Spindle and slow wave rhythms at slow wave sleep transitions are linked to strong shifts in the cortical direct current potential

Neurofeedback as a Treatment Intervention in ADHD: Current Evidence and Practice

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. 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.

Impaired memory consolidation in children with obstructive sleep disordered breathing

Memory consolidation is stabilized and even enhanced by sleep (and particularly by 12-15 Hz sleep spindles in NREM stage 2 sleep) in healthy children but it is unclear what happens to these processes when sleep is disturbed by obstructive sleep disordered breathing. This cross-sectional study investigates differences in declarative memory consolidation among children with primary snoring (PS) and obstructive sleep apnea (OSA) compared to controls. We further investigate whether memory consolidation group differences are associated with NREM stage 2 (N2) sigma (12-15 Hz) or NREM slow oscillation (0.5-1 Hz) spectral power bands. In this study, we trained and tested participants on a spatial declarative memory task with cued recall. Retest occurred after a period of daytime wake (Wake) or a night of sleep (Sleep) with in-lab polysomnography. 36 participants ages 5-9 years completed the protocol: 14 with OSA as defined by respiratory disturbance index (RDI) > 1/hour, 12 with primary snoring (PS) and 10 controls. OSA participants had poorer overall memory consolidation than controls across Wake and Sleep conditions [OSA: mean = -18.7% (5.8), controls: mean = 1.9% (7.2), t = -2.20, P = 0.04]. In contrast, PS participants and controls had comparable memory consolidation across conditions (t = 0.41; P = 0.38). We did not detect a main effect for condition (Sleep, Wake) or group x condition interaction on memory consolidation. OSA participants had lower N2 sigma power than PS (P = 0.03) and controls (P = 0.004) and N2 sigma power inversely correlated with percentage of time snoring on the study night (r = -0.33, P<0.05). Across all participants, N2 sigma power modestly correlated with memory consolidation in both Sleep (r = 0.37, P = 0.03) and Wake conditions (r = 0.44, P = 0.009). Further observed variable path analysis showed that N2 sigma power mediated the relationship between group and mean memory consolidation across Sleep and Wake states [Bindirect = 6.76(3.5), z = 2.03, P = 0.04]. NREM slow oscillation power did not correlate with memory consolidation. All results retained significance after controlling for age and BMI. In sum, participants with mild OSA had impaired memory consolidation and results were mediated by N2 sigma power. These results suggest that N2 sigma power could serve as biomarker of risk for cognitive dysfunction in children with sleep disordered breathing.

How to become an expert: A new perspective on the role of sleep in the mastery of procedural skills

How do you get to Carnegie Hall? Practice, sleep, practice. With enough practice - and sleep - we adopt new strategies that eventually become automatic, and subsequently require only the refinement of the existing skill to become an "expert". It is not known whether sleep is involved in the mastery and refinement of new skills that lead to expertise, nor is it known whether this may be primarily dependent on rapid eye movement (REM), non-REM stage 2 (NREM2) or slow wave sleep (SWS). Here, we employed behavioural and scalp-recorded electroencephalography (EEG) techniques to investigate the post-learning changes in the architecture (e.g., REM, NREM2 and SWS duration) and the electrophysiological features (e.g., rapid eye movements, sleep spindles and slow wave activity) that characterize these sleep states as individuals progress from night to night, from "Novice" to "Experts" on a cognitive procedural task (e.g., the Tower of Hanoi task). Here, we demonstrate that speed of movements improves over the course of training irrespective of whether sleep or wake intervenes training sessions, whereas accuracy improves gradually, but only significantly over a night of sleep immediately prior to mastery of the task. On the night that subjects are first exposed to the task, the density of fast spindles increased significantly during both NREM2 and SWS accompanied by increased NREM2 sigma power and SWS delta power, whereas, on the night that subjects become experts on the task, they show increased REM sleep duration and spindles became larger in terms of amplitude and duration during SWS. Re-exposure to the task one-week after it had already been mastered resulted in increased NREM sleep duration, and again, increased spindle density of fast spindles during SWS and NREM2 and increased NREM2 sigma power and SWS delta power. Importantly, increased spindle density was correlated with overnight improvement in speed and accuracy. Taken together, these results help to elucidate how REM and NREM sleep are uniquely involved in memory consolidation over the course of the mastery of a new cognitively complex skill, and help to resolve controversies regarding sequential nature of memory processing during sleep in humans, for which consistent evidence is currently lacking.

EEG slow-wave coherence changes in propofol-induced general anesthesia: experiment and theory

The electroencephalogram (EEG) patterns recorded during general anesthetic-induced coma are closely similar to those seen during slow-wave sleep, the deepest stage of natural sleep; both states show patterns dominated by large amplitude slow waves. Slow oscillations are believed to be important for memory consolidation during natural sleep. Tracking the emergence of slow-wave oscillations during transition to unconsciousness may help us to identify drug-induced alterations of the underlying brain state, and provide insight into the mechanisms of general anesthesia. Although cellular-based mechanisms have been proposed, the origin of the slow oscillation has not yet been unambiguously established. A recent theoretical study by Steyn-Ross et al. (2013) proposes that the slow oscillation is a network, rather than cellular phenomenon. Modeling anesthesia as a moderate reduction in gap-junction interneuronal coupling, they predict an unconscious state signposted by emergent low-frequency oscillations with chaotic dynamics in space and time. They suggest that anesthetic slow-waves arise from a competitive interaction between symmetry-breaking instabilities in space (Turing) and time (Hopf), modulated by gap-junction coupling strength. A significant prediction of their model is that EEG phase coherence will decrease as the cortex transits from Turing-Hopf balance (wake) to Hopf-dominated chaotic slow-waves (unconsciousness). Here, we investigate changes in phase coherence during induction of general anesthesia. After examining 128-channel EEG traces recorded from five volunteers undergoing propofol anesthesia, we report a significant drop in sub-delta band (0.05-1.5 Hz) slow-wave coherence between frontal, occipital, and frontal-occipital electrode pairs, with the most pronounced wake-vs.-unconscious coherence changes occurring at the frontal cortex.

Self-relaxation training can improve sleep quality and cognitive functions in the older: a one-year randomised controlled trial

AIMS AND OBJECTIVE

To evaluate the effects of self-relaxation training on sleep quality and cognitive functions in the older.

BACKGROUND

Ageing causes declines in sleep quality and cognitive functions in older adults, and decreased sleep quality also accelerates declines in cognitive functions. Therefore, it is necessary to find cost-effective interventions to enhance sleep quality in the older, thereby improving their cognitive functions or delaying cognitive decline.

DESIGN

Randomised controlled study.

METHODS

The study was conducted between July 2010 and June 2011 at Wangyuehu Community in Changsha, China. Eighty older adults with reduced sleep quality were selected and randomly assigned to experimental (n = 40) or control (n = 40) group. Subjects in the experimental group received self-relaxation training including progressive muscle relaxation and meditation based on sleep hygiene education, while the control group received sleep hygiene education only. Sleep quality and cognitive functions of the two groups were measured prior to training and at the end of the 3rd, 6th and 12th months using four reliable and valid questionnaires.

RESULTS

Repeated measures anova revealed that the self-relaxation training had significant main effect as well as interaction effect with time on sleep quality and cognitive functions. Except for scores of Epworth Sleepiness Scale, Mini-Mental State Examination and number memory, time had significant main effect on scores of Pittsburgh Sleep Quality Index, picture memory, associative memory and understanding memory.

CONCLUSION

Self-relaxation training can improve sleep quality and cognitive functions in the older.

RELEVANCE TO CLINICAL PRACTICE

Self-relaxation training is a non-invasive, simple and inexpensive therapeutic method of improving sleep quality and cognitive functions in community-dwelling older people.

Neurofeedback in ADHD and insomnia: vigilance stabilization through sleep spindles and circadian networks

In this review article an overview of the history and current status of neurofeedback for the treatment of ADHD and insomnia is provided. Recent insights suggest a central role of circadian phase delay, resulting in sleep onset insomnia (SOI) in a sub-group of ADHD patients. Chronobiological treatments, such as melatonin and early morning bright light, affect the suprachiasmatic nucleus. This nucleus has been shown to project to the noradrenergic locus coeruleus (LC) thereby explaining the vigilance stabilizing effects of such treatments in ADHD. It is hypothesized that both Sensori-Motor Rhythm (SMR) and Slow-Cortical Potential (SCP) neurofeedback impact on the sleep spindle circuitry resulting in increased sleep spindle density, normalization of SOI and thereby affect the noradrenergic LC, resulting in vigilance stabilization. After SOI is normalized, improvements on ADHD symptoms will occur with a delayed onset of effect. Therefore, clinical trials investigating new treatments in ADHD should include assessments at follow-up as their primary endpoint rather than assessments at outtake. Furthermore, an implication requiring further study is that neurofeedback could be stopped when SOI is normalized, which might result in fewer sessions.

Slow oscillations orchestrating fast oscillations and memory consolidation

Slow-wave sleep (SWS) facilitates the consolidation of hippocampus-dependent declarative memory. Based on the standard two-stage memory model, we propose that memory consolidation during SWS represents a process of system consolidation which is orchestrated by the neocortical <1Hz electroencephalogram (EEG) slow oscillation and involves the reactivation of newly encoded representations and their subsequent redistribution from temporary hippocampal to neocortical long-term storage sites. Indeed, experimental induction of slow oscillations during non-rapid eye movement (non-REM) sleep by slowly alternating transcranial current stimulation distinctly improves consolidation of declarative memory. The slow oscillations temporally group neuronal activity into up-states of strongly enhanced neuronal activity and down-states of neuronal silence. In a feed-forward efferent action, this grouping is induced not only in the neocortex but also in other structures relevant to consolidation, namely the thalamus generating 10-15Hz spindles, and the hippocampus generating sharp wave-ripples, with the latter well known to accompany a replay of newly encoded memories taking place in hippocampal circuitries. The feed-forward synchronizing effect of the slow oscillation enables the formation of spindle-ripple events where ripples and accompanying reactivated hippocampal memory information become nested into the single troughs of spindles. Spindle-ripple events thus enable reactivated memory-related hippocampal information to be fed back to neocortical networks in the excitable slow oscillation up-state where they can induce enduring plastic synaptic changes underlying the effective formation of long-term memories.

The function of the sleep spindle: a physiological index of intelligence and a mechanism for sleep-dependent memory consolidation

Until recently, the electrophysiological mechanisms involved in strengthening new memories into a more permanent form during sleep have been largely unknown. The sleep spindle is an event in the electroencephalogram (EEG) characterizing Stage 2 sleep. Sleep spindles may reflect, at the electrophysiological level, an ideal mechanism for inducing long-term synaptic changes in the neocortex. Recent evidence suggests the spindle is highly correlated with tests of intellectual ability (e.g.; IQ tests) and may serve as a physiological index of intelligence. Further, spindles increase in number and duration in sleep following new learning and are correlated with performance improvements. Spindle density and sigma (14-16Hz) spectral power have been found to be positively correlated with performance following a daytime nap, and animal studies suggest the spindle is involved in a hippocampal-neocortical dialogue necessary for memory consolidation. The findings reviewed here collectively provide a compelling body of evidence that the function of the sleep spindle is related to intellectual ability and memory consolidation.

The contribution of sleep to hippocampus-dependent memory consolidation

There is now compelling evidence that sleep promotes the long-term consolidation of declarative and procedural memories. Behavioral studies suggest that sleep preferentially consolidates explicit aspects of these memories, which during encoding are possibly associated with activation in prefrontal-hippocampal circuitry. Hippocampus-dependent declarative memory benefits particularly from slow-wave sleep (SWS), whereas rapid-eye-movement (REM) sleep seems to benefit procedural aspects of memory. Consolidation of hippocampus-dependent memories relies on a dialog between the neocortex and hippocampus. Crucial features of this dialog are the neuronal reactivation of new memories in the hippocampus during SWS, which stimulates the redistribution of memory representations to neocortical networks; and the neocortical slow (<1Hz) oscillation that synchronizes hippocampal-to-neocortical information transfer to activity in other brain structures.

Sleep to remember

Recently, compelling evidence has accumulated that links sleep to learning and memory. Sleep has been identified as a state that optimizes the consolidation of newly acquired information in memory. Consolidation is an active process that is presumed to rely on the covert reactivation and reorganization of newly encoded representations. Hippocampus-dependent memories benefit primarily from slow-wave sleep (SWS), whereas memories not depending on the hippocampus show greater gains over periods containing high amounts of rapid eye movement sleep. One way sleep does this is by establishing different patterns of neurotransmitters and neurohormone secretion between sleep stages. Another central role for consolidating memories is played by the slow oscillation, that is, the oscillating field potential change dominating SWS. The emergence of slow oscillations in neocortical networks depends on the prior use of these networks for encoding of information. Via efferent pathways, they synchronize the occurrence of sharp wave ripples accompanying memory reactivations in the hippocampus with thalamocortical spindle activity. Thus, hippocampal memories are fed back into neocortical networks at a time when these networks are depolarized and, because of concurrent spindle activity, can most sensitively react to these inputs with plastic changes underlying the formation of long-term memory representations.

The K-complex and slow oscillation in terms of a mean-field cortical model

We use a mean-field macrocolumn model of the cerebral cortex to offer an interpretation of the K-complex of the electroencephalogram to complement those of more detailed neuron-by-neuron models. We interpret the K-complex as a momentary excursion of the cortex from a stable low-firing state to an unstable high-firing state, and hypothesize that the related slow oscillation can be considered as the periodic oscillation between two meta-stable solutions of the mean-field model. By incorporating a Hebbian-style learning rule that links the growth in synapse strength to fluctuations in soma potential, we demonstrate a self-organization behaviour that draws the modelled cortex close to the edge of stability of the low-firing state. Furthermore, a very slow oscillation can occur in the excitability of the cortex that has similarities with the infra-slow oscillation of sleep.

Role of inhibitory feedback for information processing in thalamocortical circuits

The information transfer in the thalamus is blocked dynamically during sleep, in conjunction with the occurrence of spindle waves. In order to describe the dynamic mechanisms which control the sensory transfer of information, it is necessary to have a qualitative model for the response properties of thalamic neurons. As the theoretical understanding of the mechanism remains incomplete, we analyze two modeling approaches for a recent experiment by Le Masson et al. [Nature (London) 417, 854 (2002)] on the thalamocortical loop. We use a conductance based model in order to motivate an extension of the Hindmarsh-Rose model, which mimics experimental observations of Le Masson et al. Typically, thalamic neurons possess two different firing modes, depending on their membrane potential. At depolarized potentials, the cells fire in a single spike mode and relay synaptic inputs in a one-to-one manner to the cortex. If the cell gets hyperpolarized, T-type calcium currents generate burst-mode firing which leads to a decrease in the spike transfer. In thalamocortical circuits, the cell membrane gets hyperpolarized by recurrent inhibitory feedback loops. In the case of reciprocally coupled excitatory and inhibitory neurons, inhibitory feedback leads to metastable self-sustained oscillations, which mask the incoming input, and thereby reduce the information transfer significantly.

Grouping of brain rhythms in corticothalamic systems

Different brain rhythms, with both low-frequency and fast-frequency, are grouped within complex wave-sequences. Instead of dissecting various frequency bands of the major oscillations that characterize the brain electrical activity during states of vigilance, it is conceptually more rewarding to analyze their coalescence, which is due to neuronal interactions in corticothalamic systems. This concept of unified brain rhythms does not only include low-frequency sleep oscillations but also fast (beta and gamma) activities that are not exclusively confined to brain-activated states, since they also occur during slow-wave sleep. The major factor behind this coalescence is the cortically generated slow oscillation that, through corticocortical and corticothalamic drives, is effective in grouping other brain rhythms. The experimental evidence for unified oscillations derived from simultaneous intracellular recordings of cortical and thalamic neurons in vivo, while recent studies in humans using global methods provided congruent results of grouping different types of slow and fast oscillatory activities. Far from being epiphenomena, spontaneous brain rhythms have an important role in synaptic plasticity. The role of slow-wave sleep oscillation in consolidating memory traces acquired during wakefulness is being explored in both experimental animals and human subjects. Highly synchronized sleep oscillations may develop into seizures that are generated intracortically and lead to inhibition of thalamocortical neurons, via activation of thalamic reticular neurons, which may explain the obliteration of signals from the external world and unconsciousness during some paroxysmal states.

Declarative memory consolidation: mechanisms acting during human sleep

Of late, an increasing number of studies have shown a strong relationship between sleep and memory. Here we summarize a series of our own studies in humans supporting a beneficial influence of slow-wave sleep (SWS) on declarative memory formation, and try to identify some mechanisms that might underlie this influence. Specifically, these experiments show that declarative memory benefits mainly from sleep periods dominated by SWS, whereas there is no consistent benefit of this memory from periods rich in rapid eye movement (REM) sleep. A main mechanism of declarative memory formation is believed to be the reactivation of newly acquired memory representations in hippocampal networks that stimulates a transfer and integration of these representations into neocortical neuronal networks. Consistent with this model, spindle activity and slow oscillation-related EEG coherence increase during early sleep after intense declarative learning in humans, signs that together point toward a neocortical reprocessing of the learned material. In addition, sleep seems to provide an optimal milieu for declarative memory reprocessing and consolidation by reducing cholinergic activation and the cortisol feedback to the hippocampus during SWS.

Transcranial direct current stimulation during sleep improves declarative memory

In humans, weak transcranial direct current stimulation (tDCS) modulates excitability in the motor, visual, and prefrontal cortex. Periods rich in slow-wave sleep (SWS) not only facilitate the consolidation of declarative memories, but in humans, SWS is also accompanied by a pronounced endogenous transcortical DC potential shift of negative polarity over frontocortical areas. To experimentally induce widespread extracellular negative DC potentials, we applied anodal tDCS (0.26 mA) [correction] repeatedly (over 30 min) bilaterally at frontocortical electrode sites during a retention period rich in SWS. Retention of declarative memories (word pairs) and also nondeclarative memories (mirror tracing skills) learned previously was tested after this period and compared with retention performance after placebo stimulation as well as after retention intervals of wakefulness. Compared with placebo stimulation, anodal tDCS during SWS-rich sleep distinctly increased the retention of word pairs (p < 0.005). When applied during the wake retention interval, tDCS did not affect declarative memory. Procedural memory was also not affected by tDCS. Mood was improved both after tDCS during sleep and during wake intervals. tDCS increased sleep depth toward the end of the stimulation period, whereas the average power in the faster frequency bands (,alpha, and beta) was reduced. Acutely, anodal tDCS increased slow oscillatory activity <3 Hz. We conclude that effects of tDCS involve enhanced generation of slow oscillatory EEG activity considered to facilitate processes of neuronal plasticity. Shifts in extracellular ionic concentration in frontocortical tissue (expressed as negative DC potentials during SWS) may facilitate sleep-dependent consolidation of declarative memories.