Neurofeedback has begun to attract the attention and scrutiny of the scientific and medical mainstream. Here, neurofeedback researchers present a consensus-derived checklist that aims to improve the reporting and experimental design standards in the field.
1 September 2017 in Neuroscience & Biobehavioral Reviews
Precise temporal coordination of slow oscillations (SO) and sleep spindles is a fundamental mechanism of sleep-dependent memory consolidation. SO and spindle morphology changes considerably throughout development. Critically, it remains unknown how the precise temporal coordination of these two sleep oscillations develops during brain maturation and whether their synchronization indexes the development of memory networks. Here, we use a longitudinal study design spanning from childhood to adolescence, where participants underwent polysomnography and performed a declarative word-pair learning task. Performance on the memory task was better during adolescence. After disentangling oscillatory components from 1/f activity, we found frequency shifts within SO and spindle frequency bands. Consequently, we devised an individualized cross-frequency coupling approach, which demonstrates that SO-spindle coupling strength increases during maturation. Critically, this increase indicated enhanced memory formation from childhood to adolescence. Our results provide evidence that improved coordination between SOs and spindles indexes the development of sleep-dependent memory networks.
See Thibault et al. (doi: 10.1093/awx033 ) for a scientific commentary on this article. Neurofeedback training builds upon the simple concept of instrumental conditioning, i.e. behaviour that is rewarded is more likely to reoccur, an effect Thorndike referred to as the ‘law of effect’. In the case of neurofeedback, information about specific electroencephalographic activity is fed back to the participant who is rewarded whenever the desired electroencephalography pattern is generated. If some kind of hyperarousal needs to be addressed, the neurofeedback community considers sensorimotor rhythm neurofeedback as the gold standard. Earlier treatment approaches using sensorimotor-rhythm neurofeedback indicated that training to increase 12–15 Hz sensorimotor rhythm over the sensorimotor cortex during wakefulness could reduce attention-deficit/hyperactivity disorder and epilepsy symptoms and even improve sleep quality by enhancing sleep spindle activity (lying in the same frequency range). In the present study we sought to critically test whether earlier findings on the positive effect of sensorimotor rhythm neurofeedback on sleep quality and memory could also be replicated in a double-blind placebo-controlled study on 25 patients with insomnia. Patients spent nine polysomnography nights and 12 sessions of neurofeedback and 12 sessions of placebo-feedback training (sham) in our laboratory. Crucially, we found both neurofeedback and placebo feedback to be equally effective as reflected in subjective measures of sleep complaints suggesting that the observed improvements were due to unspecific factors such as experiencing trust and receiving care and empathy from experimenters. In addition, these improvements were not reflected in objective electroencephalographic-derived measures of sleep quality. Furthermore, objective electroencephalographic measures that potentially reflected mechanisms underlying the efficacy of neurofeedback such as spectral electroencephalographic measures and sleep spindle parameters remained unchanged following 12 training sessions. A stratification into ‘true’ insomnia patients and ‘insomnia misperceivers’ (subjective, but no objective sleep problems) did not alter the results. Based on this comprehensive and well-controlled study, we conclude that for the treatment of primary insomnia, neurofeedback does not have a specific efficacy beyond unspecific placebo effects. Importantly, we do not find an advantage of neurofeedback over placebo feedback, therefore it cannot be recommended as an alternative to cognitive behavioural therapy for insomnia, the current (non-pharmacological) standard-of-care treatment. In addition, our study may foster a critical discussion that generally questions the effectiveness of neurofeedback, and emphasizes the importance of demonstrating neurofeedback efficacy in other study samples and disorders using truly placebo and double-blind controlled trials.
Sleep spindles are related to sleep‐dependent memory consolidation and general cognitive abilities. However, they undergo drastic maturational changes during adolescence. Here we used a longitudinal approach (across 7 years) to explore whether developmental changes in sleep spindle density can explain individual differences in sleep‐dependent memory consolidation and general cognitive abilities. Ambulatory polysomnography was recorded during four nights in 34 healthy subjects (24 female) with two nights (baseline and experimental) at initial recording (age range 8–11 years) and two nights at follow‐up recording (age range 14–18 years). For declarative learning, participants encoded word pairs with a subsequent recall before and after sleep. General cognitive abilities were measured by the Wechsler Intelligence Scale. Higher slow (11–13 Hz) than fast (13–15 Hz) spindle density at frontal, central, and parietal sites during initial recordings, followed by a shift to higher fast than slow spindle density at central and parietal sites during follow‐up recordings, suggest that mature spindle topography develops throughout adolescence. Fast spindle density increases from baseline to experimental night were positively related to sleep‐dependent memory consolidation. In addition, we found that the development of fast spindles predicted the improvement in memory consolidation across the two longitudinal measurements, a finding that underlines a crucial role for mature fast spindles for sleep‐dependent memory consolidation. Furthermore, slow spindle changes across adolescence were related to general cognitive abilities, a relationship that could indicate the maturation of frontal networks relevant for efficient cognitive processing. A video abstract of this article can be viewed at: https://www.youtube.com/watch?v=7NXJzm8HbIw and https://www.youtube.com/watch?v=iuMQY1OIJ0s