Cortical plasticity induced by transcranial magnetic stimulation during wakefulness affects electroencephalogram activity during sleep

EEG-based identification system using deep neural networks with frequency features

Improving system security can be achieved through people identification. Among various methods, electroencephalography-based (EEG-based) identification is a dependable way to prevent identity theft and impersonation. Due to the distractions present in the identification environment, such as lack of focus, mental engagement, small body movements, blinking, and other noises, it is essential to analyze data that reflects these conditions. The present research aims to advance practical EEG-based identification by studying data with mental preoccupation and developing a suitable algorithm. In this article, data from a study conducted on a group of 109 individuals has been analyzed. The data is categorized into two groups: focused data and waiting data. The article describes preprocessing the data and extracting three types of features, including Statistical, Frequency, and Wavelet. Then, a deep neural network (DNN) is used to classify the data. The DNN utilizes a multilayer, fully-connected neural network, with the number of layers and neurons varying based on the data type. Optimization and regularization methods are employed to improve the accuracy of the results. The DNN achieved an average accuracy of 99.19% for frequency features over all subjects in the focused data category, while the waiting data category showed an accuracy of 97.81%.

Navigated Transcranial Magnetic Stimulation (nTMS) based Preoperative Planning for Brain Tumor Treatment

Transcranial Magnetic Stimulation (TMS) is a non-invasive technique for analyzing the central and peripheral nervous system. TMS could be a powerful therapeutic technique for neurological disorders. TMS has also shown potential in treating various neurophysiological complications, such as depression, anxiety, and obsessive-compulsive disorders, without pain and analgesics. Despite advancements in diagnosis and treatment, there has been an increase in the prevalence of brain cancer globally. For surgical planning, mapping brain tumors has proven challenging, particularly those localized in expressive regions. Preoperative brain tumor mapping may lower the possibility of postoperative morbidity in surrounding areas. A navigated TMS (nTMS) uses magnetic resonance imaging (MRI) to enable precise mapping during navigated brain stimulation. The resulting magnetic impulses can be precisely applied to the target spot in the cortical region by employing nTMS. This review focuses on nTMS for preoperative planning for brain cancer. This study reviews several studies on TMS and its subtypes in treating cancer and surgical planning. nTMS gives wider and improved dimensions of preoperative planning of the motor-eloquent areas in brain tumor patients. nTMS also predicts postoperative neurological deficits, which might be helpful in counseling patients. nTMS have the potential for finding possible abnormalities in the motor cortex areas.

What is sleep exactly? Global and local modulations of sleep oscillations all around the clock

Wakefulness, non-rapid eye-movement (NREM) and rapid eye-movement (REM) sleep differ from each other along three dimensions: behavioral, phenomenological, physiological. Although these dimensions often fluctuate in step, they can also dissociate. The current paradigm that views sleep as made of global NREM and REM states fail to account for these dissociations. This conundrum can be dissolved by stressing the existence and significance of the local regulation of sleep. We will review the evidence in animals and humans, healthy and pathological brains, showing different forms of local sleep and the consequences on behavior, cognition, and subjective experience. Altogether, we argue that the notion of local sleep provides a unified account for a host of phenomena: dreaming in REM and NREM sleep, NREM and REM parasomnias, intrasleep responsiveness, inattention and mind wandering in wakefulness. Yet, the physiological origins of local sleep or its putative functions remain unclear. Exploring further local sleep could provide a unique and novel perspective on how and why we sleep.

Repetitive Transcranial Magnetic Stimulation of the Primary Motor Cortex beyond Motor Rehabilitation: A Review of the Current Evidence

Transcranial magnetic stimulation (TMS) has emerged as a novel technique to stimulate the human brain through the scalp. Over the years, identifying the optimal brain region and stimulation parameters has been a subject of debate in the literature on therapeutic uses of repetitive TMS (rTMS). Nevertheless, the primary motor cortex (M1) has been a conventional target for rTMS to treat motor symptoms, such as hemiplegia and spasticity, as it controls the voluntary movement of the body. However, with an expanding knowledge base of the M1 cortical and subcortical connections, M1-rTMS has shown a therapeutic efficacy that goes beyond the conventional motor rehabilitation to involve pain, headache, fatigue, dysphagia, speech and voice impairments, sleep disorders, cognitive dysfunction, disorders of consciousness, anxiety, depression, and bladder dysfunction. In this review, we summarize the latest evidence on using M1-rTMS to treat non-motor symptoms of diverse etiologies and discuss the potential mechanistic rationale behind the management of each of these symptoms.

Local sleep: A new concept in brain plasticity

Traditionally, sleep and wakefulness have been considered as two global, mutually exclusive states. However, this view has been challenged by the discovery that sleep and wakefulness are actually locally regulated and that islands of these two states may often coexist in the same individual. Importantly, such a local regulation seems to be the key for many essential functions of sleep, including the maintenance of cognitive efficiency and the consolidation of new skills and memories. Indeed, local changes in sleep-related oscillations occur in brain areas that are used and involved in learning during wakefulness. In turn, these changes directly modulate experience-dependent brain adaptations and the consolidation of newly acquired memories. In line with these observations, alterations in the regional balance between wake- and sleep-like activity have been shown to accompany many pathologic conditions, including psychiatric and neurologic disorders. In the last decade, experimental research has started to shed light on the mechanisms involved in the local regulation of sleep and wakefulness. The results of this research have opened new avenues of investigation regarding the function of sleep and have revealed novel potential targets for the treatment of several pathologic conditions.

How Negative Experience Influences the Brain: A Comprehensive Review of the Neurobiological Underpinnings of Nocebo Hyperalgesia

This comprehensive review summarizes and interprets the neurobiological correlates of nocebo hyperalgesia in healthy humans. Nocebo hyperalgesia refers to increased pain sensitivity resulting from negative experiences and is thought to be an important variable influencing the experience of pain in healthy and patient populations. The young nocebo field has employed various methods to unravel the complex neurobiology of this phenomenon and has yielded diverse results. To comprehend and utilize current knowledge, an up-to-date, complete review of this literature is necessary. PubMed and PsychInfo databases were searched to identify studies examining nocebo hyperalgesia while utilizing neurobiological measures. The final selection included 22 articles. Electrophysiological findings pointed toward the involvement of cognitive-affective processes, e.g., modulation of alpha and gamma oscillatory activity and P2 component. Findings were not consistent on whether anxiety-related biochemicals such as cortisol plays a role in nocebo hyperalgesia but showed an involvement of the cyclooxygenase-prostaglandin pathway, endogenous opioids, and dopamine. Structural and functional neuroimaging findings demonstrated that nocebo hyperalgesia amplified pain signals in the spinal cord and brain regions involved in sensory and cognitive-affective processing including the prefrontal cortex, insula, amygdala, and hippocampus. These findings are an important step toward identifying the neurobiological mechanisms through which nocebo effects may exacerbate pain. Results from the studies reviewed are discussed in relation to cognitive-affective and physiological processes involved in nocebo and pain. One major limitation arising from this review is the inconsistency in methods and results in the nocebo field. Yet, while current findings are diverse and lack replication, methodological differences are able to inform our understanding of the results. We provide insights into the complexities and involvement of neurobiological processes in nocebo hyperalgesia and call for more consistency and replication studies. By summarizing and interpreting the challenging and complex neurobiological nocebo studies this review contributes, not only to our understanding of the mechanisms through which nocebo effects exacerbate pain, but also to our understanding of current shortcomings in this field of neurobiological research.

The Relationship of Transcranial Magnetic Stimulation With Sleep and Plasticity

Neuroplasticity is an area of expanding interest in psychiatry. Plasticity and metaplasticity are processes contributing to the scaling up and down of neuronal connections, and they are involved with changes in learning, memory, mood, and sleep. Effective mood treatments, including repetitive transcranial magnetic stimulation (rTMS), are reputed to work via changes in neuronal circuitry. This article explores the interrelatedness of sleep, plasticity, and rTMS treatment. A PubMed-based literature review was conducted to identify all available studies examining the relationship of rTMS, plasticity, and sleep. Key words used in this search included "TMS," "transcranial magnetic stimulation," "plasticity," "metaplasticity," "sleep," and "insomnia." Depressed mood tends to be associated with impaired neural plasticity, while antidepressant treatments can augment neural plasticity. rTMS impacts plasticity, yielding long-lasting effects, with differing impacts on the waking and sleeping brain. Higher quality sleep promotes plasticity and learning. Reports on the sleep impact of high-frequency and low-frequency rTMS are mixed. The efficacy of rTMS may rely on brain plasticity manipulation, enhanced via the stimulation of neural circuits. Total sleep time and sleep continuity are sleep qualities that are likely necessary but insufficient for the homeostatic plasticity driven by slow-wave sleep. Understanding the relationship between sleep and rTMS treatment is likely critical to enhancing outcomes.

Sleepiness as a Local Phenomenon

Sleep occupies a third of our life and is a primary need for all animal species studied so far. Nonetheless, chronic sleep restriction is a growing source of morbidity and mortality in both developed and developing countries. Sleep loss is associated with the subjective feeling of sleepiness and with decreased performance, as well as with detrimental effects on general health, cognition, and emotions. The ideas that small brain areas can be asleep while the rest of the brain is awake and that local sleep may account for at least some of the cognitive and behavioral manifestations of sleepiness are making their way into the scientific community. We herein clarify the different ways sleep can intrude into wakefulness, summarize recent scientific advances in the field, and offer some hypotheses that help framing sleepiness as a local phenomenon.

Local sleep

The historic sleep regulatory paradigm invokes "top-down" imposition of sleep on the brain by sleep regulatory circuits. While remaining conceptually useful, many sleep phenomena are difficult to explain using that paradigm, including, unilateral sleep, sleep-walking, and poor performance after sleep deprivation. Further, all animals sleep after non-lethal brain lesions, regardless of whether the lesion includes sleep regulatory circuits, suggesting that sleep is a fundamental property of small viable neuronal/glial networks. That small areas of the brain can exhibit non-rapid eye movement sleep-like states is summarized. Further, sleep-like states in neuronal/glial cultures are described. The local sleep states, whether in vivo or in vitro, share electrophysiological properties and molecular regulatory components with whole animal sleep and exhibit sleep homeostasis. The molecular regulatory components of sleep are also involved in plasticity and inflammation. Like sleep, these processes, are initiated by local cell-activity dependent events, yet have at higher levels of tissue organization whole body functions. While there are large literatures dealing with local initiation and regulation of plasticity and inflammation, the literature surrounding local sleep is in its infancy and clinical applications of the local sleep concept are absent. Regardless, the local use-dependent sleep paradigm can advise and advance future research and clinical applications.

Slow-Wave Activity Enhancement to Improve Cognition

Slow-wave activity (SWA), and its coupling with other sleep features, reorganizes cortical circuitry, supporting cognition. This raises the question: can cognition be improved through SWA enhancement? SWA enhancement techniques range from behavioral interventions (such as exercise), which have high feasibility but low specificity, to laboratory-based techniques (such as transcranial stimulation), which have high specificity but are less feasible for widespread use. In this review we describe the pathways through which SWA is enhanced. Pathways encompass enhanced neural activity, increased energy metabolism, and endocrine signaling during wakefulness; also direct enhancement during sleep. We evaluate the robustness and practicality of SWA-enhancement techniques, discuss approaches for determining a causal role of SWA on cognition, and present questions to clarify the mechanisms of SWA-dependent cognitive improvements.

Brain Oscillations in Sport: Toward EEG Biomarkers of Performance

Brain dynamics is at the basis of top performance accomplishment in sports. The search for neural biomarkers of performance remains a challenge in movement science and sport psychology. The non-invasive nature of high-density electroencephalography (EEG) recording has made it a most promising avenue for providing quantitative feedback to practitioners and coaches. Here, we review the current relevance of the main types of EEG oscillations in order to trace a perspective for future practical applications of EEG and event-related potentials (ERP) in sport. In this context, the hypotheses of unified brain rhythms and continuity between wake and sleep states should provide a functional template for EEG biomarkers in sport. The oscillations in the thalamo-cortical and hippocampal circuitry including the physiology of the place cells and the grid cells provide a frame of reference for the analysis of delta, theta, beta, alpha (incl.mu), and gamma oscillations recorded in the space field of human performance. Based on recent neuronal models facilitating the distinction between the different dynamic regimes (selective gating and binding) in these different oscillations we suggest an integrated approach articulating together the classical biomechanical factors (3D movements and EMG) and the high-density EEG and ERP signals to allow finer mathematical analysis to optimize sport performance, such as microstates, coherency/directionality analysis and neural generators.

Modeling the effects of noninvasive transcranial brain stimulation at the biophysical, network, and cognitive level

Noninvasive transcranial brain stimulation (NTBS) is widely used to elucidate the contribution of different brain regions to various cognitive functions. Here we present three modeling approaches that are informed by functional or structural brain mapping or behavior profiling and discuss how these approaches advance the scientific potential of NTBS as an interventional tool in cognitive neuroscience. (i) Leveraging the anatomical information provided by structural imaging, the electric field distribution in the brain can be modeled and simulated. Biophysical modeling approaches generate testable predictions regarding the impact of interindividual variations in cortical anatomy on the injected electric fields or the influence of the orientation of current flow on the physiological stimulation effects. (ii) Functional brain mapping of the spatiotemporal neural dynamics during cognitive tasks can be used to construct causal network models. These models can identify spatiotemporal changes in effective connectivity during distinct cognitive states and allow for examining how effective connectivity is shaped by NTBS. (iii) Modeling the NTBS effects based on neuroimaging can be complemented by behavior-based cognitive models that exploit variations in task performance. For instance, NTBS-induced changes in response speed and accuracy can be explicitly modeled in a cognitive framework accounting for the speed-accuracy trade-off. This enables to dissociate between behavioral NTBS effects that emerge in the context of rapid automatic responses or in the context of slow deliberate responses. We argue that these complementary modeling approaches facilitate the use of NTBS as a means of dissecting the causal architecture of cognitive systems of the human brain.

Wakefulness delta waves increase after cortical plasticity induction

OBJECTIVE

Delta waves (DW) are present both during sleep and in wakefulness. In the first case, DW are considered effectors of synaptic plasticity, while in wakefulness, when they appear in the case of brain lesions, their functional meaning is not unanimously recognized. To throw light on the latter, we aimed to investigate the impact on DW exerted by the cortical plasticity-inducing protocol of intermittent theta burst stimulation (iTBS).

METHODS

Twenty healthy subjects underwent iTBS (11 real iTBS and nine sham iTBS) on the left primary motor cortex with the aim of inducing long-term potentiation (LTP)-like phenomena. Five-minute resting open-eye 32-channel EEG, right opponens pollicis motor-evoked potentials (MEPs), and alertness behavioral scales were collected before and up to 30 min after the iTBS. Power spectral density (PSD), interhemispheric coherence between homologous sensorimotor regions, and intrahemispheric coherence were calculated for the frequency bands ranging from delta to beta.

RESULTS

Real iTBS induced a significant increase of both MEP amplitude and DW PSD lasting up to 30 min after stimulation, while sham iTBS did not. The DW increase was evident over frontal areas ipsilateral and close to the stimulated cortex (electrode F3). Neither real nor sham iTBS induced significant modifications in the PSD of theta, alpha, and beta bands and in the interhemispheric coherence. Behavioral visuo-analogic scales score did not demonstrate changes in alertness after stimulations. No correlations were found between MEP amplitude and PSD changes in the delta band.

CONCLUSIONS

Our data showed that LTP induction in the motor cortex during wakefulness, by means of iTBS, is accompanied by a large and enduring increase of DW over the ipsilateral frontal cortex.

SIGNIFICANCE

The present results are strongly in favor of a prominent role of DW in the neural plasticity processes taking place during the awake state.

A neocortical delta rhythm facilitates reciprocal interlaminar interactions via nested theta rhythms

Delta oscillations (1-4 Hz) associate with deep sleep and are implicated in memory consolidation and replay of cortical responses elicited during wake states. A potent local generator has been characterized in thalamus, and local generators in neocortex have been suggested. Here we demonstrate that isolated rat neocortex generates delta rhythms in conditions mimicking the neuromodulatory state during deep sleep (low cholinergic and dopaminergic tone). The rhythm originated in an NMDA receptor-driven network of intrinsic bursting (IB) neurons in layer 5, activating a source of GABAB receptor-mediated inhibition. In contrast, regular spiking (RS) neurons in layer 5 generated theta-frequency outputs. In layer 2/3 principal cells, outputs from IB cells associated with IPSPs, whereas those from layer 5 RS neurons related to nested bursts of theta-frequency EPSPs. Both interlaminar spike and field correlations revealed a sequence of events whereby sparse spiking in layer 2/3 was partially reflected back from layer 5 on each delta period. We suggest that these reciprocal, interlaminar interactions may represent a "Helmholtz machine"-like process to control synaptic rescaling during deep sleep.

Is sleep essential for neural plasticity in humans, and how does it affect motor and cognitive recovery?

There is a general consensus that sleep is strictly linked to memory, learning, and, in general, to the mechanisms of neural plasticity, and that this link may directly affect recovery processes. In fact, a coherent pattern of empirical findings points to beneficial effect of sleep on learning and plastic processes, and changes in synaptic plasticity during wakefulness induce coherent modifications in EEG slow wave cortical topography during subsequent sleep. However, the specific nature of the relation between sleep and synaptic plasticity is not clear yet. We reported findings in line with two models conflicting with respect to the underlying mechanisms, that is, the “synaptic homeostasis hypothesis” and the “consolidation” hypothesis, and some recent results that may reconcile them. Independently from the specific mechanisms involved, sleep loss is associated with detrimental effects on plastic processes at a molecular and electrophysiological level. Finally, we reviewed growing evidence supporting the notion that plasticity-dependent recovery could be improved managing sleep quality, while monitoring EEG during sleep may help to explain how specific rehabilitative paradigms work. We conclude that a better understanding of the sleep-plasticity link could be crucial from a rehabilitative point of view.

About sleep's role in memory

Over more than a century of research has established the fact that sleep benefits the retention of memory. In this review we aim to comprehensively cover the field of "sleep and memory" research by providing a historical perspective on concepts and a discussion of more recent key findings. Whereas initial theories posed a passive role for sleep enhancing memories by protecting them from interfering stimuli, current theories highlight an active role for sleep in which memories undergo a process of system consolidation during sleep. Whereas older research concentrated on the role of rapid-eye-movement (REM) sleep, recent work has revealed the importance of slow-wave sleep (SWS) for memory consolidation and also enlightened some of the underlying electrophysiological, neurochemical, and genetic mechanisms, as well as developmental aspects in these processes. Specifically, newer findings characterize sleep as a brain state optimizing memory consolidation, in opposition to the waking brain being optimized for encoding of memories. Consolidation originates from reactivation of recently encoded neuronal memory representations, which occur during SWS and transform respective representations for integration into long-term memory. Ensuing REM sleep may stabilize transformed memories. While elaborated with respect to hippocampus-dependent memories, the concept of an active redistribution of memory representations from networks serving as temporary store into long-term stores might hold also for non-hippocampus-dependent memory, and even for nonneuronal, i.e., immunological memories, giving rise to the idea that the offline consolidation of memory during sleep represents a principle of long-term memory formation established in quite different physiological systems.

Local experience-dependent changes in the wake EEG after prolonged wakefulness

STUDY OBJECTIVES

Prolonged wakefulness leads to a progressive increase in sleep pressure, reflected in a global increase in slow wave activity (SWA, 0.5-4.5 Hz) in the sleep electroencephalogram (EEG). A global increase in wake theta activity (5-9 Hz) also occurs. Recently, it was shown that prolonged wakefulness in rodents leads to signs of "local sleep" in an otherwise awake brain, accompanied by a slow/theta wave (2-6 Hz) in the local EEG that occurs at different times in different cortical areas. Compelling evidence in animals and humans also indicates that sleep is locally regulated by the amount of experience-dependent plasticity. Here, we asked whether the extended practice of tasks that involve specific brain circuits results in increased occurrence of local intermittent theta waves in the human EEG, above and beyond the global EEG changes previously described.

DESIGN

Participants recorded with high-density EEG completed 2 experiments during which they stayed awake ≥ 24 h practicing a language task (audiobook listening [AB]) or a visuomotor task (driving simulator [DS]).

SETTING

Sleep laboratory.

PATIENTS OR PARTICIPANTS

16 healthy participants (7 females).

INTERVENTIONS

Two extended wake periods.

MEASUREMENTS AND RESULTS

Both conditions resulted in global increases in resting wake EEG theta power at the end of 24 h of wake, accompanied by increased sleepiness. Moreover, wake theta power as well as the occurrence and amplitude of theta waves showed regional, task-dependent changes, increasing more over left frontal derivations in AB, and over posterior parietal regions in DS. These local changes in wake theta power correlated with similar local changes in sleep low frequencies including SWA.

CONCLUSIONS

Extended experience-dependent plasticity of specific circuits results in a local increase of the wake theta EEG power in those regions, followed by more intense sleep, as reflected by SWA, over the same areas.

Learning and memory

Learning and memory functions are crucial in the interaction of an individual with the environment and involve the interplay of large, distributed brain networks. Recent advances in technologies to explore neurobiological correlates of neuropsychological paradigms have increased our knowledge about human learning and memory. In this chapter we first review and define memory and learning processes from a neuropsychological perspective. Then we provide some illustrations of how noninvasive brain stimulation can play a major role in the investigation of memory functions, as it can be used to identify cause-effect relationships and chronometric properties of neural processes underlying cognitive steps. In clinical medicine, transcranial magnetic stimulation may be used as a diagnostic tool to understand memory and learning deficits in various patient populations. Furthermore, noninvasive brain stimulation is also being applied to enhance cognitive functions, offering exciting translational therapeutic opportunities in neurology and psychiatry.

High density electroencephalography in sleep research: potential, problems, future perspective

High density EEG (hdEEG) during sleep combines the superior temporal resolution of EEG recordings with high spatial resolution. Thus, this method allows a topographical analysis of sleep EEG activity and thereby fosters the shift from a global view of sleep to a local one. HdEEG allowed to investigate sleep rhythms in terms of their characteristic behavior (e.g., the traveling of slow waves) and in terms of their relationship to cortical functioning (e.g., consciousness and cognitive abilities). Moreover, recent studies successfully demonstrated that hdEEG can be used to study brain functioning in neurological and neuro-developmental disorders, and to evaluate therapeutic approaches. This review highlights the potential, the problems, and future perspective of hdEEG in sleep research.

A Neurobiological Model of Insomnia

Insomnia is a common clinical condition resulting in significant costs and morbidity. Previous models of insomnia focusing on psychological and behavioral processes are useful clinically, but lack neurobiological specificity. We propose an insomnia model based on basic and clinical neuroscience findings, and hypothesize that insomnia results from persistent activity in wake-promoting neural structures during NREM sleep. The simultaneous occurrence of sleeping and waking neural activity helps to explain clinical phenomenology and treatment effects in insomnia.

Recalling and forgetting dreams: theta and alpha oscillations during sleep predict subsequent dream recall

Under the assumption that dream recall is a peculiar form of declarative memory, we have hypothesized that (1) the encoding of dream contents during sleep should share some electrophysiological mechanisms with the encoding of episodic memories of the awake brain and (2) recalling a dream(s) after awakening from non-rapid eye movement (NREM) and rapid eye movement (REM) sleep should be associated with different brain oscillations. Here, we report that cortical brain oscillations of human sleep are predictive of successful dream recall. In particular, after morning awakening from REM sleep, a higher frontal 5-7 Hz (theta) activity was associated with successful dream recall. This finding mirrors the increase in frontal theta activity during successful encoding of episodic memories in wakefulness. Moreover, in keeping with the different EEG background, a different predictive relationship was found after awakening from stage 2 NREM sleep. Specifically, a lower 8-12 Hz (alpha) oscillatory activity of the right temporal area was associated with a successful dream recall. These findings provide the first evidence of univocal cortical electroencephalographic correlates of dream recall, suggesting that the neurophysiological mechanisms underlying the encoding and recall of episodic memories may remain the same across different states of consciousness.

Electrophysiological correlates of sleep homeostasis in freely behaving rats

The electrical activity of the brain does not only reflect the current level of arousal, ongoing behavior, or involvement in a specific task but is also influenced by what kind of activity, and how much sleep and waking occurred before. The best marker of sleep-wake history is the electroencephalogram (EEG) spectral power in slow frequencies (slow-wave activity, 0.5-4 Hz, SWA) during sleep, which is high after extended wakefulness and low after consolidated sleep. While sleep homeostasis has been well characterized in various species and experimental paradigms, the specific mechanisms underlying homeostatic changes in brain activity or their functional significance remain poorly understood. However, several recent studies in humans, rats, and computer simulations shed light on the cortical mechanisms underlying sleep regulation. First, it was found that the homeostatic changes in SWA can be fully accounted for by the variations in amplitude and slope of EEG slow waves, which are in turn determined by the efficacy of corticocortical connectivity. Specifically, the slopes of sleep slow waves were steeper in early sleep compared to late sleep. Second, the slope of cortical evoked potentials, which is an established marker of synaptic strength, was steeper after waking, and decreased after sleep. Further, cortical long-term potentiation (LTP) was partially occluded if it was induced after a period of waking, but it could again be fully expressed after sleep. Finally, multiunit activity recordings during sleep revealed that cortical neurons fired more synchronously after waking, and less so after a period of consolidated sleep. The decline of all these electrophysiological measures-the slopes of slow waves and evoked potentials and neuronal synchrony-during sleep correlated with the decline of the traditional marker of sleep homeostasis, EEG SWA. Taken together, these data suggest that homeostatic changes in sleep EEG are the result of altered neuronal firing and synchrony, which in turn arise from changes in functional neuronal connectivity.

Linking oligodendrocyte and myelin dysfunction to neurocircuitry abnormalities in schizophrenia

Multiple lines of evidence in schizophrenia, from brain imaging, studies in postmortem brains, and genetic association studies, have implicated oligodendrocyte and myelin dysfunction in this disease. Recent studies suggest that oligodendrocyte and myelin dysfunction leads to changes in synaptic formation and function, which could lead to cognitive dysfunction, a core symptom of schizophrenia. Furthermore, there is accumulating data linking oligodendrocyte and myelin dysfunction with dopamine and glutamate abnormalities, both of which are found in schizophrenia. These findings implicate oligodendrocyte and myelin dysfunction as a primary change in schizophrenia, not only as secondary consequences of the illness or treatment. Strategies targeting oligodendrocyte and myelin abnormalities could therefore provide therapeutic opportunities for patients suffering from schizophrenia.

Slow wave activity during sleep: functional and therapeutic implications

Electroencephalographic slow-wave activity (EEG SWA) is an electrophysiological signature of slow (0.5 to 4.0 Hz), synchronized, oscillatory neocortical activity. In healthy individuals, EEG SWA is maximally expressed during non-rapid-eye-movement (non-REM) sleep, and intensifies as a function of prior wake duration. Many of the cellular and network mechanisms generating EEG SWA have been identified, but a number of questions remain unanswered. For example, although EEG SWA is a marker of sleep need, its precise relationship with sleep homeostasis and its roles in the brain are unknown. In this review, the authors discuss their current understanding of the neural mechanisms and possible functions of EEG SWA.

Enhancing plasticity through repeated rTMS sessions: the benefits of a night of sleep

OBJECTIVE

Previous work has demonstrated that corticospinal facilitation from 20Hz repetitive transcranial magnetic stimulation (rTMS) was greater during a second rTMS session 24h after the first. We sought to determine whether such metaplasticity is dependent on a particular phase of the normal sleep-wake/circadian cycle.

METHODS

Twenty healthy participants received two sessions of 20Hz rTMS over the hand motor cortex (M1) spaced 12h apart, either over-day or overnight.

RESULTS

Baseline corticospinal excitability did not differ by group or session. The time-of-day of Session 1 did not influence the relative increase in excitability following rTMS. However, the increase in excitability from the second rTMS session was 2-fold greater in the overnight group.

CONCLUSIONS

When a night with sleep follows rTMS to M1, the capacity to induce subsequent plasticity in M1 is enhanced, suggesting sleep-wake and/or circadian-dependent modulation of processes of metaplasticity.

SIGNIFICANCE

TMS treatment of neuropsychiatric disorders entails repeated sessions of rTMS. Our findings suggest that the timing of sessions relative to the sleep-wake/circadian cycle may be a critical factor in the cumulative effect of treatment. Future studies using this paradigm may provide mechanistic insights into human metaplasticity, leading to refined strategies to enhance non-invasive stimulation therapies.

The effects of morning training on night sleep: a behavioral and EEG study

The consolidation of memories in a variety of learning processes benefits from post-training sleep, and recent work has suggested a role for sleep slow wave activity (SWA). Previous studies using a visuomotor learning task showed a local increase in sleep SWA in right parietal cortex, which was correlated with post-sleep performance enhancement. In these as in most similar studies, learning took place in the evening, shortly before sleep. Thus, it is currently unknown whether learning a task in the morning, followed by the usual daily activities, would also result in a local increase in sleep SWA during the night, and in a correlated enhancement in performance the next day. To answer this question, a group of subjects performed a visuomotor learning task in the morning and was retested the following morning. Whole night sleep was recorded with high-density EEG. We found an increase of SWA over the right posterior parietal areas that was most evident during the second sleep cycle. Performance improved significantly the following morning, and the improvement was positively correlated with the SWA increase in the second sleep cycle. These results suggest that training-induced changes in sleep SWA and post-sleep improvements do not depend upon the time interval between original training and sleep.

The slow (<1 Hz) rhythm of non-REM sleep: a dialogue between three cardinal oscillators

The slow (<1 Hz) rhythm, the most important electroencephalogram (EEG) signature of non-rapid eye movement (NREM) sleep, is generally viewed as originating exclusively from neocortical networks. Here we argue that the full manifestation of this fundamental sleep oscillation in a corticothalamic module requires the dynamic interaction of three cardinal oscillators: one predominantly synaptically based cortical oscillator and two intrinsic, conditional thalamic oscillators. The functional implications of this hypothesis are discussed in relation to other EEG features of NREM sleep, with respect to coordinating activities in local and distant neuronal assemblies and in the context of facilitating cellular and network plasticity during slow-wave sleep.

Functional structure of spontaneous sleep slow oscillation activity in humans

Background

During non-rapid eye movement (NREM) sleep synchronous neural oscillations between neural silence (down state) and neural activity (up state) occur. Sleep Slow Oscillations (SSOs) events are their EEG correlates. Each event has an origin site and propagates sweeping the scalp. While recent findings suggest a SSO key role in memory consolidation processes, the structure and the propagation of individual SSO events, as well as their modulation by sleep stages and cortical areas have not been well characterized so far.

Methodology/Principal Findings

We detected SSO events in EEG recordings and we defined and measured a set of features corresponding to both wave shapes and event propagations. We found that a typical SSO shape has a transition to down state, which is steeper than the following transition from down to up state. We show that during SWS SSOs are larger and more locally synchronized, but less likely to propagate across the cortex, compared to NREM stage 2. Also, the detection number of SSOs as well as their amplitudes and slopes, are greatest in the frontal regions. Although derived from a small sample, this characterization provides a preliminary reference about SSO activity in healthy subjects for 32-channel sleep recordings.

Conclusions/Significance

This work gives a quantitative picture of spontaneous SSO activity during NREM sleep: we unveil how SSO features are modulated by sleep stage, site of origin and detection location of the waves. Our measures on SSOs shape indicate that, as in animal models, onsets of silent states are more synchronized than those of neural firing. The differences between sleep stages could be related to the reduction of arousal system activity and to the breakdown of functional connectivity. The frontal SSO prevalence could be related to a greater homeostatic need of the heteromodal association cortices.

Slow waves, synaptic plasticity and information processing: insights from transcranial magnetic stimulation and high-density EEG experiments

Sleep slow waves are the main phenomenon underlying NREM sleep. They are homeostatically regulated, they are thought to be linked to learning and plasticity processes and, at the same time, they are associated with marked changes in cortical information processing. Using transcranial magnetic stimulation (TMS) and high-density (hd) EEG we can measure slow waves, induce and measure plastic changes in the cerebral cortex and directly assess corticocortical information transmission. In this manuscript we review the results of recent experiments in which TMS with hd-EEG is used to demonstrate (i) a causal link between cortical plastic changes and sleep slow waves and (ii) a causal link between slow waves and the decreased ability of thalamocortical circuits to integrate information and to generate conscious experience during NREM sleep. The data presented here suggest a unifying mechanism linking slow waves, plasticity and cortical information integration; moreover, they suggest that TMS can be used as a nonpharmacological means to controllably induce slow waves in the human cerebral cortex.

Consensus paper: combining transcranial stimulation with neuroimaging

In the last decade, combined transcranial magnetic stimulation (TMS)-neuroimaging studies have greatly stimulated research in the field of TMS and neuroimaging. Here, we review how TMS can be combined with various neuroimaging techniques to investigate human brain function. When applied during neuroimaging (online approach), TMS can be used to test how focal cortex stimulation acutely modifies the activity and connectivity in the stimulated neuronal circuits. TMS and neuroimaging can also be separated in time (offline approach). A conditioning session of repetitive TMS (rTMS) may be used to induce rapid reorganization in functional brain networks. The temporospatial patterns of TMS-induced reorganization can be subsequently mapped by using neuroimaging methods. Alternatively, neuroimaging may be performed first to localize brain areas that are involved in a given task. The temporospatial information obtained by neuroimaging can be used to define the optimal site and time point of stimulation in a subsequent experiment in which TMS is used to probe the functional contribution of the stimulated area to a specific task. In this review, we first address some general methodologic issues that need to be taken into account when using TMS in the context of neuroimaging. We then discuss the use of specific brain mapping techniques in conjunction with TMS. We emphasize that the various neuroimaging techniques offer complementary information and have different methodologic strengths and weaknesses.

From creation to consolidation: a novel framework for memory processing

Long after playing squash, your brain continues to process the events that occurred during the game, thereby improving your game, and more generally, enhancing adaptive behavior. Understanding these mysterious processes may require novel theories.