs usually exhibit a slower resting-state electroencephalogram (EEG), corresponding to a neurodevelopmental lag. Frequently, children with LDs show working memory (WM) impairment, associated with an abnormal task-related EEG with overall slower EEG activity (more delta and theta power, and less gamma activity in posterior sites). These EEG patterns indicate inefficient neural resource management. Neurofeedback (NFB) treatments aimed at normalizing the resting-state EEG of LD children have shown improvements in cognitive-behavioral indices and diminished EEG abnormalities. Given the typical findings of WM impairment in children with LDs, we aimed to explore the effects of an NFB treatment on the WM of children with LDs by analyzing the WM-related EEG power spectrum. EEGs of 18 children (8–11 y.o.) with LDs were recorded, pre- and post-treatment, during performance of a Sternberg-type WM task. Thirty sessions of an NFB treatment (NFB-group, n = 10) or 30 sessions of a placebo-sham treatment (sham-group, n = 8) were administered. We analyzed the before and after treatment group differences for the behavioral performance and the WM-related EEG power spectrum. The NFB group showed faster response times in the WM task post-treatment. They also exhibited a decreased theta power and increased beta and gamma power at the frontal and posterior sites post-treatment. We explain these findings in terms of NFB improving the efficiency of neural resource management, maintenance of memory representations, and improved subvocal memory rehearsal.
... Positive reinforcement seems to be more important than the feedback's operating component [56]. Although some studies have found good results while using the same reinforcement for all participants [28,57,58], other studies have found limited effect or no effect at all [29]. Our results suggest that one cause for these discrepancies may reside in the use of the same or low-preference reinforcements for all participants, an issue that had not been monitored for so far. ...
The brain activity that is measured by electroencephalography (EEG) can be modified through operant conditioning, specifically using neurofeedback (NF). NF has been applied to several disorders claiming that a change in the erratic brain activity would be accompanied by a reduction of the symptoms. However, the expected results are not always achieved. Some authors have suggested that the lack of an adequate response may be due to an incorrect application of the operant conditioning principles. A key factor in operant conditioning is the use of reinforcers and their value in modifying behavior, something that is not always sufficiently taken into account. This work aims to clarify the relevance of the motivational value versus the purely informational value of the reinforcer. In this study, 113 subjects were randomly assigned two different reinforcer conditions: a selected reinforcer—the subjects subjectively selected the reinforcers—or an imposed reinforcer—the reinforcers were assigned by the experimenter—and both groups undertook NF sessions to enhance the sensorimotor rhythm (SMR). In addition, the selected reinforcer group was divided into two subgroups: one receiving real NF and the other one sham NF. There were no significant differences between the groups at baseline in terms of SMR amplitude. After the intervention, only those subjects belonging to the selected reinforcer group and receiving real NF increased their SMR. Our results provide evidence for the importance of the motivational value of the reinforcer in Neurofeedback success.
... Online EEG signals were processed using NeuroPype (Intheon) software. Signals were bandpass filtered for the sensorimotor frequency (12-17 Hz) used from the previous monkey study (Philippens et al., 2017), but human studies generally use 12-15 Hz (Schabus et al., 2014). ...
Electroencephalographic activity over the sensorimotor cortex has been one of the best studied targets for neurofeedback therapy. Parkinson’s disease patients display abnormal brain rhythms in the motor cortex caused by increased synchrony in the basal ganglia-cortical pathway. Few studies have examined the effects of sensorimotor-based neurofeedback therapy in humans with PD. In this pilot study, one patient, diagnosed with Parkinson’s disease 10 years prior, participated in two consecutive days of EEG neurofeedback training to increase sensorimotor rhythm (SMR) power over the motor cortex. Using a visual display connected to ongoing EEG, the patient voluntarily manipulated SMR power, and he/she was awarded with points to positively reinforce successful increases over a predefined threshold. Recorded EEG data were source localized and analyzed for the occurrence of high amplitude bursts of SMR activity as well as bursts in the beta frequency band in the precentral cortex. The rate of SMR bursts increased with each subsequent training session, while the rate of beta bursts only increased on the final session. Relative power in the beta band, a marker of PD symptom severity, decreased over the motor cortex in the later session. These results provide first evidence for the feasibility of SMR neurofeedback training as a non-invasive therapy for reducing Parkinson’s disease related activity and upregulating SMR in the human motor cortex.
... Sleep quality measurement can be carried out by various methods, such as subjective and objective methods. One of the objective methods is polysomnography; it is the standard gold of sleep quality measurement (Schabus et al., 2014). ...
Many cancer patients experience sleep disturbances or have poor sleep quality. The measurement of sleep quality in cancer patients has not been carried out in hospitals in Indonesia. The tools for measuring sleep are costly. Sleep quality measurement with sleep quality instruments has not been applied as a standard for patient assessment. To test the validity and reliability of the Indonesian version of the Sleep Quality Scale instrument to measure the quality of one's sleep and to test the internal consistency and retest reliability of the Indonesian version of the Sleep Quality Scale instrument to measure the quality of one's sleep. The instrument used was SQS with six components and 28 items. This research is a quantitative approach with a cross-sectional design. This research is a study of the validity and reliability of the instrument. The content validity test was measured using Aiken's V formula. The construct validity was measured using the product-moment, and using factor analysis, the reliability of SQS was measured using the Cronbach Alphand the reliability of the retest was using the ICC test. The Sleep Quality Scale shows good validity, namely the content validity value of Aiken's value V0.976, the validity of the extract of all SQS items, is valid. Internal consistency reliability shows good results. Cronbach Alpha 0.849, the ICC value on the test-retest test is 0.903. The goodness of fit test shows unsatisfactory results with a p-value of chi-square 0.00, RSMEA = 0.067, GFI = 0.750 and CFI = 0.869. Clinicians can use the Indonesian version of the Sleep Quality Scale instrument as an instrument to measure sleep quality in cancer patients.
... Many NF training studies, in which the amplitude of the SMR should be increased over one electrode position, observed withinsession changes in SMR power but no between-session changes (Vernon et al., 2003;Vernon, 2005;Ros et al., 2010;Kober et al., 2015aKober et al., ,b, 2017bKober et al., , 2019Reichert et al., 2016). SMR-based NF studies that report on between-session changes either used ratios of the power within two or more frequency bands or relied on relative power changes limiting the evaluation of changes in absolute SMR power values between sessions Zambotti et al., 2012;Kober et al., 2013;Ros et al., 2013;Schabus et al., 2014Schabus et al., , 2017. Generally, in the NF literature it is disputed whether NF training should lead to within-or betweensession changes in the EEG (Enriquez-Geppert et al., 2017). ...
Modulating connectivity measures in EEG-based neurofeedback studies is assumed to be a promising therapeutic and training tool. However, little is known so far about its effects and trainability. In the present study, we investigated the effects of up- and down-regulating SMR (12–15 Hz) coherence by means of neurofeedback training on EEG activity and memory functions. Twenty adults performed 10 neurofeedback training sessions in which half of them tried to increase EEG coherence between Cz and CPz in the SMR frequency range, while the other half tried to down-regulate coherence. Up-regulation of SMR coherence led to between- and within-session changes in EEG coherence. SMR power increased across neurofeedback training sessions but not within training sessions. Cross-over training effects on baseline EEG measures were also observed in this group. Up-regulation of SMR coherence was also associated with improvements in memory functions when comparing pre- and post-test results. Participants were not able to down-regulate SMR coherence. This group did not show any changes in baseline EEG measures or memory functions comparing pre- and post-test. Our results provide insights in the trainability and effects of connectivity-based neurofeedback training and indications for its practical application.
... All participants were right-handed and had normal or corrected-to-normal vision and hearing. While this study aimed to assess the relationship between NFB training efficacy and pain modulation, previous studies have reported an average effect size of r = 0.40 for the correlation between NFB training induced EEG and behavioral changes (Nan et al., 2012(Nan et al., , 2020Schabus et al., 2014). According to G*Power software (Faul et al., 2007), a sample size between 34 (for one-tailed correlation analyses) and 44 (for two-tailed correlation analyses) is appropriate to detect an effect size of r = 0.40, at significance level of 0.05 with 80% power. ...
Studies have shown an association between sensorimotor α-oscillation and pain perception. It suggests the potential use of neurofeedback (NFB) training for pain modulation through modifying sensorimotor α-oscillation. Here, a single-session NFB training protocol targeted on increasing sensorimotor α-oscillations was applied to forty-five healthy participants. Pain thresholds to nociceptive laser stimulations and pain ratings (intensity and unpleasantness) to identical laser painful stimulations were assessed immediately before and after NFB training. Participants had larger pain thresholds, but rated the identical painful laser stimulation as more unpleasant after NFB training. These pain measurements were further compared between participants with high or low NFB training efficacy that was quantified as the regression slope of α-oscillation throughout the ten training blocks. A significant increase in pain thresholds was observed among participants with high-efficacy; whereas a significant increase in pain ratings was observed among participants with low-efficacy. These results suggested that NFB training decreased the sensory-discriminative aspect of pain, but increased the affective-motivational aspect of pain, whereas both pain modulations were dependent upon the NFB training efficacy. Importantly, correlation analysis across all participants revealed that a greater NFB training efficacy predicted a greater increase in pain thresholds particularly at hand contralateral to NFB target site, but no significant correlation was observed between NFB training efficacy and modulation on pain ratings. It thus provided causal evidence for a link between sensorimotor α-oscillation and the sensory-discriminative aspect of pain, and highlighted the need for personalized neurofeedback for the benefits on pain modulation at the individual level. Future studies can adopt a double-blind sham-controlled protocol to validate NFB training induced pain modulation.
... Even though this protocol was first used to treat the ADHD, it has also been applied as a one-size-fits-all protocol for other conditions such as insomnia (Hammer, Colbert, Brown, & Ilioi, 2011;Schabus et al., 2014), cognitive performance (Doppelmayr & Weber, 2011), impulsivity (Bluschke, Broschwitz, Khol, Roessner, & Beste, 2016;Liu, Hou, Sourina, & Bazanova, 2016), and executive functions or autism (Kouijzer, de Moor, Gerrits, Congedo, & van Schie, 2009). ...
Objective/Background: Theta-to-Beta ratio is one of the most studied electroencephalography findings in ADHD in the neurotherapy field, alongside the neurofeedback (NF) protocols whose objective is reducing it. The NF field has developed to a great level in the last decade. One of the approaches that became of particular interest to the clinicians has been Z-score training (ZT). In general, there are still a few studies about the efficacy of ZT and even fewer that compare this technique with the classic protocols. This study aimed to check the efficacy of ZT in reducing Theta-to-Beta ratio. Participants: 15 patients diagnosed with combined type ADHD aged 7 to 18, recruited in retrospect. Methods: The participants were divided in two groups. One of the groups was provided with the ZT intervention and the other one, the Theta/Beta (T/B) protocol. Both groups went through ten 30-min NF sessions using videos selected by themselves as a reinforcement. The main outcomes of this study were the patients’ Theta-to-Beta ratio metrics. Results: Both groups showed a decrease in Theta-to-Beta ratio; the ZT group showed a decrease of 1.02 points average and the T/B group showed a decrease of 0.15 points average, only being statistically significant for the ZT group.
... A quantitative electroencephalogram (QEEG) diagnostics performed prior to the EEG NFB therapy assessed the effect of the neurofeedback method on the neurophysiological parameters in the EEG recording of the b, b2, waves, sensorimotor rhythm (SMR) and t waves. The first test demonstrated dominance of the SMR activity (12-15 Hz) and b waves (15)(16)(17)(18)(19)(20) in the left brain hemisphere (b waves were correct, and SMR was incorrect), which was consistent with emotional imbalance and attention deficits. The d waves (1-3 Hz) and t waves (4-8 Hz) in the central region slightly exceeded the norm of 20 and 10 µV, respectively. ...
Amyotrophic lateral sclerosis is a progressive and fatal degenerative neuromuscular disease with few if any treatment options and physical rehabilitation addressing specific deficits is the most frequent form of therapy. Patients also suffer from depression and increased anxiety. Our purpose was to assess the neurorehabilitation effectiveness in a patient with amyotrophic lateral sclerosis who underwent stem cell transplantation but refused physiotherapy due to depression. Disease progression was followed using the revised Amyotrophic Lateral Sclerosis Functional Rating Scale bimonthly for six months pre-and then post-stem cell transplantation. Psychological traits were assessed using six standardized tests. Quantitative electroencephalogram diagnostics was performed before the first and after the last neurofeedback session, and sessions were conducted on a 3-times-a-week basis. The physiotherapy protocol included proprioceptive neuromuscular facilitation, electrical modalities unit applied to the lumbar spine area, and breathing, relaxation and walking exercises, among others. Increased motivation and marked decrease in the pain level was associated with the patient's willingness to complete physiotherapy, which resulted in improvements in most neuromuscular deficits and in increased respiratory capacity. During the 12 post-rehabilitation months, progression of the disease decelerated, and a positive behavioral change was noted. The study suggested that neurofeedback could be used as a neurorehabilitation component of the personalized complex rehabilitation protocol in patients with amyotrophic lateral sclerosis.
... Yet, the comparison between our two experimental groups (i.e., HRV biofeedback group and HRV/NFB group) offers us an alternative to the sham condition and helps us to investigate the specificity of the NFB training. A few previous SMR-based NFB pieces of research claimed to demonstrate the specificity of NFB by reporting only changes in the trained EEG frequencies and not the whole EEG spectrum Doppelmayr and Weber, 2011;Gruzelier, 2014;Schabus et al., 2014;Kober et al., 2015Kober et al., , 2017Reichert et al., 2015). However, it remains unclear whether participants can intentionally modify amplitudes of specifically selected electroencephalographic frequencies. ...
Neurofeedback (NFB) is an operant conditioning procedure whereby an individual learns to self-regulate the electrical activity of his/her brain. Initially developed as a treatment intervention for pathologies with underlying EEG dysfunctions, NFB is also used as a training tool to enhance specific cognitive states required in high-performance situations. The original idea behind the NFB training effect is that the changes should only be circumscribed to the trained EEG frequencies. The EEG frequencies which are not used as feedback frequencies should be independent and not affected by the neurofeedback training. Despite the success of sensorimotor rhythm NFB training in cognitive performance enhancement, it remains unclear whether all participants can intentionally modify the power densities of specifically selected electroencephalographic (EEG) frequencies. In the present study, participants were randomly assigned to either a control heart rate variability (HRV) biofeedback (HRV) training group or a combination of HRV biofeedback and neurofeedback (HRV/NFB) training group. This randomized mixed design experiment consisted of two introductory theoretical lessons and a training period of 6 weeks. We investigated the evolution of the different EEG frequency bands of our two experimental groups across and within session. All the participants exhibited EEG changes across and within session. However, within the HRV/NFB training group, untrained EEG frequencies have been significantly modified, unlike some of the trained frequencies. Moreover, EEG activity was modified in both the HRV group and the HRV/NFB groups. Hence, the EEG changes were not only circumscribed to the trained frequency bands or to the training modality.
... One study induced slowly oscillating potential stimulation in healthy adults and found an immediate change in spindle activity that enhanced the retention of hippocampus-dependent declarative memories [104]. Similar findings were observed in a group of adult participants who suffered from insomnia; they evinced changes in sleep spindles and concomitant increases in memory consolidation following sensorimotor rhythm conditioning [105]. Using acoustic perturbation to modulate slow waves and spindles in children, another study [106] found that children performed better if they had a greater number of fast spindles following the manipulation. ...
Sleep is a basic need. Mounting evidence suggests this is particularly true during adolescence, a developmental period involving substantial changes in the brain regions supporting cognition, learning, and emotion. Although sleep loss is a normative psychosocially and biologically driven developmental process, it occurs alongside behaviors that characterize adolescence, including deepening cognitive sophistication, improved emotion regulation, and intensifying social cognition, calling into question how sleep may impact these developmental milestones. This review synthesizes growing research aimed at addressing this timely question. It presents evidence that neurodevelopmental changes in brain structure, function, and sleep physiology mechanistically link the relationship between sleep and cognitive ability.
Chronic sleep disturbance has a pronounced adverse impact on a person’s quality of life and physical and mental well-being. Despite the high prevalence of the disorder and the need for therapeutic interventions, the accessibility and effectiveness of conventional insomnia treatments remain limited. The electroencephalography (EEG)-neurofeedback control method is based on objective brain activity data to teach the patient self-regulation. This study performed a systematic analysis of current data on the use of neurofeedback technology for the treatment of sleep disorders, assessing the method’s effectiveness and limitations. The search and review of publications from international databases over the past 10 years was performed in accordance with the PRISMA guidelines and the methods described in the RELISH Consortium. The results show that neurofeedback control, in particular, based on individual peak alpha frequency, is a viable and promising therapy. The technology significantly improves subjective and objective sleep parameters, such as reducing sleep latency, increasing total sleep time, and improving sleep quality. With its high efficacy and safety, neurofeedback control can become one of the key components of personalized medicine for the long-term treatment of insomnia and other sleep disorders.
Investigation of neural mechanisms of real-time functional MRI neurofeedback (rtfMRI-nf) training requires an efficient study control approach. A common rtfMRI-nf study design involves an experimental group, receiving active rtfMRI-nf, and a control group, provided with sham rtfMRI-nf. We report the first study in which rtfMRI-nf procedure is controlled through counterbalancing training runs with active and sham rtfMRI-nf for each participant. Healthy volunteers (n = 18) used rtfMRI-nf to upregulate fMRI activity of an individually defined target region in the left dorsolateral prefrontal cortex (DLPFC) while performing tasks that involved mental generation of a random numerical sequence and serial summation of numbers in the sequence. Sham rtfMRI-nf was provided based on fMRI activity of a different brain region, not involved in these tasks. The experimental procedure included two training runs with the active rtfMRI-nf and two runs with the sham rtfMRI-nf, in a randomized order. The participants achieved significantly higher fMRI activation of the left DLPFC target region during the active rtfMRI-nf conditions compared to the sham rtfMRI-nf conditions. fMRI functional connectivity of the left DLPFC target region with the nodes of the central executive network was significantly enhanced during the active rtfMRI-nf conditions relative to the sham conditions. fMRI connectivity of the target region with the nodes of the default mode network was similarly enhanced. fMRI connectivity changes between the active and sham conditions exhibited meaningful associations with individual performance measures on the Working Memory Multimodal Attention Task, the Approach-Avoidance Task, and the Trail Making Test. Our results demonstrate that the counterbalanced active-sham study design can be efficiently used to investigate mechanisms of active rtfMRI-nf in direct comparison to those of sham rtfMRI-nf. Further studies with larger group sizes are needed to confirm the reported findings and evaluate clinical utility of this study control approach.
Poststroke cognitive impairment (PSCI) is a major poststroke complication. Cognitive impairment includes a range of deficits, like reduced semantic fluency, poor concentration, information processing slowing down, memory impairment,difficulty in processing speech, and aphasia. Multiple cognitive domains can be affected by PSCI, such as visuospatial abilities, language, executive functioning, memory and attention. A recent technology, brain computer interface (BCI) is now being used to improve memory, attention, and consciousness in poststroke subjects. The visual P300-BCI spelling system is found to be useful for language training. The covert visual spatial attention (CVSA)-BCI helps to enhance neuroplasticity, reducing the imbalance between hemispheres, and increasing the connectivity between hemispheres. This in turn improves attention, and remedies visuospatial defects. Multimode and multichannel BCI is useful to activate neural plasticity, and improve the relationship between hemispheres. EEG-NF-BCI enables patients to observe a graphical representation of their brain activity, and self-regulate it into an optimal state. In the nonvisual BCI mode based on P300, increase in P300 amplitude indicates the improvement of attention resulting after training. In recent years, due to new developments in BCI technology and brain imaging, real-time fMRI closed-loop training has successfully improved visual attention and behavioral performance. The BCI offers hope of recovery for people with severe physical and cognitive impairments after a stroke.
Introduction: Insomnia affects nearly 1/3 of the worldwide population. Electroencephalography neurofeedback (EEG-NFB) is one of the methods used in applied psychophysiology, which can improve nightly sleep scheme. Research objective: The aim of this pilot study was to assess the relative effect of a 20-day neurorehabilitation intervention based on EEG-NFB therapy in insomnia patients treated at a day rehabilitation centre. Materials and methods: Seventy-four patients with insomnia: 28 women (mean age ± SD: 67.9 ± 8.84 years, range: 42–83 years) and 46 men (mean age ± SD: 63.0 ± 9.24 years, range: 42-80 years) were subjected to the EEG-NFB training-neurorehabilitation using the C4 protocol: sensorimotor rhythm (SMR) (12-15 Hz)/theta (4-7 Hz). The individual everyday EEG-NFB training consisted of 20, 30-minute sessions. Before and after the training, the data was collected from 12-electrode quantitative EEG (QEEG) tests. In addition, several standardised psychological questionnaires were performed: Pittsburgh Sleep Quality Index (PSQI), State-Trait Anxiety Inventory (STAI) and Beck Depression Inventory (BDI). Results: The EEG-NFB therapy reduced anxiety (7.39 ± 1.0 vs. 6.12 ± 0.88 in STAI, p< 0.001) and improved patients' mood (17.6 ± 3.9 vs. 14.65 ± 3.39 in BDI, p< 0.001). During the PSQI test, the time of falling asleep and number of night awakenings were statistically reduced (both p<0.001). However, there was no significant difference in the -SMR amplitude between pre- to post-treatment (9.15 ± 3.11 and 8.62 ± 2.82, respectively, p=0.095). Conclusions: Due to the subjective improvement of sleep quality, without statistically significant changes in the electrophysiological record (expressed by SMR amplitude), it is advisable to continue research with the use of EEG-NFB therapy.
Neurofeedback training (NFT) is a noninvasive neuromodulation method for children with attention-deficit/hyperactivity disorder (ADHD). Brain rhythms, the unique pattern in electroencephalogram (EEG), are widely used as the training target. Most of current studies used a fixed frequency division of brain rhythms, which ignores the individual developmental difference of each child. In this study, we validated the feasibility of NFT using individual beta rhythm. A total of 55 children with ADHD were divided into two groups using the relative power of individual or fixed beta rhythms as the training index. ADHD rating scale (ADHD-RS) was completed before and after NFT, and the EEG and behavioral features were extracted during the training process. After intervention, the attention ability of both groups was significantly improved, showing a significant increase in beta power, a decrease in scores of ADHD-RS and an improvement in behavioral and other EEG features. The training effect was significantly better with individualized beta training, showing more improvement in ADHD-RS scores. Furthermore, the distribution of brain rhythms moved towards high frequency after intervention. This study demonstrates the effectiveness of NFT based on individual beta rhythm for the intervention of children with ADHD. When designing a NFT protocol and the corresponding data analysis process, an individualized brain rhythm division should be applied to reflect the actual brain state and to accurately evaluate the effect of NFT.
Timely relief of anxiety in healthy people is important, but there is little research on this topic at present. Neurofeedback training allows subjects to regulate their specific brain activities autonomously and thus alter their corresponding cognitive functions. Inattention is a significant cognitive deficit in patients with anxiety. Sensorimotor rhythm (SMR) was reported to be closely related to attention. In this study, trainability, frequency specificity, and brain-behavior relationships were utilized to verify the validity of a relative SMR power protocol. An EEG neurofeedback training system was developed for alleviating anxiety levels in healthy people. The EEG data were collected from 33 subjects during SMR up-training sessions. Subjects attended six times neurofeedback training for about 2 weeks. The feedback value of the neurofeedback group was the relative SMR power at the feedback electrode (electrode C3), while the feedback values for the control group were pseudorandom numbers. The trainability index revealed that the learning trend showed an increase in SMR power activity at the C3 electrode, confirming effects across training. The frequency specificity index revealed only that SMR band activity increased significantly in the neurofeedback group. The brain-behavior relationships index revealed that increased SMR activity correlated negatively with the severity of anxiety. This study indicates that neurofeedback training using a relative SMR power protocol, based on activity at the C3 electrode, could relieve anxiety levels for healthy people and increase the SMR power. Preliminary studies support the feasibility and efficacy of the relative SMR power protocol for healthy people with anxiety.
Supplementary information:
The online version contains supplementary material available at 10.1007/s11571-021-09732-8.
Neurofeedback training (NFT) enables users to learn self-control of EEG activity of interest and then to create many benefits on cognitive function. A considerable number of nonresponders who fail to achieve successful NFT have often been reported in the within-session prediction. This study aimed to investigate successful EEG NFT of upregulation alpha activity in terms of trainability, independence, and between-session predictability validation. Forty-six participants completed 12 training sessions. Spectrotemporal analysis revealed the upregulation success on brain activity of 8–12 Hz exclusively to demonstrate trainability and independence of alpha NFT. Three learning indices of between-session changes exhibited significant correlations with eyes-closed resting state (ECRS) alpha amplitude before the training exclusively. Through a stepwise linear discriminant analysis, the prediction model of ECRS’s alpha frequency band amplitude exhibited the best accuracy (89.1%) validation regarding the learning index of increased alpha amplitude on average. This study performed a systematic analysis on NFT success, the performance of the 3 between-session learning indices, and the validation of ECRS alpha activity for responder prediction. The findings would assist researchers in obtaining insight into the training efficacy of individuals and then attempting to adapt an efficient strategy in NFT success.
Sleep disturbances are one of the preventive factors to delay the onset and progression of Alzheimer's disease. Early identification of Alzheimer's disease patients prone to develop sleep disturbances to offer early medical intervention is important. Resting-state functional MRI is a widely used method to investigate the neural mechanisms and find neuroimaging biomarkers in neuropsychiatric diseases. In this study, we applied percent amplitude of fluctuation (PerAF) and mPerAF (divided by global mean PerAF) to test the strength of intrinsic brain activity in 38 mild Alzheimer's disease patients with sleep disturbances (ADSD) and 21 mild Alzheimer's disease patients without sleep disturbances (ADNSD). Compared with ADNSD, we found decreased intrinsic brain activity in the calcarine gyrus, the lingual gyrus, the fusiform gyrus extending to the parahippocampal gyrus, the precentral gyrus, the postcentral gyrus (all in the left hemisphere) and the left brainstem. Conclusively, ADSD exhibited reduced neural activity in specific brain regions related to the sensorimotor network and the visual network, which indicated the contribution of sleep disturbances to the progression of Alzheimer's disease. Especially, the ventral visual pathway to the hippocampus might serve for the memory impaired by sleep disturbances in Alzheimer's disease, and the brainstem might be critical in the initiation of sleep disturbances in Alzheimer's disease. These findings further elucidate the interactions between Alzheimer's disease and sleep disturbances and could help with the early recognition of Alzheimer's disease patients who tend to develop sleep disturbances.
Background: Neurofeedback (NF) training, as a method of self-regulation of brain activity, may be beneficial in elderly patients with mild cognitive impairment (MCI). In this pilot study, we investigated whether a sensorimotor (SMR)/theta NF training could improve cognitive performance and brain electrical activity in elderly patients with MCI. Methods: Twenty elderly patients with MCI were assigned to 20 consecutive sessions of sensorimotor (SMR)/theta NF training, during 10 weeks, on a basis of two sessions each week. Neuropsychological assessments and questionnaires, as well as electroencephalogram (EEG), were performed and compared between baseline (T0), after the last NF training session at 10 weeks (T1), and 1-month follow-up (T2). Results: Repeated measures ANOVA revealed that from baseline to post-intervention, participants showed significant improvement in the Montreal cognitive assessment (MoCa, F = 4.78; p = 0.012), the delayed recall of the Rey auditory verbal learning test (RAVLT, F = 3.675; p = 0.032), the Forward digit span (F = 13.82; p < 0.0001), the Anxiety Goldberg Scale (F = 4.54; p = 0.015), the Wechsler Adult Intelligence Score–Fourth Edition (WAIS-IV; F = 24.75; p < 0.0001), and the Mac Nair score (F = 4.47; p = 0.016). EEG theta power (F = 4.44; p = 0.016) and alpha power (F = 3.84; p = 0.027) during eyes-closed resting-state significantly increased after the NF training and showed sustained improvement at a 1-month follow-up. Conclusion: Our results suggest that NF training could be effective to reduce cognitive deficits in elderly patients with MCI and improve their EEG activity. If these findings are confirmed by randomized controlled studies with larger samples of patients, NF could be seen as a useful non-invasive, non-pharmacological tool for preventing further decline, rehabilitation of cognitive function in the elderly. Clinical Trial Registration: This pilot study was a preliminary step before the trial registered in www.ClinicalTrials.gov, under the number of NCT03526692.
Zespół nadpobudliwości psychoruchowej (ang. attention deficit hyperactivity
disorder – ADHD), to zespół zaburzeń charakteryzujący się deficytem uwagi,
hiperaktywnością oraz impulsywnością, współwystępujący bardzo często z innego
rodzaju dysfunkcjami, w tym ośrodkowych procesów słuchowych. W przypadku dzieci
powoduje to, iż choroba bardzo często stanowi przyczynę różnego rodzaju trudności
szkolnych, problemów emocjonalno-społecznych, zarówno w szkole, jak i w domu.
Jedną z kilku sprawdzonych i stosowanych od lat metod terapii ADHD jest EEG Biofeedback.
Niniejsza praca stanowi studium przypadku dziewięcioletniego chłopca
z zespołem ADHD współwystępującym z deficytami ośrodkowego przetwarzania
słuchowego, którego poddano terapii EEG Biofeedback. Efektywność terapii oceniano
za pomocą wywiadu z rodzicami, kwestionariusza spostrzeżeń rodziców dziecka,
testów behawioralnych badających funkcje poznawcze i wyższe funkcje słuchowe.
Badany był także wpływ terapii na aktywność bioelektryczną mózgu dziecka. Wyniki
analiz porównawczych po treningach pokazały szereg korzystnych zmian zarówno
w normalizacji aktywności mózgu, jak i w funkcjonowaniu poznawczym i słuchowym
chłopca. Po zastosowaniu terapii EEG Biofeedback poprawił się także stan emocjonalny,
jak również zachowanie dziecka, co w konsekwencji wpłynęło pozytywnie na
jego relacje społeczne w szkole i w domu. Uzyskane wyniki wskazują że treningi EEG
Biofeedback mogą stanowić skuteczną metodę terapeutyczną dzieci z ADHD.
Attention deficit hyperactivity disorder – ADHD is a syndrome characterized by
attention deficits, hyperactivity and impulsivity co-morbid often with central auditory
processing dysfunctions. In children it causes then different learning difficulties, socioemotional
problems in school and home environment. Currently, the EEG Biofeedback
is one of the few empirically proven methods employed for years in the ADHD
treatment. This paper present a case study of 9-year-old boy with ADHD co-morbid
with central auditory processing deficits, who was treated with EEG Biofeedback. The
effectiveness of therapy was evaluated by medical history, parent’s observations included
in special questionnaires and behavioral tests examining cognitive and higher
auditory functions. The impact of therapy on the child’s brain bioelectric activity
(EEG) was also tested. The results of study showed normalization of brain activity after
therapy which accompanied both better child’s cognitive and auditory functioning.
After EEG Biofeedback trainings the emotional as well as the behavioral state had also
improved, which in turn had a positive effect on the social relationships of the child in
school and at home. To summarize it could be said that EEG Biofeedback training can
be an effective therapeutic method for children with ADHD.
Neurofeedback (NF) training has been used for the treatment of neuropathic pain. This paper presents the results of assessment of the learning ability of five patients having neuropathic pain. The following two types of baselines were adopted: Baseline 1 refers to power on Day 1 in PreNF state; and Baseline 2 refers to power recorded on each training day in PreNF state. The result of the study demonstrated that not only the baseline its selection is also important to demonstrate the validity of training protocol. It was also found that Baseline 2 can be used to define cut-off time for training (when training should be stopped). All five patients can be classified as learner and alpha band was found to be most relevant for NF training.
EEG-neurofeedback (NF) is used as a training method for altering brain and associated functional activity in healthy individuals and patients alike. Depending on the chosen NF protocol (aiming at enhancing alpha, beta etc. EEG frequency band activity), NF training effects may be rather specific, aiming at ameliorating cognitive or non-cognitive states. We present data of an elderly female patient with minor neurocognitive disorder (MND). As the core symptoms of MND are acquired cognitive impairments due to neurodegenerative processes, NF training effects should be most pronounced regarding disease-related non-cognitive symptoms (i. e., sleeping disturbances and depression). Neuropsychological testing was conducted prior and after termination of the NF training. Two NF protocols (sensorimotor rhythm / SMR and alpha asymmetry / AA) were offered successively, each consisting of 12 sessions with six training blocks. AA NF should reduce depressive symptomatology, while SMR NF should ameliorate sleeping behavior and possibly attention and memory. Overall, our patient with MND exhibited partly positive NF training effects regarding brain electrical activity (i. e., AA, but not SMR) and associated cognitive and non-cognitive functions (i. e., memory and sleep, but not attention or depression). Thus, even in elderly with MND NF training should be regarded as a complementary non-pharmacological treatment for frequently reported disease-related cognitive and behavioral-affective symptoms.
Purpose of Review
Current traditional treatments for ADHD present serious limitations in terms of long-term maintenance of symptom remission and side effects. Here, we provide an overview of the rationale and scientific evidence of the efficacy of neurofeedback in regulating the brain functions in ADHD. We also review the institutional and professional regulation of clinical neurofeedback implementations.
Recent Findings
Based on meta-analyses and (large multicenter) randomized controlled trials, three standard neurofeedback training protocols, namely theta/beta (TBR), sensori-motor rhythm (SMR), and slow cortical potential (SCP), turn out to be efficacious and specific. However, the practical implementation of neurofeedback as a clinical treatment is currently not regulated.
Summary
We conclude that neurofeedback based on standard protocols in ADHD should be considered as a viable treatment alternative and suggest that further research is needed to understand how specific neurofeedback protocols work. Eventually, we emphasize the need for standard neurofeedback training for practitioners and binding standards for use in clinical practice.
Background:
Neurofeedback holds promise as an intervention for the psychophysiological dysfunction found in posttraumatic stress disorder (PTSD). Few empirical studies have assessed the efficacy of neurofeedback for PTSD, and none in individuals with refugee trauma. A proposed mechanism for neurofeedback efficacy in PTSD is through remediating deficits in cognitive control. We assessed pre- and postchanges in symptoms and neurocognitive functioning of refugee clients participating in a neurofeedback intervention for PTSD.
Methods:
Clinical data for 13 adult refugees with chronic PTSD who participated in neurofeedback combined with trauma counseling (NFT) was compared with 13 adult refugees placed on a waitlist to receive neurofeedback. Waitlist clients continued to receive trauma counseling alone (TC). NFT was additionally assessed pre- and posttherapy for changes in event-related potentials (ERPs) and behavioral indices of cognitive control using a visual continuous performance task (VCPT). Comparison VCPT data from healthy controls (HC) was available from the Human Brain Index database.
Results:
Posttherapy, NFT had significantly lower symptoms of trauma, anxiety, and depression compared with TC. NFT demonstrated an increased P3 amplitude and improved behavioral performance suggesting a normalization of cognitive control.
Conclusions:
These preliminary observations are consistent with a possible benefit of neurofeedback for remediating PTSD. This may be achieved at least partially by an improvement in cognitive control. Further confirmation of the effectiveness of the treatment now requires a randomized controlled trial that considers issues such as placebo response, nonspecific therapist effects, and duration of treatment.
It has been well documented that depression can lead to insomnia. However, evidence from previous research and from clinical experience indicates that the reverse can also be the case: long-standing insomnia can often lead to depression. The aim of this study is to test the hypothesis that, for many people suffering from both depression and insomnia, treating the insomnia successfully without medication can lead the depression to lift as well. The sample consisted of 86 consecutive patients or clients who presented as suffering from chronic insomnia. Two thirds of these people were also suffering from depression at intake. During an initial hour-long interview, self-report estimates of key sleep parameters were recorded, and the Beck Depression Inventory was administered. Subjects were then introduced to the "Sleep Better Without Drugs" self-help program (a book and three audio cassettes, which they used at home to improve their sleep. At follow-up, six to eight weeks later, the sleep parameters were recorded again and the Beck Depression Inventory was re-administered. Results showed that 70% of the insomnia sufferers who were depressed before treatment and learned to sleep better were no longer depressed, or were significantly less depressed, once their sleep had improved. By contrast, among people who did not learn to sleep better, none experienced a significant reduction in depression. The conclusion is that, for many people who suffer from both depression and insomnia, treating the insomnia successfully without medication can eliminate or significantly reduce the depression.
Insomnia is a common and clinically important problem. It may arise directly from a sleep-wake regulatory dysfunction and/or indirectly result from comorbid psychiatric, behavioral, medical, or neurological conditions. As an important public-health problem, insomnia requires accurate diagnosis and effective treatment. Insomnia is primarily diagnosed clinically with a detailed medical, psychiatric, and sleep history. Polysomnography is indicated when a sleep-related breathing disorder or periodic limb movement disorder is suspected, initial diagnosis is uncertain, treatment fails, or precipitous arousals occur with violent or injurious behavior. However, polysomnography is not indicated for the routine evaluation of transient insomnia, chronic insomnia, or insomnia associated with psychiatric disorders.
The development of a 21-item self-report inventory for measuring the severity of anxiety in psychiatric populations is described. The initial item pool of 86 items was drawn from three preexisting scales: the Anxiety Checklist, the Physician’s Desk Reference Checklist, and the Situational Anxiety Checklist. A series of analyses was used to reduce the item pool. The resulting Beck Anxiety Inventory (BAI) is a 21-item scale that showed high internal consistency (α = .92) and test—retest reliability over 1 week, r (81) = .75. The BAI discriminated anxious diagnostic groups (panic disorder, generalized anxiety disorder, etc.) from nonanxious diagnostic groups (major depression, dysthymic disorder, etc). In addition, the BAI was moderately correlated with the revised Hamilton Anxiety Rating Scale, r (150) = .51, and was only mildly correlated with the revised Hamilton Depression Rating Scale, r (153) = .25.
Primary insomnia, as defined by DSM-IV-TR, refers to a persistent sleep disturbance which is not connected to a current psychiatric or physical condition, but significantly impairs social and occupational functioning. This study explored the impact of Cognitive Behavioral Therapy for Insomnia (CBT-i) on sleep, daytime functioning and health-related quality of life (HRQoL). Next, we investigated which factors predicted positive treatment outcome by examining demographics, insomnia characteristics, baseline levels of daytime function, HRQoL, sleep-disruptive beliefs and psychological health on post-treatment sleep quality, daytime function and HRQoL. 138 consecutive primary insomnia patients completed questionnaires pre- and post-treatment and at 6 months follow-up. After CBT-i, robust clinical improvements were observed in sleep, daytime function and HRQoL, regardless of age, gender, type or duration of the complaint. Patients with pre-treatment severe insomnia, pronounced daytime impairment and low psychological well-being benefited most.
Electroencephalography (EEG)-neurofeedback has been shown to offer therapeutic benefits to patients with attention-deficit/hyperactivity disorder (ADHD) in several, mostly uncontrolled studies. This pilot study is designed to test the feasibility and safety of using a double-blind placebo feedback-controlled design and to explore the initial efficacy of individualized EEG-neurofeedback training in children with ADHD. Fourteen children (8–15 years) with ADHD defined according to the DSM-IV-TR criteria were randomly allocated to 30 sessions of EEG-neurofeedback (n = 8) or placebo feedback (n = 6). Safety measures (adverse events and sleep problems), ADHD symptoms and global improvement were monitored. With respect to feasibility, all children completed the study and attended all study visits and training sessions. No significant adverse effects or sleep problems were reported. Regarding the expectancy, 75% of children and their parent(s) in the active neurofeedback group and 50% of children and their parent(s) in the placebo feedback group thought they received placebo feedback training. Analyses revealed significant improvements of ADHD symptoms over time, but changes were similar for both groups. This pilot study shows that it is feasible to conduct a rigorous placebo-controlled trial to investigate the efficacy of neurofeedback training in children with ADHD. However, a double-blind design may not be feasible since using automatic adjusted reward thresholds may not work as effective as manually adjusted reward thresholds. Additionally, implementation of active learning strategies may be an important factor for the efficacy of EEG-neurofeedback training. Based on the results of this pilot study, changes are made in the design of the ongoing study.
Electronic supplementary material
The online version of this article (doi:10.1007/s00702-010-0524-2) contains supplementary material, which is available to authorized users.
Insomnia is a sleeping disorder, usually studied from a behavioural perspective, with a focus on somatic and cognitive arousal. Recent studies have suggested that an impairment of information processes due to the presence of cortical hyperarousal might interfere with normal sleep onset and/or consolidation. As such, a treatment modality focussing on CNS arousal, and thus influencing information processing, might be of interest. Seventien insomnia patients were randomly assigned to either a tele-neurofeedback (n = 9) or an electromyography tele-biofeedback (n = 8) protocol. Twelve healthy controls were used to compare baseline sleep measures. A polysomnography was performed pre and post treatment. Total Sleep Time (TST), was considered as our primary outcome variable. Sleep latency decreased pre to post treatment in both groups, but a significant improvement in TST was found only after the neurofeedback (NFB) protocol. Furthermore, sleep logs at home showed an overall improvement only in the neurofeedback group, whereas the sleep logs in the lab remained the same pre to post training. Only NFB training resulted in an increase in TST. The mixed results concerning perception of sleep might be related to methodological issues, such as the different locations of the training and sleep measurements.
About one third of patients with epilepsy do not benefit from medical treatment. For these patients electroencephalographic (EEG) biofeedback is a viable alternative. EEG biofeedback, or neurofeedback, normalizes or enhances EEG activity by means of operant conditioning. While dozens of scientific reports have been published on neurofeedback for seizure disorder, most have been case series with too few subjects to establish efficacy. The purpose of this paper is to meta-analyze existing research on neurofeedback and epilepsy.
We analyzed every EEG biofeedback study indexed in MedLine, PsychInfo, and PsychLit databases between 1970 and 2005 on epilepsy that provided seizure frequency change in response to feedback. Sixty-three studies have been published, 10 of which provided enough outcome information to be included in a meta-analysis. All studies consisted of patients whose seizures were not controlled by medical therapies, which is a very important factor to keep in mind when interpreting the results. Nine of 10 studies reinforced sensorimotor rhythms (SMR) while 1 study trained slow cortical potentials (SCP). All studies reported an overall mean decreased seizure incidence following treatment and 64 out of 87 patients (74%) reported fewer weekly seizures in response to EEG biofeedback. Treatment effect was mean log (post/pre) where pre and post represent number of seizures per week prior to treatment and at final evaluation, respectively. Due to prevalence of small groups, Hedges's g was computed for effect size. As sample heterogeneity was possible (Q test, p=.18), random effects were assumed and the effect of intervention was −0.233, SE= 0.057, z [Formula: see text] −4.11, p<.001.
Based on this meta-analysis, EEG operant conditioning was found to produce a significant reduction on seizure frequency. This finding is especially noteworthy given the patient group, individuals who had been unable to control their seizures with medical treatment.
Study objectives:
While daytime impairment is a defining feature of primary insomnia (PI), prior research using objective measures has not yielded clear and reliable evidence of global or specific deficits. In this investigation subjective and neuropsychological measures of daytime impairment were concurrently evaluated in subjects with primary insomnia (PIs) and in healthy good sleeper subjects (GSs). The goals for the study were to assess (1) whether PIs differ from GSs on subjective and/or objective measures and (2) the extent to which subjective and objective measures provide discordant information.
Design:
Subjects were evaluated on multiple self-report measures of sleep and daytime performance and were administered a comprehensive set of neuropsychological tests.
Setting:
The University of Rochester Sleep and Neurophysiology Research Laboratory (Rochester, NY).
Patients or participants:
Forty-nine subjects (32 PIs and 17 GSs). Seventy-one percent of the sample was female; average age 39 +/- 11 yrs.
Results:
Overall, PIs reported worse sleep, diminished activity levels, and a greater number and severity of daytime complaints. However, PIs did not show deficits on neuropsychological tests. Additionally, neuropsychological measures were not associated with severity of daytime complaints. Objectively measured sleep was found to be associated with performance (motor speed), while prospective and objective sleep measures were associated with level of daytime complaint.
Conclusions:
The discrepancy between subjective daytime complaints and objective performance in individuals with insomnia is common, but poorly understood. This discordance may suggest that daytime impairment corresponds less to "output" and more to attentional bias or to the realistic appraisal that "effort" is required to maintain normal performance.
Insomnia is a common disorder effecting millions of people worldwide. Currently most individuals suffering from insomnia take medications to help them sleep. However, there are a variety of behavioral treatments, which have been shown to be effective in empirical studies that offer many advantages over medications. In addition, behavioral treatments have been shown to be more effective long-term than medication. This paper reviews the principles and practice of these behavioral treatments. At the end of the paper there is also a brief discussion of circadian rhythm disorders that can mimic insomnia.
To compare NREM EEG power in primary insomnia (PI) and good sleeper controls (GSC), examining both sex and NREM period effects; to examine relationships between EEG power, clinical characteristics, and self-reports of sleep.
Overnight polysomnographic study.
Sleep laboratory.
PI (n=48; 29 women) and GSC (n=25; 15 women).
None.
EEG power from 1-50 Hz was computed for artifact-free sleep epochs across four NREM periods. Repeated measures mixed effect models contrasted differences between groups, EEG frequency bands, and NREM periods. EEG power-frequency curves were modeled using regressions with fixed knot splines.
Mixed models showed no significant group (PI vs. GSC) differences; marginal sex differences (delta and theta bands); significant differences across NREM periods; and group*sex and group*NREM period interactions, particularly in beta and gamma bands. Modeled power-frequency curves showed no group difference in whole-night NREM, but PI had higher power than GSC from 18-40 Hz in the first NREM period. Among women, PI had higher 16 to 44-Hz power than GSC in the first 3 NREM periods, and higher 3 to 5-Hz power across all NREM periods. PI and GSC men showed no consistent differences in EEG power. High-frequency EEG power was not related to clinical or subjective sleep ratings in PI.
Women with PI, but not men, showed increased high-frequency and low-frequency EEG activity during NREM sleep compared to GSC, particularly in early NREM periods. Sex and NREM period may moderate quantitative EEG differences between PI and GSC.
To investigate polysomnographic (PSG) sleep and NREM sleep characteristics, including sleep spindles and spectral activity involved in offline consolidation of a motor sequence learning task.
Counterbalanced within-subject design.
Three weekly visits to the sleep laboratory.
Fourteen healthy participants aged between 20 and 30 years (8 women).
Motor sequence learning (MSL) task or motor control (CTRL) task before sleep.
Subjects were trained on either the MSL or CTRL task in the evening and retested 12 hours later the following morning on the same task after a night of PSG sleep recording. Total number and duration of sleep spindles and spectral power between 0.5 and 24 Hz were quantified during NREM sleep. After performing the MSL task, subjects exhibited a large increase in number and duration of sleep spindles compared to after the CTRL task. Higher sigma (sigma; 13 Hz) and beta (beta; 18-20 Hz) spectral power during the post-training night's sleep were also observed after the MSL task.
These results provide evidence that sleep spindles are involved in the offline consolidation of a new sequence of finger movements known to be sleep dependent. Moreover, they expand on prior findings by showing that changes in NREM sleep following motor learning are specific to consolidation (and learning), and not to nonspecific motor activity. Finally, these data demonstrate, for the first time, higher fast rhythms (beta frequencies) during sleep after motor learning.
The purpose of this study was to evaluate the reliability of sleep disorder diagnoses in DSM-III-R by using a newly developed interview, the Structured Interview for Sleep Disorders According to DSM-III-R (SIS-D) and to evaluate the concordance between these diagnoses and sleep laboratory data. In addition, the sources of disagreements between two interviewers in the diagnoses given to the same patient were determined.
Two different interviewers used the SIS-D to diagnose 68 patients with complaints of sleep disorders. The concordance between these interviewers' diagnoses and polysomnographic findings was investigated by using kappa statistics.
There were excellent reliabilities for almost all current main diagnostic categories and good concordance between diagnoses made on the basis of the structured interview and polysomnographic data. The main source of disagreement between interviewers was found in the symptom information given by the patient.
These findings provide support for the utility of DSM-III-R sleep disorder diagnoses and for their retention in DSM-IV. These findings also accord well with a recent literature review of the DSM-III-R diagnosis of primary insomnia by the DSM-IV Work Group on Sleep Disorders. The good concordance between interview diagnoses and polysomnographic data suggests that a structured interview such as the SIS-D may be a useful screening instrument. The authors discuss the implications of these findings for the polysomnographic evaluation of chronic insomnia.
Declarative memory consolidation is enhanced by sleep. In the investigation of underlying mechanisms, mainly rapid eye movement (REM) sleep and slow-wave sleep have been considered. More recently, sleep stage 2 with sleep spindles as a most prominent feature has received increasing attention. Specifically, in rats hippocampal ripples were found to occur in temporal proximity to cortical sleep spindles, indicating an information transfer between the hippocampus and neocortex, which is supposed to underlie the consolidation of declarative memories during sleep. This study in humans looks at the changes in EEG activity during nocturnal sleep after extensive training on a declarative learning task, as compared with a nonlearning control task of equal visual stimulation and subjectively rated cognitive strain. Time spent in each sleep stage, spindle density, and EEG power spectra for 28 electrode locations were determined. During sleep after training, the density of sleep spindles was significantly higher after the learning task as compared with the nonlearning control task. This effect was largest during the first 90 min of sleep (p < 0.01). Additionally, spindle density was correlated to recall performance both before and after sleep (r = 0.56; p < 0.05). Power spectra and time spent in sleep stages did not differ between learning and nonlearning conditions. Results indicate that spindle activity during non-REM sleep is sensitive to previous learning experience.
Insomnia is a highly prevalent, often debilitating, and economically burdensome form of sleep disturbance caused by various situational, medical, emotional, environmental and behavioral factors. Although several consensually-derived nosologies have described numerous insomnia phenotypes, research concerning these phenotypes has been greatly hampered by a lack of widely accepted operational research diagnostic criteria (RDC) for their definition. The lack of RDC has, in turn, led to inconsistent research findings for most phenotypes largely due to the variable definitions used for their ascertainment. Given this problem, the American Academy of Sleep Medicine (AASM) commissioned a Work Group (WG) to review the literature and identify those insomnia phenotypes that appear most valid and tenable. In addition, this WG was asked to derive standardized RDC for these phenotypes and recommend assessment procedures for their ascertainment. This report outlines the WG's findings, the insomnia RDC derived, and research assessment procedures the WG recommends for identifying study participants who meet these RDC.
Insomnia is a condition which affects millions of individuals, giving rise to emotional distress, daytime fatigue, and loss of productivity. Despite its prevalence, it has received scant clinical attention. An adequate evaluation of persistent insomnia requires detailed historical information as well as medical, psychological and psychiatric assessment. Use of a classification system for sleep disorders and familiarity with major diagnostic groups will facilitate the clinician's evaluation and treatment. Thorough assessment also requires attention to the unique aspects of presentation and specific set of etiologies which are associated with particular age groups.
Background:
The paper reports on the development of the WHOQOL-BREF, an abbreyiated version of the WHOQOL-100 quality of life assessment.
Method:
The WHOQOL-BREF was derived from data collected using the WHOQOL-100. It produces scores for four domains related to quality of life: physical health, psychological, social relationships and environment. It also includes one facet on overall quality of life and general health.
Results:
Domain scores produced by the WHOQOL-BREF correlate highly (0.89 or above) with WHOQOL-100 domain scores (calculated on a four domain structure). WHOQOL-BREF domain scores demonstrated good discriminant validity, content validity, internal consistency and test-retest reliability.
Conclusion:
These data suggest that the WHOQOL-BREF provides a valid and reliable alternative to the assessment of domain profiles using the WHOQOL-100. It is envisaged that the WHOQOL-BREF will be most useful in studies that require a brief assessment of quality of life, for example, in large epidemiological studies and clinical trials where quality of life is of interest. In addition, the WHOQOL-BREF may be of use to health professionals in the assessment and evaluation of treatment efficacy.
In the present study, we evaluate the temporal and stagewise distribution of high frequency EEG activity (HFA) in primary and secondary insomnia. Three groups (n=9 per group) were compared: primary insomnia (PI), Insomnia secondary to major depression (MDD), and good sleeper controls (GS). Groups were matched for age, sex and body mass. Average spectral profiles were created for each sleep epoch. Grand averages were created for each NREM cycle and each stage of sleep after removing waking and movement epochs and epochs containing micro or miniarousals. It was found that HFA (in terms of relative power) tends to increase across NREM cycles, occurs maximally during stage 1 and during REM sleep, and that both these effects are exaggerated in patients with PI. In addition, HFA was found to be inversely associated with Delta activity and the three groups in our study appear to exhibit characteristic Delta/Beta patterns. Our data are consistent with the perspective that HFA is related to CNS arousal to the extent that Beta/Gamma activity occurs maximally during shallow stages of sleep and maximally in subjects with PI.
Even though it is known that sleep benefits declarative memory consolidation, the role of sleep in the storage of temporal sequences has rarely been examined. Thus we explored the influence of sleep on temporal order in an episodic memory task followed by sleep or sleep deprivation. Thirty-four healthy subjects (17 men) aged between 19 and 28 years participated in the randomized, counterbalanced, between-subject design. Parameters of interests were NREM/REM cycles, spindle activity and spindle-related EEG power spectra. Participants of both groups (sleep group/sleep deprivation group) performed retrieval in the evening, morning and three days after the learning night. Results revealed that performance in temporal order memory significantly deteriorated over three days only in sleep deprived participants. Furthermore our data showed a positive relationship between the ratios of the (i) first NREM/REM cycle with more REM being associated with delayed temporal order recall. Most interestingly, data additionally indicated that (ii) memory enhancers in the sleep group show more fast spindle related alpha power at frontal electrode sites possibly indicating access to a yet to be consolidated memory trace. We suggest that distinct sleep mechanisms subserve different aspects of episodic memory and are jointly involved in sleep-dependent memory consolidation.
To replicate a previous study, 16 psychophysiological insomniacs were randomly assigned to either Theta feedback or sensorimotor rhythm (SMR) feedback. Evaluations by home sleep logs and by 3 nights in the laboratory were done before biofeedback, immediately after biofeedback, and 9 months later. Results from this study replicate previous findings. Both Theta and SMR feedback seemed effective treatments of insomnia according to home sleep logs. According to evaluations at the sleep laboratory, tense and anxious insomniacs benefited only from Theta feedback but not from SMR feedback, while those who were relaxed at intake but still could not sleep benefited only from SMR but not from Theta feedback.
This paper describes the World Health Organization's project to develop a quality of life instrument (the WHOQOL). It outlines the reasons that the project was undertaken, the thinking that underlies the project, the method that has been followed in its development and the current status of the project. The WHOQOL assesses individuals' perception of their position in life in the context of the culture and value systems in which they live and in relation to their goals, expectations, standards and concerns. It has been developed collaboratively in several culturally diverse centres over four years. Piloting of the WHOQOL on some 4500 respondents in 15 cultural settings has been completed. On the basis of this data the revised WHOQOL Field Trial Form has been finalized, and field testing is currently in progress. The WHOQOL produces a multi-dimensional profile of scores across six domains and 24 sub-domains of quality of life
There is already profound knowledge about the evidence that cognitive behavioral
therapy (CBT) is effective for the treatment of insomnia (Benca, 2005; Morin et al., 1999;
Morin, 2004; Morin et al., 2006). However, the characterization of non-pharmacological
treatment effects like CBT on specific sleep parameters (e.g., sleep spindles, sleep
architecture, electroencephalographic (EEG) power densities during sleep after CBT) are
scarce (Cervena et al., 2004). In our approach we investigated if instrumental
conditioning of 12-15Hz EEG oscillations would enhance sleep quality as well as
declarative memory performance in healthy subjects. Additionally preliminary data
indicating instrumental conditioning of 12-15Hz EEG oscillations as a promising
treatment of insomnia will be presented. EEG recordings over the sensorimotor cortex
show a very distinctive oscillatory pattern in a frequency range between 12-15Hz termed
sensorimotor rhythm (SMR). SMR appears to be dominant during quiet but alert
wakefulness, desynchronizes by the execution of movements and synchronizes by the
inhibition of motor behavior. This frequency range is also known to be high during light
non-rapid eye movement (NREM) sleep, and represents the sleep spindle peak frequency.
In the early 70ies Sterman, Howe, and MacDonald (1970) could demonstrate in cats that
instrumental conditioning of SMR during wakefulness can influence subsequent sleep.
Hauri (1981) was then the first to apply effectively a combination of biofeedback and
neurofeedback to humans suffering from psychophysiologic insomnia. Results revealed
that the patients benefited from the instrumental conditioning protocols. As research
surprisingly stopped at that point, we intended to clarify the effects of instrumental SMR
conditioning (ISC) on sleep quality as well as on declarative memory performance with
today’s technologies and by using a well controlled design which included a control group
receiving the same amount of attention and training. Our results confirmed that within 10
sessions of ISC it is possible to increase 12-15Hz activity significantly. Interestingly, the
increased SMR activity (i) was also expressed during subsequent sleep by eliciting
positive changes in various sleep parameters like sleep spindle number or sleep onset
latency and (ii) was associated with the enhancement of declarative learning. In addition
to these fascinating results, preliminary data from our laboratory point to the possibility
that people suffering from primary insomnia could likewise benefit from this conditioning
protocol as indicated by improved measures of subjective and objective sleep quality.
Question of the study
In the current literature it is still matter of discussion in which ways sleep might be beneficial for memory consolidation/enhancement. Former studies successfully demonstrated that sleep after learning produces greater (procedural/implicit) memory enhancements than equal amounts of waking. As far as naps are concerned, only few studies have been published on this issue; with respect to the influence of naps on declarative/explicit memory performance, there is even a complete lack of empirical data.
Subjects and methods
To find out whether 60-min naps (time in bed) might have a positive effect on declarative memory performance, we tested 22 subjects aged between 19 and 30 years. Subjects were trained on a declarative word-pair association task (prior to sleep) and were tested (cued recall) before and after 1 h of midday napping.
Results
Overall performance was significantly greater after sleep than before the nap. The data indicated that only those participants entering slow wave sleep (M=18.23 min) during the nap showed memory enhancement thereafter. Furthermore, quantitative EEG analyses revealed strong positive associations of (occipital) theta activity during the nap with memory performance enhancement.
Conclusions
In conclusion, the present findings support the sleep-dependent memory consolidation hypothesis and extend its scope to declarative learning in short midday naps.
It has been suggested that healthy sleep facilitates the consolidation of newly acquired memories and underlying brain plasticity. The authors tested the hypothesis that patients with primary insomnia (PI) would show deficits in sleep-related memory consolidation compared to good sleeper controls (GSC). The study used a four-group parallel design (n=86) to investigate the effects of 12 h of night-time, including polysomnographically monitored sleep ('sleep condition' in PI and GSC), versus 12 h of daytime wakefulness ('wake condition' in PI and GSC) on procedural (mirror tracing task) and declarative memory consolidation (visual and verbal learning task). Demographic characteristics and memory encoding did not differ between the groups at baseline. Polysomnography revealed a significantly disturbed sleep profile in PI compared to GSC in the sleep condition. Night-time periods including sleep in GSC were associated with (i) a significantly enhanced procedural and declarative verbal memory consolidation compared to equal periods of daytime wakefulness in GSC and (ii) a significantly enhanced procedural memory consolidation compared to equal periods of daytime wakefulness and night-time sleep in PI. Across retention intervals of daytime wakefulness, no differences between the experimental groups were observed. This pattern of results suggests that healthy sleep fosters the consolidation of new memories, and that this process is impaired for procedural memories in patients with PI. Future work is needed to investigate the impact of treatment on improving sleep and memory.
EEG-feedback, also called neurofeedback, is a training procedure aimed at altering brain activity, and is used as a treatment for disorders like Attention Deficit/Hyperactivity Disorder (ADHD). Studies have reported positive effects of neurofeedback on attention and other dependent variables. However, double-blind studies including a sham neurofeedback control group are lacking. The inclusion of such group is crucial to control for unspecific effects. The current work presents a sham-controlled, double-blind evaluation. The hypothesis was that neurofeedback enhances attention and decreases impulsive behavior. Participants (n=27) were students selected on relatively high scores on impulsivity/inattention questionnaires (Barrat Impulsivity Scale and Broadbent CFQ). They were assigned to a neurofeedback treatment or a sham group. (sham)Neurofeedback training was planned for 15 weeks consisting of a total of 30 sessions, each lasting 22 min. Before and after 16 sessions (i.e., interim analyses), qEEG was recorded and impulsivity and inattention was assessed using a stop signal task and reversed continuous performance task and two questionnaires. Results of the interim analyses showed that participants were blind with respect to group inclusion, but no trend towards an effect of neurofeedback on behavioral measures was observed. Therefore in line with ethical guidelines the experiment was ceased. These results implicate a possible lack of effect of neurofeedback when one accounts for non-specific effects. However, the specific form of feedback and application of the sham-controlled double-blind design may have diminished the effect of neurofeedback.
Neural synchronization in the gamma band has been associated with feature binding and intelligence. Using neurofeedback, we aimed at changing the power of the gamma band and investigated whether these changes would influence behavioral measures of feature binding and intelligence. The results show that people are indeed able to alter the power in the gamma band if provided with neurofeedback. Moreover, the increase of gamma band power was related to a decrease of binding costs and an increase in intelligence, suggesting that the control of feature binding and intelligence share a common underlying mechanism.
Primary insomnia is defined as difficulties in falling asleep, maintaining sleep or non-restorative sleep accompanied by significantly impaired daytime functioning in the absence of a specific physical, mental or substance-related cause. The current review provides substantial support for the concept that hyperarousal processes from the molecular to the higher system level play a key role in the pathophysiology of primary insomnia. Autonomous, neuroendocrine, neuroimmunological, electrophysiological and neuroimaging studies demonstrate increased levels of arousal in primary insomnia during both night and daytime. In the light of neurobiological theories of sleep-wake regulation, primary insomnia may be conceptualized as a final common pathway resulting from the interplay between a genetic vulnerability for an imbalance between arousing and sleep-inducing brain activity, psychosocial/medical stressors and perpetuating mechanisms including dysfunctional sleep-related behavior, learned sleep preventing associations and other cognitive factors like tendency to worry/ruminate.
To test whether instrumental conditioning of sensorimotor rhythm (SMR; 12-15 Hz) has an impact on sleep parameters as well as declarative memory performance in humans.
Randomized, parallel group design
10 instrumental conditioning sessions, pre- and posttreatment investigation including sleep evaluations
27 healthy subjects (13 male) Interventions: SMR-conditioning (experimental group) or randomized-frequency conditioning (control group); declarative memory task before and after a 90-min nap
The experimental group was trained to enhance the amplitude of their SMR-frequency range, whereas the control group participated in a randomized-frequency conditioning program (i.e., every session a different 3-Hz frequency bin between 7 and 20 Hz). During pre- and posttreatment the subjects had to attend the sleep laboratory to take a 90-min nap (2:00-3:30 pm) and to perform a declarative memory task before and after sleep. The experimental design was successful in conditioning an increase in relative 12-15 Hz amplitude within 10 sessions (d = 0.7). Increased SMR activity was also expressed during subsequent sleep by eliciting positive changes in different sleep parameters (sleep spindle number [d = 0.6], sleep onset latency [d = 0.7]); additionally, this increased 12-15 Hz amplitude was associated with enhancement in retrieval score computed at immediate cued recall (d = 0.9).
Relative SMR amplitude increased over 10 instrumental conditioning sessions (in the experimental group only) and this "shaping of one's own brain activity" improved subsequent declarative learning and facilitated the expression of 12-15 Hz spindle oscillations during sleep. Most interestingly, these electrophysiological changes were accompanied by a shortened sleep onset latency.
EEG power spectra of 12 primary, drug-free, sleep-onset insomniacs and 12 age-matched normal sleepers were compared. Subjects slept for 3 consecutive nights in the laboratory, during which EEGs from C3A2 and O1A2 were continuously recorded on FM tape, in addition to standard EOG and EMG leads. The first unambiguous minute of record from each sleep stage, including wakefulness prior to sleep, was selected from the first sleep cycle of night 3. Analog EEG data from 0.5 to 30.5 Hz were digitized at 128 samples/sec, cosine tapered, and subjected to FFT with a resolution of 1 Hz. Sleep latencies of insomniacs (52.0 min) and normals (12.6 min) differed (P less than 0.001). There were no other sleep stage differences. Non-parametric statistics showed that, during wakefulness, insomniacs had significantly more beta activity and less alpha activity than normals. During stage 1, insomniacs had significantly more beta activity than normals. There were no differences during stages 2, 3, or 4. During REM sleep the insomniacs again had significantly more beta activity than the normals. Data from both EEG leads were generally consistent. Thus, insomniacs have increased beta and decreased alpha activity relative to normals prior to the onset of stage 2 sleep. This agrees with our previous finding of increased presleep physiological activity in insomniacs. However, the present data also suggest that a CNS component of this activity, reflected by increased beta EEG, is reactivated during REM sleep.
Despite the prevalence of sleep complaints among psychiatric patients, few questionnaires have been specifically designed to measure sleep quality in clinical populations. The Pittsburgh Sleep Quality Index (PSQI) is a self-rated questionnaire which assesses sleep quality and disturbances over a 1-month time interval. Nineteen individual items generate seven "component" scores: subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbances, use of sleeping medication, and daytime dysfunction. The sum of scores for these seven components yields one global score. Clinical and clinimetric properties of the PSQI were assessed over an 18-month period with "good" sleepers (healthy subjects, n = 52) and "poor" sleepers (depressed patients, n = 54; sleep-disorder patients, n = 62). Acceptable measures of internal homogeneity, consistency (test-retest reliability), and validity were obtained. A global PSQI score greater than 5 yielded a diagnostic sensitivity of 89.6% and specificity of 86.5% (kappa = 0.75, p less than 0.001) in distinguishing good and poor sleepers. The clinimetric and clinical properties of the PSQI suggest its utility both in psychiatric clinical practice and research activities.
Survey data have shown that a minority of people who complain of insomnia receive medical treatment for this problem. Patients who seek treatment for insomnia at medical clinics and sleep disorders centers are a self-selected group who may not be representative of all individuals with insomnia. Fifty patients presenting to a sleep disorders center with an insomnia complaint were compared to 50 subjects with insomnia recruited through the newspaper for psychopharmacological studies. No differences in sleep parameters were found, but significant differences on psychometric measures and in daytime alertness were present. The implications of these differences are discussed.
Persistent psychophysiologic (learned) insomnia (PPI) is an objectively verifiable sleep disturbance that develops secondary to chronic, somatized tension and negative conditioning. Twenty-two patients diagnosed as PPI were compared on sleep and psychological questionnaires to 22 normal subjects (Ns) and to 19 insomnia patients with dysthymic disorders (DD). PPI patients typically had difficulties initiating and maintaining sleep, as did the DDs, but showed normal sleep staging. While PPIs were similar to Ns on most psychological tests, they typically were repressors and sensation avoiders. Many PPI patients suffered from tension-related symptoms such as headaches. PPI patients and Ns revealed less psychopathology than DD patients on almost all psychological scales.
A slow-wave electroencephalographic rhythm recorded from the sensorimotor cortex of the waking cat has been correlated behaviorally
with the suppression of movement. Facilitation of this rhythm through conditioning selectively enhances a similar pattern
recorded during sleep, the familiar spindle burst. The training also produced longer epochs of undisturbed sleep. The specific
neural mechanism manipulated during wakefulness appears to function also in sleep and to be involved with the regulation of
phasic motor behavior.
Synopsis
This is an introductory report for the Brief Symptom Inventory (BSI), a brief psychological self-report symptom scale. The BSI was developed from its longer parent instrument, the SCL-90-R, and psychometric evaluation reveals it to be an acceptable short alternative to the complete scale. Both test-retest and internal consistency reliabilities are shown to be very good for the primary symptom dimensions of the BSI, and its correlations with the comparable dimensions of the SCL-90-R are quite high. In terms of validation, high convergence between BSI scales and like dimensions of the MMPI provide good evidence of convergent validity, and factor analytic studies of the internal structure of the scale contribute evidence of construct validity. Several criterion-oriented validity studies have also been completed with this instrument
To replicate a previous study, 16 psychophysiological insomniacs were randomly assigned to either Theta feedback or sensorimotor rhythm (SMR) feedback. Evaluations by home sleep logs and by 3 nights in the laboratory were done before biofeedback, immediately after biofeedback, and 9 months later. Results from this study replicate previous findings. Both Theta and SMR feedback seemed effective treatments of insomnia according to home sleep logs. According to evaluations at the sleep laboratory, tense and anxious insomniacs benefited only from Theta feedback but not from SMR feedback, while those who were relaxed at intake but still could not sleep benefited only from SMR but not from Theta feedback.
After evaluating 165 insomniacs, 48 psychophysiologic insomniacs were randomly assigned to one of the following four groups: electromyographic (EMG) feedback, combined EMG and theta feedback, sensorimotor rhythm (SMR) feedback, and no treatment (control). Sleep evaluations by home logs and in the laboratory were done before and after biofeedback and nine months later. No feedback group showed improved sleep significantly more than did the controls. The amount of feedback learning correlated significantly with sleep improvement for the SMR group but not for the other groups. Initial tension of the insomniacs correlated positively with sleep improvement for the EMG group, but negatively with sleep improvement for the SMR group. Those treated with the biofeedback that seemed appropriate for their specific deficiencies showed significant sleep improvements, while those who received inappropriate feedback did not. Appropriate biofeedback methods may be effective for specific types of insomnia, but these procedures offer no panacea for all poor sleep.
The paper describes a reliable and valid method for the automatic detection of sleep spindles in whole night polygraphy. The recording of a multi-channel EEG during sleep polysomnography was performed in 10 healthy volunteers aged 20-35 years. This objective method should improve the time-consuming and subjective visual evaluation by increasing the accuracy and allowing the calculation of quantitative variables (i.e., frequency and amplitude), thereby facilitating scientific work with quantitative data. An important part of the method is the treatment of artifacts (i.e., muscle and spindle-like alpha activity). Compared to hardware solutions, our software method has the advantage of higher flexibility in regard to artifact identification and usual spindle definitions.
The morbidity of sleep problems has been well documented; however, they are frequently associated with and are symptomatic of several psychiatric disorders. It is unclear how much of the morbidity can be accounted for by the associated psychiatric and substance abuse disorders and medical problems, and how much by the sleep problems per se. Sleep problems may also be an early sign of a psychiatric problem. This paper reports data from an epidemiologic community survey of over 10,000 adults living in three U.S. communities. A structured diagnostic assessment of psychiatric disorders as well as assessment of the presence of insomnia not due to medical conditions, medication, drug or alcohol abuse, and a 1-year follow-up were completed. Persons with insomnia in the past year without any psychiatric disorders ever (uncomplicated insomnia); with a psychiatric disorder in the past year (complicated insomnia); and with neither insomnia nor psychiatric disorders ever were compared on treatment utilization and the first onset of a psychiatric disorder in the subsequent year. Eight percent of those with uncomplicated as compared with 14.9% with complicated insomnia and 2.5% with neither had sought treatment from the general medical sector for emotional problems in the 6 months prior to the interview. The rates of treatment sought from the psychiatric specialty sector were 3.8%, 9.4%, and 1.2%, respectively. These differences were significant after controlling for sociodemographic characteristics and were sustained when the persons were interviewed 1 year later. Uncomplicated insomnia was also associated with an increase in risk for first onset of major depression, panic disorder, and alcohol abuse over the following year. Insomnia, even in the absence of psychiatric disorders, is associated with increased use of general medical and mental health treatment for emotional problems and for the subsequent first onset in the following year of some psychiatric disorders. Early diagnosis and treatment of uncomplicated insomnia may be useful.
A number of paradoxes are apparent in the assessment and treatment of psychophysiological insomnia and sleep state misperception. Three of these paradoxes exist as discrepancies between polysomnographic (PSG) measures and the subjective impressions regarding sleep quality and quantity. The remaining incongruity exists largely within the objective domain. In the case of subjective-objective discrepancies, patients with insomnia: (1) frequently identify themselves as having been awake when awakened from PSG defined sleep; (2) tend to overestimate sleep latency and underestimate total sleep time as compared with PSG measures; (3) appear to derive more benefit from pharmacotherapy that can be explained by objective gains. The remaining paradox pertains to the observation that hypnotic medications, by and large, do not normalize sleep architecture or produce a more 'sleep-like' EEG. In this paper, we review possible explanations for these various paradoxes, introduce a new perspective and suggest possible research avenues. The model introduced is based on the observation that beta and/or gamma activity (which have been found to be associated with cognitive processes) is enhanced in insomnia at or around sleep onset. We propose that this kind of high frequency EEG activity may interfere with the normal establishment of sleep onset-related mesograde amnesia. As a result, the patient with insomnia maintains a level of information and/or memory processing that blurs the phenomenological distinction between sleep and wakefulness and influences retrospective judgments about sleep initiation and duration.
Insomnia is a condition which affects millions of individuals, giving rise to emotional distress, daytime fatigue, and loss of productivity. Despite its prevalence, it has received scant clinical attention. An adequate evaluation of persistent insomnia requires detailed historical information as well as medical, psychological and psychiatric assessment. Use of a classification system for sleep disorders and familiarity with major diagnostic groups will facilitate the clinician's evaluation and treatment. Thorough assessment also requires attention to the unique aspects of presentation and specific set of etiologies which are associated with particular age groups.
Several studies have shown that patients with insomnia exhibit elevated levels of Beta EEG activity (14-35 Hz) at or around sleep onset and during NREM sleep. In this study, we evaluated 1) the extent to which high frequency EEG activity is limited to the 14-32 Hz domain, 2) whether high frequency EEG activity (HFA) is associated with discrepancies between subjective and PSG measures of sleep continuity, and 3) the extent to which high frequency EEG activity occurs in patients with primary, as opposed to secondary, insomnia.
Three groups (n=9 per group) were compared: Primary Insomnia, Insomnia secondary to Major Depression, and Good Sleeper Controls. Groups were matched for age, sex and body mass. Average spectral profiles were created for each NREM cycle after removing waking and movement epochs and epochs containing micro- or mini-arousals.
Sleep Research Laboratory
Patients with primary and secondary insomnia
N/A.
Subjects with Primary Insomnia exhibited more average NREM activity for Beta-1 (14-20Hz), Beta-2 (20-35Hz) and Gamma activity (35-45Hz) than the other two groups (p.<.01). Group differences were also suggestive for Omega activity (45.0-125Hz) (p.<.10), with MDD subjects tending to exhibit more activity than the other groups. Correlational analyses revealed that average NREM Beta-1 and Beta-2 activity tended to be negatively correlated with subjective-objective discrepancy measures for total sleep time and sleep latency.
Our results confirm that Beta activity is increased in Primary Insomnia. In addition, our data suggest that high frequency activity in patients with Primary Insomnia is limited to the Beta/Gamma range (14-45 Hz), and is negatively associated with the perception of sleep.
Objectives:
Recently, we undertook an empirical review using meta-analytic techniques to assess the extent to which these therapeutic strategies produce comparable outcomes. No differences between the two therapeutic strategies were found, except for sleep latency (SL). Behavior therapy demonstrated a greater reduction in latency to sleep onset as compared to pharmacotherapy. In the present paper, we provide a brief summary of our meta-analysis and then (1) critically review the outcomes and (2) place the findings into a larger context that takes into account what factors represent barriers to treatment and how can we insure that in the future patients will have increased access to behavioral sleep medicine services.
Epidemiologists have published more than 50 studies of insomnia based on data collected in various representative community-dwelling samples or populations. These surveys provide estimates of the prevalence of insomnia according to four definitions: insomnia symptoms, insomnia symptoms with daytime consequences, sleep dissatisfaction and insomnia diagnoses. The first definition, based on insomnia criteria as defined by the DSM-IV, recognizes that about one-third of a general population presents at least one of them. The second definition shows that, when daytime consequences of insomnia are taken into account, the prevalence is between 9% and 15%. The third definition represents 8-18% of the general population. The last definition, more precise and corresponding to a decision-making diagnosis, sets the prevalence at 6% of insomnia diagnoses according to the DSM-IV classification. These four definitions of insomnia have higher prevalence rates in women than in men. The prevalence of insomnia symptoms generally increases with age, while the rates of sleep dissatisfaction and diagnoses have little variation with age. Numerous factors can initiate or maintain insomnia. Mental disorders and organic diseases are the factors that have been the most frequently studied. The association between insomnia and major depressive episodes has been constantly reported: individuals with insomnia are more likely to have a major depressive illness. Longitudinal studies have shown that the persistence of insomnia is associated with the appearance of a new depressive episode. Future epidemiological studies should focus on the natural evolution of insomnia. Epidemiological genetic links of insomnia are yet to be studied.
To date there have been seven studies which find that beta EEG is elevated at around sleep onset and during polysomnographic sleep in patients with insomnia. These findings suggest that insomnia may be characterized by central nervous system (CNS) hyperarousal. In this article, the seven studies are critically reviewed, two theoretical perspectives on beta EEG are presented, and the concept of hyperarousal as a three component process is discussed.
Functional significance of stage 2 sleep spindle activity for declarative memory consolidation.
Randomized, within-subject, multicenter.
Weekly sleep laboratory visits, actigraphy, and sleep diary (4 weeks).
Twenty-four healthy subjects (12 men) aged between 20 and 30 years.
Declarative memory task or nonlearning control task before sleep.
This study measured spindle activity during stage 2 sleep following a (declarative) word-pair association task as compared to a control task. Participants performed a cued recall in the evening after learning (160 word pairs) as well as in the subsequent morning after 8 hours of undisturbed sleep with full polysomnography. Overnight change in the number of recalled words, but not absolute memory performance, correlated significantly with increased spindle activity during the experimental night (r24 = .63, P < .01). Time spent in each sleep stage could not account for this relationship.
A growing body of evidence supports the active role of sleep for information reprocessing. Whereas past research focused mainly on the distinct rapid eye movement and slow-wave sleep, these results indicate that increased sleep stage 2 spindle activity is related to an increase in recall performance and, thus, may reflect memory consolidation.
To date, the only standard for the classification of sleep-EEG recordings that has found worldwide acceptance are the rules published in 1968 by Rechtschaffen and Kales. Even though several attempts have been made to automate the classification process, so far no method has been published that has proven its validity in a study including a sufficiently large number of controls and patients of all adult age ranges. The present paper describes the development and optimization of an automatic classification system that is based on one central EEG channel, two EOG channels and one chin EMG channel. It adheres to the decision rules for visual scoring as closely as possible and includes a structured quality control procedure by a human expert. The final system (Somnolyzer 24 x 7) consists of a raw data quality check, a feature extraction algorithm (density and intensity of sleep/wake-related patterns such as sleep spindles, delta waves, SEMs and REMs), a feature matrix plausibility check, a classifier designed as an expert system, a rule-based smoothing procedure for the start and the end of stages REM, and finally a statistical comparison to age- and sex-matched normal healthy controls (Siesta Spot Report). The expert system considers different prior probabilities of stage changes depending on the preceding sleep stage, the occurrence of a movement arousal and the position of the epoch within the NREM/REM sleep cycles. Moreover, results obtained with and without using the chin EMG signal are combined. The Siesta polysomnographic database (590 recordings in both normal healthy subjects aged 20-95 years and patients suffering from organic or nonorganic sleep disorders) was split into two halves, which were randomly assigned to a training and a validation set, respectively. The final validation revealed an overall epoch-by-epoch agreement of 80% (Cohen's kappa: 0.72) between the Somnolyzer 24 x 7 and the human expert scoring, as compared with an inter-rater reliability of 77% (Cohen's kappa: 0.68) between two human experts scoring the same dataset. Two Somnolyzer 24 x 7 analyses (including a structured quality control by two human experts) revealed an inter-rater reliability close to 1 (Cohen's kappa: 0.991), which confirmed that the variability induced by the quality control procedure, whereby approximately 1% of the epochs (in 9.5% of the recordings) are changed, can definitely be neglected. Thus, the validation study proved the high reliability and validity of the Somnolyzer 24 x 7 and demonstrated its applicability in clinical routine and sleep studies.