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

Intracortical mechanisms of single pulse electrical stimulation (SPES) evoked excitations and inhibitions in humans

Cortico-cortical evoked potentials (CCEPs) elicited by single-pulse electric stimulation (SPES) are widely used to assess effective connectivity between cortical areas and are also implemented in the presurgical evaluation of epileptic patients. Nevertheless, the cortical generators underlying the various components of CCEPs in humans have not yet been elucidated. Our aim was to describe the laminar pattern arising under SPES evoked CCEP components (P1, N1, P2, N2, P3) and to evaluate the similarities between N2 and the downstate of sleep slow waves. We used intra-cortical laminar microelectrodes (LMEs) to record CCEPs evoked by 10 mA bipolar 0.5 Hz electric pulses in seven patients with medically intractable epilepsy implanted with subdural grids. Based on the laminar profile of CCEPs, the latency of components is not layer-dependent, however their rate of appearance varies across cortical depth and stimulation distance, while the seizure onset zone does not seem to affect the emergence of components. Early neural excitation primarily engages middle and deep layers, propagating to the superficial layers, followed by mainly superficial inhibition, concluding in a sleep slow wave-like inhibition and excitation sequence.

Sleep spindles as neurophysiological biomarkers of schizophrenia

Schizophrenia (SCZ) is a complex psychiatric disorder characterized by a wide range of clinical symptoms, including disrupted sleep. In recent years, there has been growing interest in assessing alterations in sleep parameters in patients with SCZ. Sleep spindles are brief (0.5-2 s) bursts of 12- to 16-Hz rhythmic electroencephalogram (EEG) oscillatory activity occurring during non-rapid eye movement (NREM) sleep. Spindles have been implicated in several critical brain functions, including learning, memory and plasticity, and are thought to reflect the integrity of underlying thalamocortical circuits. This review aims to provide an overview of the current research investigating sleep spindles in SCZ. After briefly describing the neurophysiological features of sleep spindles, I will discuss alterations in spindle characteristics observed in SCZ, their associations with the clinical symptomatology of these patients and their putative underlying neuronal and molecular mechanisms. I will then discuss the utility of sleep spindle measures as predictors of treatment response and disease progression. Finally, I will highlight future directions for research in this emerging field, including the prospect of utilizing sleep spindles as neurophysiological biomarkers of SCZ.

Electrophysiological findings in migraine may reflect abnormal synaptic plasticity mechanisms: A narrative review

BACKGROUND

The cyclical brain disorder of sensory processing accompanying migraine phases lacks an explanatory unified theory.

METHODS

We searched Pubmed for non-invasive neurophysiological studies on migraine and related conditions using transcranial magnetic stimulation, electroencephalography, visual and somatosensory evoked potentials. We summarized the literature, reviewed methods, and proposed a unified theory for the pathophysiology of electrophysiological abnormalities underlying migraine recurrence.

RESULTS

All electrophysiological modalities have determined specific changes in brain dynamics across the different phases of the migraine cycle. Transcranial magnetic stimulation studies show unbalanced recruitment of inhibitory and excitatory circuits, more consistently in aura, which ultimately results in a substantially distorted response to neuromodulation protocols. Electroencephalography investigations highlight a steady pattern of reduced alpha and increased slow rhythms, largely located in posterior brain regions, which tends to normalize closer to the attacks. Finally, non-painful evoked potentials suggest dysfunctions in habituation mechanisms of sensory cortices that revert during ictal phases.

CONCLUSION

Electrophysiology shows dynamic and recurrent functional alterations within the brainstem-thalamus-cortex loop varies continuously and recurrently in migraineurs. Given the central role of these structures in the selection, elaboration, and learning of sensory information, these functional alterations suggest chronic, probably genetically determined dysfunctions of the synaptic short- and long-term learning mechanisms.

Coupling between the prelimbic cortex, nucleus reuniens, and hippocampus during NREM sleep remains stable under cognitive and homeostatic demands

The interplay between the medial prefrontal cortex and hippocampus during non-rapid eye movement (NREM) sleep contributes to the consolidation of contextual memories. To assess the role of the thalamic nucleus reuniens (Nre) in this interaction, we investigated the coupling of neuro-oscillatory activities among prelimbic cortex, Nre, and hippocampus across sleep states and their role in the consolidation of contextual memories using multi-site electrophysiological recordings and optogenetic manipulations. We showed that ripples are time-locked to the Up state of cortical slow waves, the transition from UP to DOWN state in thalamic slow waves, the troughs of cortical spindles, and the peaks of thalamic spindles during spontaneous sleep, rebound sleep and sleep following a fear conditioning task. In addition, spiking activity in Nre increased before hippocampal ripples, and the phase-locking of hippocampal ripples and thalamic spindles during NREM sleep was stronger after acquisition of a fear memory. We showed that optogenetic inhibition of Nre neurons reduced phase-locking of ripples to cortical slow waves in the ventral hippocampus whilst their activation altered the preferred phase of ripples to slow waves in ventral and dorsal hippocampi. However, none of these optogenetic manipulations of Nre during sleep after acquisition of fear conditioning did alter sleep-dependent memory consolidation. Collectively, these results showed that Nre is central in modulating hippocampus and cortical rhythms during NREM sleep.

Sleep, learning, and memory in human research using noninvasive neuroimaging techniques

An accumulating body of evidence indicates that sleep is beneficial for learning and memory. Task performance improves significantly after a period that includes sleep, whereas a lack of sleep nullifies or impairs such improvements. Our current knowledge about sleep's role in learning and memory has been obtained based on studies that were conducted in both animal models and human subjects. Nevertheless, how sleep promotes learning and memory in humans is not fully understood. In this review, we overview our current understating of how sleep may contribute to learning and memory, covering different roles of non-rapid eye movement and rapid eye movement sleep. We then discuss cutting-edge advanced techniques that are currently available, including simultaneous functional magnetic resonance imaging (fMRI) and electroencephalogram (EEG) and simultaneous functional magnetic resonance spectroscopy (fMRS) and EEG measurements, and evaluate how these may contribute to advance the understanding of the role of sleep in human cognition. We also highlight the current limitations and challenges using these methods and discuss ways that may allow us to overcome these limitations.

Dissociable neural mechanisms of cognition and well-being in youth versus healthy aging

Mental health, cognition, and their underlying neural processes in healthy aging are rarely studied simultaneously. Here, in a sample of healthy younger (n = 62) and older (n = 54) adults, we compared subjective mental health as well as objective global cognition across several core cognitive domains with simultaneous electroencephalography (EEG). We found significantly greater symptoms of anxiety, depression, and loneliness in youth and in contrast, greater mental well-being in older adults. Yet, global performance across core cognitive domains was significantly worse in older adults. EEG-based source imaging of global cognitive task-evoked processing showed reduced suppression of activity in the anterior medial prefrontal default mode network (DMN) region in older adults relative to youth. Global cognitive performance efficiency was predicted by greater activity in the right dorsolateral prefrontal cortex in younger adults and in contrast, by greater activity in right inferior frontal cortex in older adults. Furthermore, greater mental well-being in older adults related to lesser global task-evoked activity in the posterior DMN. Overall, these results suggest dissociated neural mechanisms underlying global cognition and mental well-being in youth versus healthy aging. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Brain Stimulation for Improving Sleep and Memory

Over the past few decades, the importance of sleep has become increasingly recognized for many physiologic functions, including cognition. Many studies have reported the deleterious effect of sleep loss or sleep disruption on cognitive performance. Beyond ensuring adequate sleep quality and duration, discovering methods to enhance sleep to augment its restorative effects is important to improve learning in many populations, such as the military, students, age-related cognitive decline, and cognitive disorders.

Impairment of sleep homeostasis in cervical dystonia patients

Alterations in brain plasticity seem to play a role in the pathophysiology of cervical dystonia (CD). Since evidences indicate that sleep regulates brain plasticity, we hypothesized that an alteration in sleep homeostatic mechanisms may be involved in the pathogenesis of CD. We explored sleep in control subjects (CTL) and CD patients before (T_pre-BoNT) and after (T_post-BoNT) botulinum toxin (BoNT) treatment. A physiological slow wave activity (SWA) power decrease throughout the night was observed in CTL but not in CD at T_pre-BoNT. BoNT restored the physiological SWA decrease in CD at T_post-BoNT. Furthermore, in the first part of the night, CD at T_post-BNT showed a frontal increase and parietal decrease in SWA power compared to CD at T_pre-BoNT, with a SWA distribution comparable to that observed in CTL. Our data highlighted a pathophysiological relationship between SWA during sleep and CD and provided novel insight into the transient central plastic effect of BoNT.

Quantifying arousal and awareness in altered states of consciousness using interpretable deep learning

Consciousness can be defined by two components: arousal (wakefulness) and awareness (subjective experience). However, neurophysiological consciousness metrics able to disentangle between these components have not been reported. Here, we propose an explainable consciousness indicator (ECI) using deep learning to disentangle the components of consciousness. We employ electroencephalographic (EEG) responses to transcranial magnetic stimulation under various conditions, including sleep (n = 6), general anesthesia (n = 16), and severe brain injury (n = 34). We also test our framework using resting-state EEG under general anesthesia (n = 15) and severe brain injury (n = 34). ECI simultaneously quantifies arousal and awareness under physiological, pharmacological, and pathological conditions. Particularly, ketamine-induced anesthesia and rapid eye movement sleep with low arousal and high awareness are clearly distinguished from other states. In addition, parietal regions appear most relevant for quantifying arousal and awareness. This indicator provides insights into the neural correlates of altered states of consciousness.

Sleep and homeostatic control of plasticity

Sleep homeostasis is a complex neurobiologic phenomenon involving a number of molecular pathways, neurotransmitter release, synaptic activity, and factors modulating neural networks. Sleep plasticity allows for homeostatic optimization of neural networks and the replay-based consolidation of specific circuits, especially important for cognition, behavior, and information processing. Furthermore, research is currently moving from an essentially brain-focused to a more comprehensive view involving other systems, such as the immune system, hormonal status, and metabolic pathways. When dysfunctional, these systems contribute to sleep loss and fragmentation as well as to sleep need. In this chapter, the implications of neural plasticity and sleep homeostasis for the diagnosis and treatment of some major sleep disorders, such as insomnia and sleep deprivation, obstructive sleep apnea syndrome, restless legs syndrome, REM sleep behavior disorder, and narcolepsy are discussed in detail with their therapeutical implications. This chapter highlights that sleep is necessary for the maintenance of an optimal brain function and is sensitive to both genetic background and environmental enrichment. Even in pathologic conditions, sleep acts as a resilient plastic state that consolidates prior information and prioritizes network activity for efficient brain functioning.

Bridging the gap: TMS-EEG from Lab to Clinic

The combination of transcranial magnetic stimulation (TMS) and electroencephalography (EEG) has reached technological maturity and has been an object of significant scientific interest for over two decades. Ιn parallel, accumulating evidence highlights the potential of TMS-EEG as a useful tool in the field of clinical neurosciences. Nevertheless, its clinical utility has not yet been established, partly because technical and methodological limitations have created a gap between an evolving scientific tool and standard clinical practice. Here we review some of the identified gaps that still prevent TMS-EEG moving from science laboratories to clinical practice. The principal and partly overlapping gaps include: 1) complex and laborious application, 2) difficulty in obtaining high-quality signals, 3) suboptimal accuracy and reliability, and 4) insufficient understanding of the neurobiological substrate of the responses. All these four aspects need to be satisfactorily addressed for the method to become clinically applicable and enter the diagnostic and therapeutic arena. In the current review, we identify steps that might be taken to address these issues and discuss promising recent studies providing tools to aid bridging the gaps.

Alterations in TRN-anterodorsal thalamocortical circuits affect sleep architecture and homeostatic processes in oxidative stress vulnerable Gclm-/- mice

Schizophrenia is associated with alterations of sensory integration, cognitive processing and both sleep architecture and sleep oscillations in mouse models and human subjects, possibly through changes in thalamocortical dynamics. Oxidative stress (OxS) damage, including inflammation and the impairment of fast-spiking gamma-aminobutyric acid neurons have been hypothesized as a potential mechanism responsible for the onset and development of schizophrenia. Yet, the link between OxS and perturbation of thalamocortical dynamics and sleep remains unclear. Here, we sought to investigate the effects of OxS on sleep regulation by characterizing the dynamics of thalamocortical networks across sleep-wake states in a mouse model with a genetic deletion of the modifier subunit of glutamate-cysteine ligase (Gclm knockout, KO) using high-density electrophysiology in freely-moving mice. We found that Gcml KO mice exhibited a fragmented sleep architecture and impaired sleep homeostasis responses as revealed by the increased NREM sleep latencies, decreased slow-wave activities and spindle rate after sleep deprivation. These changes were associated with altered bursting activity and firing dynamics of neurons from the thalamic reticularis nucleus, anterior cingulate and anterodorsal thalamus. Administration of N-acetylcysteine (NAC), a clinically relevant antioxidant, rescued the sleep fragmentation and spindle rate through a renormalization of local neuronal dynamics in Gclm KO mice. Collectively, these findings provide novel evidence for a link between OxS and the deficits of frontal TC network dynamics as a possible mechanism underlying sleep abnormalities and impaired homeostatic responses observed in schizophrenia.

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.

Reconfigurations within resonating communities of brain regions following TMS reveal different scales of processing

An overarching goal of neuroscience research is to understand how heterogeneous neuronal ensembles cohere into networks of coordinated activity to support cognition. To investigate how local activity harmonizes with global signals, we measured electroencephalography (EEG) while single pulses of transcranial magnetic stimulation (TMS) perturbed occipital and parietal cortices. We estimate the rapid network reconfigurations in dynamic network communities within specific frequency bands of the EEG, and characterize two distinct features of network reconfiguration, flexibility and allegiance, among spatially distributed neural sources following TMS. Using distance from the stimulation site to infer local and global effects, we find that alpha activity (8–12 Hz) reflects concurrent local and global effects on network dynamics. Pairwise allegiance of brain regions to communities on average increased near the stimulation site, whereas TMS-induced changes to flexibility were generally invariant to distance and stimulation site. In contrast, communities within the beta (13–20 Hz) band demonstrated a high level of spatial specificity, particularly within a cluster comprising paracentral areas. Together, these results suggest that focal magnetic neurostimulation to distinct cortical sites can help identify both local and global effects on brain network dynamics, and highlight fundamental differences in the manifestation of network reconfigurations within alpha and beta frequency bands.

TMS may be used to probe the causal link between local regional activity and global brain dynamics. Using simultaneous TMS-EEG and dynamic community detection, we introduce what we call “resonating communities” or frequency band-specific clusters in the brain, as a way to index local and global processing. These resonating communities within the alpha and beta bands display both global (or integrating) behavior and local specificity, highlighting fundamental differences in the manifestation of network reconfigurations.

Sleep spindle and slow wave abnormalities in schizophrenia and other psychotic disorders: Recent findings and future directions

Sleep spindles and slow waves are the two main oscillatory activities occurring during NREM sleep. Slow waves are ∼1 Hz, high amplitude, negative-positive deflections that are primarily generated and coordinated within the cortex, whereas sleep spindles are 12-16 Hz, waxing and waning oscillations that are initiated within the thalamus and regulated by thalamo-cortical circuits. In healthy subjects, these oscillations are thought to be responsible for the restorative aspects of sleep and have been increasingly shown to be involved in learning, memory and plasticity. Furthermore, deficits in sleep spindles and, to lesser extent, slow waves have been reported in both chronic schizophrenia (SCZ) and early course psychosis patients. In this article, we will first describe sleep spindle and slow wave characteristics, including their putative functional roles in the healthy brain. We will then review electrophysiological, genetic, and cognitive studies demonstrating spindle and slow wave impairments in SCZ and other psychotic disorders, with particularly emphasis on recent findings in early course patients. Finally, we will discuss how future work, including sleep studies in individuals at clinical high risk for psychosis, may help position spindles and slow waves as candidate biomarkers, as well as novel treatment targets, for SCZ and related psychotic disorders.

The effect of repetitive transcranial magnetic stimulation for insomnia: a systematic review and meta-analysis

BACKGROUND

Repetitive transcranial magnetic stimulation (rTMS) might be a promising technique in treating insomnia. A comprehensive meta-analysis of the available literature is conducted to offer evidence.

OBJECTIVE

To evaluate the efficacy and safety of rTMS for insomnia, either as monotherapy or as a complementary strategy.

METHODS

CENTRAL, PubMed, EMBASE, PsycINFO, CINAHL, PEDro, CBM, CNKI, WANFANG, and VIP were searched from earliest record to August 2019. Randomized control trials (RCTs) published in English and Chinese examining effects of rTMS on patients with insomnia were included. Two authors independently completed the article selection, data extraction and rating. Physiotherapy Evidence Database (PEDro) scale was used to assess the methodological quality of the included studies. The RevMan software was used for meta-analysis. The quality of the evidence was assessed by Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach.

RESULTS

A total of 36 trials from 28 eligible studies were included, involving a total of 2357 adult participants (mean age, 48.80 years; 45.33% males). Compared with sham rTMS, rTMS was associated with improved PSQI total score (SMD -2.31, 95% CI -2.95 to -1.66; Z = 7.01, P < 0.00001) and scores of seven subscales. Compared to other treatment, rTMS as an adjunct to other treatment was associated with improved PSQI total score (SMD -1.44, 95% CI -2.00 to -0.88; Z = 5.01, P < 0.00001), and may have effects on scores of seven subscales. Compared with other treatment, rTMS was associated with improved Pittsburgh sleep quality index (PSQI) total score (SMD -0.63, 95% CI -1.22 to -0.04; Z = 2.08, P = 0.04), and may have a better score in sleep latency, sleep disturbance and hypnotic using of seven subscales. In the three pair of comparisons, the results for polysomnography (PSG) outcomes were varied. In general, rTMS may improve sleep quality through increasing slow wave and rapid eye movement (REM) sleep. The rTMS group was more prone to headache than the sham or blank control group (RR 1.71, 95% CI 1.03 to 2.85; Z = 2.07, P = 0.04). No severe adverse events were reported. Reporting biases and low and very low grade of some evidences should be considered when interpreting the results of this meta-analysis.

CONCLUSIONS

Our findings indicate that rTMS may be a safe and effective option for insomnia. Further international, multicenter, high-quality RCTs with more objective, quality of life related and follow-up assessments are needed.

Divergent neuronal activity patterns in the avian hippocampus and nidopallium

Sleep-related brain activity occurring during non-rapid eye-movement (NREM) sleep is proposed to play a role in processing information acquired during wakefulness. During mammalian NREM sleep, the transfer of information from the hippocampus to the neocortex is thought to be mediated by neocortical slow-waves and their interaction with thalamocortical spindles and hippocampal sharp-wave ripples (SWRs). In birds, brain regions composed of pallial neurons homologous to neocortical (pallial) neurons also generate slow-waves during NREM sleep, but little is known about sleep-related activity in the hippocampus and its possible relationship to activity in other pallial regions. We recorded local field potentials (LFP) and analogue multiunit activity (AMUA) using a 64-channel silicon multi-electrode probe simultaneously inserted into the hippocampus and medial part of the nidopallium (i.e., caudal medial nidopallium; NCM) or separately into the caudolateral nidopallium (NCL) of adult female zebra finches (Taeniopygia guttata) anesthetized with isoflurane, an anesthetic known to induce NREM sleep-like slow-waves. We show that slow-waves in NCM and NCL propagate as waves of neuronal activity. In contrast, the hippocampus does not show slow-waves, nor sharp-wave ripples, but instead displays localized gamma activity. In conclusion, neuronal activity in the avian hippocampus differs from that described in mammals during NREM sleep, suggesting that hippocampal memories are processed differently during sleep in birds and mammals.

Brain Stimulation for Improving Sleep and Memory

Given the critical role of sleep, particularly sleep slow oscillations, sleep spindles, and hippocampal sharp wave ripples, in memory consolidation, sleep enhancement represents a key opportunity to improve cognitive performance. Techniques such as transcranial electrical and magnetic stimulation and acoustic stimulation can enhance slow oscillations and sleep spindles and potentially improve memory. Targeted memory reactivation in sleep may enhance or stabilize memory consolidation. Each technique has technical considerations that may limit its broader clinical application. Therefore, neurostimulation to enhance sleep quality, in particular sleep slow oscillations, has the potential for improving sleep-related memory consolidation in healthy and clinical populations.

Self-health monitoring and wearable neurotechnologies

Brain-computer interfaces and wearable neurotechnologies are now used to measure real-time neural and physiologic signals from the human body and hold immense potential for advancements in medical diagnostics, prevention, and intervention. Given the future role that wearable neurotechnologies will likely serve in the health sector, a critical state-of-the-art assessment is necessary to gain a better understanding of their current strengths and limitations. In this chapter we present wearable electroencephalography systems that reflect groundbreaking innovations and improvements in real-time data collection and health monitoring. We focus on specifications reflecting technical advantages and disadvantages, discuss their use in fundamental and clinical research, their current applications, limitations, and future directions. While many methodological and ethical challenges remain, these systems host the potential to facilitate large-scale data collection far beyond the reach of traditional research laboratory settings.

Connectivity differences between consciousness and unconsciousness in non-rapid eye movement sleep: a TMS-EEG study

The neuronal connectivity patterns that differentiate consciousness from unconsciousness remain unclear. Previous studies have demonstrated that effective connectivity, as assessed by transcranial magnetic stimulation combined with electroencephalography (TMS-EEG), breaks down during the loss of consciousness. This study investigated changes in EEG connectivity associated with consciousness during non-rapid eye movement (NREM) sleep following parietal TMS. Compared with unconsciousness, conscious experiences during NREM sleep were associated with reduced phase-locking at low frequencies (<4 Hz). Transitivity and clustering coefficient in the delta and theta bands were also significantly lower during consciousness compared to unconsciousness, with differences in the clustering coefficient observed in scalp electrodes over parietal-occipital regions. There were no significant differences in Granger-causality patterns in frontal-to-parietal or parietal-to-frontal connectivity between reported unconsciousness and reported consciousness. Together these results suggest that alterations in spectral and spatial characteristics of network properties in posterior brain areas, in particular decreased local (segregated) connectivity at low frequencies, is a potential indicator of consciousness during sleep.

Visual and automatic classification of the cyclic alternating pattern in electroencephalography during sleep

Cyclic alternating pattern (CAP) is a neurophysiological pattern that can be visually scored by international criteria. The aim of this study was to verify the feasibility of visual CAP scoring using only one channel of sleep electroencephalogram (EEG) to evaluate the inter-scorer agreement in a variety of recordings, and to compare agreement between visual scoring and automatic scoring systems. Sixteen hours of single-channel European data format recordings from four different sleep laboratories with either C4-A1 or C3-A2 channels and with different sampling frequencies were used in this study. Seven independent scorers applied visual scoring according to international criteria. Two automatic blind scorings were also evaluated. Event-based inter-scorer agreement analysis was performed. The pairwise inter-scorer agreement (PWISA) was between 55.5 and 84.3%. The average PWISA was above 60% for all scorers and the global average was 69.9%. Automatic scoring systems showed similar results to those of visual scoring. The study showed that CAP could be scored using only one EEG channel. Therefore, CAP scoring might also be integrated in sleep scoring features and automatic scoring systems having similar performances to visual sleep scoring systems.

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.

Network Properties in Transitions of Consciousness during Propofol-induced Sedation

Reliable electroencephalography (EEG) signatures of transitions between consciousness and unconsciousness under anaesthesia have not yet been identified. Herein we examined network changes using graph theoretical analysis of high-density EEG during patient-titrated propofol-induced sedation. Responsiveness was used as a surrogate for consciousness. We divided the data into five states: baseline, transition into unresponsiveness, unresponsiveness, transition into responsiveness, and recovery. Power spectral analysis showed that delta power increased from responsiveness to unresponsiveness. In unresponsiveness, delta waves propagated from frontal to parietal regions as a traveling wave. Local increases in delta connectivity were evident in parietal but not frontal regions. Graph theory analysis showed that increased local efficiency could differentiate the levels of responsiveness. Interestingly, during transitions of responsive states, increased beta connectivity was noted relative to consciousness and unconsciousness, again with increased local efficiency. Abrupt network changes are evident in the transitions in responsiveness, with increased beta band power/connectivity marking transitions between responsive states, while the delta power/connectivity changes were consistent with the fading of consciousness using its surrogate responsiveness. These results provide novel insights into the neural correlates of these behavioural transitions and EEG signatures for monitoring the levels of consciousness under sedation.

The effect of dim light at night on cerebral hemodynamic oscillations during sleep: A near-infrared spectroscopy study

Recent studies have reported that dim light at night (dLAN) is associated with risks of cardiovascular complications, such as hypertension and carotid atherosclerosis; however, little is known about the underlying mechanism. Here, we evaluated the effect of dLAN on the cerebrovascular system by analyzing cerebral hemodynamic oscillations using near-infrared spectroscopy (NIRS). Fourteen healthy male subjects underwent polysomnography coupled with cerebral NIRS. The data collected during sleep with dim light (10 lux) were compared with those collected during sleep under the control dark conditions for the sleep structure, cerebral hemodynamic oscillations, heart rate variability (HRV), and their electroencephalographic (EEG) power spectrum. Power spectral analysis was applied to oxy-hemoglobin concentrations calculated from the NIRS signal. Spectral densities over endothelial very-low-frequency oscillations (VLFOs) (0.003-0.02 Hz), neurogenic VLFOs (0.02-0.04 Hz), myogenic low-frequency oscillations (LFOs) (0.04-0.15 Hz), and total LFOs (0.003-0.15 Hz) were obtained for each sleep stage. The polysomnographic data revealed an increase in the N2 stage under the dLAN conditions. The spectral analysis of cerebral hemodynamics showed that the total LFOs increased significantly during slow-wave sleep (SWS) and decreased during rapid eye movement (REM) sleep. Specifically, endothelial (median of normalized value, 0.46 vs. 0.72, p = 0.019) and neurogenic (median, 0.58 vs. 0.84, p = 0.019) VLFOs were enhanced during SWS, whereas endothelial VLFOs (median, 1.93 vs. 1.47, p = 0.030) were attenuated during REM sleep. HRV analysis exhibited altered spectral densities during SWS induced by dLAN, including an increase in very-low-frequency and decreases in low-frequency and high-frequency ranges. In the EEG power spectral analysis, no significant difference was detected between the control and dLAN conditions. In conclusion, dLAN can disturb cerebral hemodynamics via the endothelial and autonomic systems without cortical involvement, predominantly during SWS, which might represent an underlying mechanism of the increased cerebrovascular risk associated with light exposure during sleep.

Schizophrenia and sleep disorders: links, risks, and management challenges

Schizophrenia is a major psychiatric disorder that has a massive, long-lasting negative impact on the patients as well as society. While positive symptoms (i.e., delusions and hallucinations), negative symptoms (i.e., anhedonia, social withdrawal), and cognitive impairments are traditionally considered the most prominent features of this disorder, the role of sleep and sleep disturbances has gained increasing prominence in clinical practice. Indeed, the vast majority of patients with schizophrenia report sleep abnormalities, which tend to precede illness onset and can predict an acute exacerbation of psychotic symptoms. Furthermore, schizophrenia patients often have a comorbid sleep disorder, including insomnia, obstructive sleep apnea, restless leg syndrome, or periodic limb movement disorder. Despite accumulating data, the links between sleep disorders and schizophrenia have not been thoroughly examined, in part because they are difficult to disentangle, as numerous factors contribute to their comorbidity, including medication status. Additionally, sleep disorders are often not the primary focus of clinicians treating this population, despite studies suggesting that comorbid sleep disorders carry their own unique risks, including worsening of psychotic symptoms and poorer quality of life. There is also limited information about effective management strategies for schizophrenia patients affected by significant sleep disturbances and/or sleep disorders. To begin addressing these issues, the present review will systematically examine the literature on sleep disorders and schizophrenia, focusing on studies related to 1) links between distinct sleep disorders and schizophrenia; 2) risks unique to patients with a comorbid sleep disorder; and 3) and management challenges and strategies.

Fast fMRI can detect oscillatory neural activity in humans

Oscillatory neural dynamics play an important role in the coordination of large-scale brain networks. High-level cognitive processes depend on dynamics evolving over hundreds of milliseconds, so measuring neural activity in this frequency range is important for cognitive neuroscience. However, current noninvasive neuroimaging methods are not able to precisely localize oscillatory neural activity above 0.2 Hz. Electroencephalography and magnetoencephalography have limited spatial resolution, whereas fMRI has limited temporal resolution because it measures vascular responses rather than directly recording neural activity. We hypothesized that the recent development of fast fMRI techniques, combined with the extra sensitivity afforded by ultra-high-field systems, could enable precise localization of neural oscillations. We tested whether fMRI can detect neural oscillations using human visual cortex as a model system. We detected small oscillatory fMRI signals in response to stimuli oscillating at up to 0.75 Hz within single scan sessions, and these responses were an order of magnitude larger than predicted by canonical linear models. Simultaneous EEG-fMRI and simulations based on a biophysical model of the hemodynamic response to neuronal activity suggested that the blood oxygen level-dependent response becomes faster for rapidly varying stimuli, enabling the detection of higher frequencies than expected. Accounting for phase delays across voxels further improved detection, demonstrating that identifying vascular delays will be of increasing importance with higher-frequency activity. These results challenge the assumption that the hemodynamic response is slow, and demonstrate that fMRI has the potential to map neural oscillations directly throughout the brain.

The Slow Oscillation in Cortical and Thalamic Networks: Mechanisms and Functions

During even the most quiescent behavioral periods, the cortex and thalamus express rich spontaneous activity in the form of slow (<1 Hz), synchronous network state transitions. Throughout this so-called slow oscillation, cortical and thalamic neurons fluctuate between periods of intense synaptic activity (Up states) and almost complete silence (Down states). The two decades since the original characterization of the slow oscillation in the cortex and thalamus have seen considerable advances in deciphering the cellular and network mechanisms associated with this pervasive phenomenon. There are, nevertheless, many questions regarding the slow oscillation that await more thorough illumination, particularly the mechanisms by which Up states initiate and terminate, the functional role of the rhythmic activity cycles in unconscious or minimally conscious states, and the precise relation between Up states and the activated states associated with waking behavior. Given the substantial advances in multineuronal recording and imaging methods in both in vivo and in vitro preparations, the time is ripe to take stock of our current understanding of the slow oscillation and pave the way for future investigations of its mechanisms and functions. My aim in this Review is to provide a comprehensive account of the mechanisms and functions of the slow oscillation, and to suggest avenues for further exploration.

Real-time automated EEG tracking of brain states using neural field theory

A real-time fitting system is developed and used to fit the predictions of an established physiologically-based neural field model to electroencephalographic spectra, yielding a trajectory in a physiological parameter space that parametrizes intracortical, intrathalamic, and corticothalamic feedbacks as the arousal state evolves continuously over time. This avoids traditional sleep/wake staging (e.g., using Rechtschaffen-Kales stages), which is fundamentally limited because it forces classification of continuous dynamics into a few discrete categories that are neither physiologically informative nor individualized. The classification is also subject to substantial interobserver disagreement because traditional staging relies in part on subjective evaluations. The fitting routine objectively and robustly tracks arousal parameters over the course of a full night of sleep, and runs in real-time on a desktop computer. The system developed here supersedes discrete staging systems by representing arousal states in terms of physiology, and provides an objective measure of arousal state which solves the problem of interobserver disagreement. Discrete stages from traditional schemes can be expressed in terms of model parameters for backward compatibility with prior studies.

Repetitive transcranial magnetic stimulation induced slow wave activity modification: A possible role in disorder of consciousness differential diagnosis?

Slow wave activity (SWA) generation depends on cortico-thalamo-cortical loops that are disrupted in patients with chronic Disorders of Consciousness (DOC), including the Unresponsive Wakefulness Syndrome (UWS) and the Minimally Conscious State (MCS). We hypothesized that the modulation of SWA by means of a repetitive transcranial magnetic stimulation (rTMS) could reveal residual patterns of connectivity, thus supporting the DOC clinical differential diagnosis. We enrolled 10 DOC individuals who underwent a 24hh polysomnography followed by a real or sham 5Hz-rTMS over left primary motor area, and a second polysomnographic recording. A preserved sleep-wake cycle, a standard temporal progression of sleep stages, and a SWA perturbation were found in all of the MCS patients and in none of the UWS individuals, only following the real-rTMS. In conclusion, our combined approach may improve the differential diagnosis between MCS patients, who show a partial preservation of cortical plasticity, and UWS individuals, who lack such properties.

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.

Thalamic reticular nucleus induces fast and local modulation of arousal state

During low arousal states such as drowsiness and sleep, cortical neurons exhibit rhythmic slow wave activity associated with periods of neuronal silence. Slow waves are locally regulated, and local slow wave dynamics are important for memory, cognition, and behaviour. While several brainstem structures for controlling global sleep states have now been well characterized, a mechanism underlying fast and local modulation of cortical slow waves has not been identified. Here, using optogenetics and whole cortex electrophysiology, we show that local tonic activation of thalamic reticular nucleus (TRN) rapidly induces slow wave activity in a spatially restricted region of cortex. These slow waves resemble those seen in sleep, as cortical units undergo periods of silence phase-locked to the slow wave. Furthermore, animals exhibit behavioural changes consistent with a decrease in arousal state during TRN stimulation. We conclude that TRN can induce rapid modulation of local cortical state.

DOI:http://dx.doi.org/10.7554/eLife.08760.001

We usually think of sleep as a global state: that the entire brain is either asleep or awake. However, recent evidence has suggested that smaller regions of the brain can show sleep-like activity while the rest of the brain remains awake. It is not clear why or how these sleep-like patterns of brain activity appear, and whether they are related to the drowsy behaviour that occurs when one is about to fall asleep.

Lewis, Voigts et al. investigated how this process works in mice using a technique called optogenetics. This technique makes it possible to genetically engineer mice so that the activity of particular areas of the brain can be switched on or off by light. Lewis, Voigts et al. used light to stimulate different regions of the brain and tracked the resulting brain activity using tiny electrodes that are capable of detecting the activity of individual neurons.

The experiments show that stimulating one part of a deep brain structure called the thalamic reticular nucleus causes just one small part of the brain to switch from being awake to producing sleep-like brain wave patterns. When a larger area is stimulated, the whole brain switches into this sleep-like pattern. Stimulation of the thalamic reticular nucleus also caused the animals to become drowsy and they were more likely to fall asleep, which suggests that sleep-like activity in small parts of the brain may contribute to drowsiness.

Lewis, Voigts et al.’s findings identify a brain switch that can influence whether an animal is awake or asleep. Importantly, they show that sleep can be independently controlled in small brain regions, and that the thalamic reticular nucleus contains a ‘map’ that allows it to induce sleep in just one region, or across the whole brain. Memories are strengthened during sleep, so the next challenge is to study whether the thalamic reticular nucleus influences memory formation. The findings also suggest that further study of this brain region may be useful for understanding how the sleep and awake states are controlled by particular neurons.

DOI:http://dx.doi.org/10.7554/eLife.08760.002

Formation and Dynamics of Waves in a Cortical Model of Cholinergic Modulation

Acetylcholine (ACh) is a regulator of neural excitability and one of the neurochemical substrates of sleep. Amongst the cellular effects induced by cholinergic modulation are a reduction in spike-frequency adaptation (SFA) and a shift in the phase response curve (PRC). We demonstrate in a biophysical model how changes in neural excitability and network structure interact to create three distinct functional regimes: localized asynchronous, traveling asynchronous, and traveling synchronous. Our results qualitatively match those observed experimentally. Cortical activity during slow wave sleep (SWS) differs from that during REM sleep or waking states. During SWS there are traveling patterns of activity in the cortex; in other states stationary patterns occur. Our model is a network composed of Hodgkin-Huxley type neurons with a M-current regulated by ACh. Regulation of ACh level can account for dynamical changes between functional regimes. Reduction of the magnitude of this current recreates the reduction in SFA the shift from a type 2 to a type 1 PRC observed in the presence of ACh. When SFA is minimal (in waking or REM sleep state, high ACh) patterns of activity are localized and easily pinned by network inhomogeneities. When SFA is present (decreasing ACh), traveling waves of activity naturally arise. A further decrease in ACh leads to a high degree of synchrony within traveling waves. We also show that the level of ACh determines how sensitive network activity is to synaptic heterogeneity. These regimes may have a profound functional significance as stationary patterns may play a role in the proper encoding of external input as memory and traveling waves could lead to synaptic regularization, giving unique insights into the role and significance of ACh in determining patterns of cortical activity and functional differences arising from the patterns.

Physiologically based arousal state estimation and dynamics

A neural field model of the brain is used to represent brain states using physiologically based parameters rather than arbitrary, discrete sleep stages. Each brain state is represented as a point in a physiologically parametrized space. Over time, changes in brain state cause these points to trace continuous trajectories, unlike the artificial discrete jumps in sleep stage that occur with traditional sleep staging. The discrete Rechtschaffen and Kales sleep stages are associated with regions in the physiological parameter space based on their electroencephalographic features, which enables interpretation of traditional sleep stages in terms of physiological trajectories. Wake states are found to be associated with strong positive corticothalamic feedback compared to sleep. The existence of physiologically valid trajectories between brain states in the model is demonstrated. Actual trajectories for an individual can be determined by fitting the model using EEG alone, and enable analysis of the physiological differences between subjects.

Sleep smart-optimizing sleep for declarative learning and memory

The last decade has witnessed a spurt of new publications documenting sleep's essential contribution to the brains ability to form lasting memories. For the declarative memory domain, slow wave sleep (the deepest sleep stage) has the greatest beneficial effect on the consolidation of memories acquired during preceding wakefulness. The finding that newly encoded memories become reactivated during subsequent sleep fostered the idea that reactivation leads to the strengthening and transformation of the memory trace. According to the active system consolidation account, trace reactivation leads to the redistribution of the transient memory representations from the hippocampus to the long-lasting knowledge networks of the cortex. Apart from consolidating previously learned information, sleep also facilitates the encoding of new memories after sleep, which probably relies on the renormalization of synaptic weights during sleep as suggested by the synaptic homeostasis theory. During wakefulness overshooting potentiation causes an imbalance in synaptic weights that is countered by synaptic downscaling during subsequent sleep. This review briefly introduces the basic concepts and central findings of the research on sleep and memory, and discusses implications of this lab-based work for everyday applications to make the best possible use of sleep's beneficial effect on learning and memory.

Opportunities for concurrent transcranial magnetic stimulation and electroencephalography to characterize cortical activity in stroke

Stroke is the leading cause of disability in the United States. Despite the high incidence and mortality of stroke, sensitive and specific brain-based biomarkers predicting persisting disabilities are lacking. Both neuroimaging techniques like electroencephalography (EEG) and non-invasive brain stimulation (NIBS) techniques such as transcranial magnetic stimulation (TMS) have proven useful in predicting prognosis, recovery trajectories and response to rehabilitation in individuals with stroke. We propose, however, that additional synergetic effects can be achieved by simultaneously combining both approaches. Combined TMS-EEG is able to activate discrete cortical regions and directly assess local cortical reactivity and effective connectivity within the network independent of the integrity of descending fiber pathways and also outside the motor system. Studying cortical reactivity and connectivity in patients with stroke TMS-EEG may identify salient neural mechanisms underlying motor disabilities and lead to novel biomarkers of stroke pathophysiology which can then be used to assess, monitor, and refine rehabilitation approaches for individuals with significant disability to improve outcomes and quality of life after stroke.

Sleep in patients with schizophrenia

Numerous electrophysiological and neuroimaging studies have reported neurophysiological and cognitive deficits in schizophrenia patients during wakefulness. However, these findings have been inconsistently replicated across different groups of patients, thus complicating the identification of underlying neuronal defects. Sleep minimizes possible waking-related confounds, including decreased motivation and presence of active symptoms. Additionally, the two main sleep rhythms, slow waves and spindles, reflect the intrinsic activity of corticothalamic circuits and are associated with cognitive activities, including learning and memory, occurring during wakefulness. In this review I will present the most relevant sleep findings in schizophrenia, with particular emphasis on several recent studies that have consistently reported sleep spindle deficits in patients with schizophrenia. I will then elaborate on how these findings may contribute to a better understanding of the neurobiology of schizophrenia as well as to the development of novel pharmacological and non-pharmacological interventions to ameliorate the symptoms and cognitive impairments of schizophrenia patients.

Neocortical inhibitory activities and long-range afferents contribute to the synchronous onset of silent states of the neocortical slow oscillation

During slow-wave sleep, neurons of the thalamocortical network are engaged in a slow oscillation (<1 Hz), which consists of an alternation between the active and the silent states. Several studies have provided insights on the transition from the silent, which are essentially periods of disfacilitation, to the active states. However, the conditions leading to the synchronous onset of the silent state remain elusive. We hypothesized that a synchronous input to local inhibitory neurons could contribute to the transition to the silent state in the cat suprasylvian gyrus during natural sleep and under ketamine-xylazine anesthesia. After partial and complete deafferentation of the cortex, we found that the silent state onset was more variable among remote sites. We found that the transition to the silent state was preceded by a reduction in excitatory postsynaptic potentials and firing probability in cortical neurons. We tested the impact of chloride-mediated inhibition in the silent-state onset. We uncovered a long-duration (100-300 ms) inhibitory barrage occurring about 250 ms before the silent state onset in 3-6% of neurons during anesthesia and in 12-15% of cases during natural sleep. These inhibitory activities caused a decrease in cortical firing that reduced the excitatory drive in the neocortical network. That chain reaction of disfacilitation ends up on the silent state. Electrical stimuli could trigger a network silent state with a maximal efficacy in deep cortical layers. We conclude that long-range afferents to the neocortex and chloride-mediated inhibition play a role in the initiation of the silent state.

Repetitive transcranial magnetic stimulation increases the corticospinal inhibition and the brain-derived neurotrophic factor in chronic myofascial pain syndrome: an explanatory double-blinded, randomized, sham-controlled trial

Chronic myofascial pain syndrome has been related to defective descending inhibitory systems. Twenty-four females aged 19 to 65 years with chronic myofascial pain syndrome were randomized to receive 10 sessions of repetitive transcranial magnetic stimulation (rTMS) (n = 12) at 10 Hz or a sham intervention (n = 12). We tested if pain (quantitative sensory testing), descending inhibitory systems (conditioned pain modulation [quantitative sensory testing + conditioned pain modulation]), cortical excitability (TMS parameters), and the brain-derived neurotrophic factor (BDNF) would be modified. There was a significant interaction (time vs group) regarding the main outcomes of the pain scores as indexed by the visual analog scale on pain (analysis of variance, P < .01). Post hoc analysis showed that compared with placebo-sham, the treatment reduced daily pain scores by -30.21% (95% confidence interval = -39.23 to -21.20) and analgesic use by -44.56 (-57.46 to -31.67). Compared to sham, rTMS enhanced the corticospinal inhibitory system (41.74% reduction in quantitative sensory testing + conditioned pain modulation, P < .05), reduced the intracortical facilitation in 23.94% (P = .03), increased the motor evoked potential in 52.02% (P = .02), and presented 12.38 ng/mL higher serum BDNF (95% confidence interval = 2.32-22.38). No adverse events were observed. rTMS analgesic effects in chronic myofascial pain syndrome were mediated by top-down regulation mechanisms, enhancing the corticospinal inhibitory system possibly via BDNF secretion modulation.

PERSPECTIVE

High-frequency rTMS analgesic effects were mediated by top-down regulation mechanisms enhancing the corticospinal inhibitory, and this effect involved an increase in BDNF secretion.

Plumes of neuronal activity propagate in three dimensions through the nuclear avian brain

BACKGROUND

In mammals, the slow-oscillations of neuronal membrane potentials (reflected in the electroencephalogram as high-amplitude, slow-waves), which occur during non-rapid eye movement sleep and anesthesia, propagate across the neocortex largely as two-dimensional traveling waves. However, it remains unknown if the traveling nature of slow-waves is unique to the laminar cytoarchitecture and associated computational properties of the neocortex.

RESULTS

We demonstrate that local field potential slow-waves and correlated multiunit activity propagate as complex three-dimensional plumes of neuronal activity through the avian brain, owing to its non-laminar, nuclear neuronal cytoarchitecture.

CONCLUSIONS

The traveling nature of slow-waves is not dependent upon the laminar organization of the neocortex, and is unlikely to subserve functions unique to this pattern of neuronal organization. Finally, the three-dimensional geometry of propagating plumes may reflect computational properties not found in mammals that contributed to the evolution of nuclear neuronal organization and complex cognition in birds.

Time-frequency analysis of short-lasting modulation of EEG induced by TMS during wake, sleep deprivation and sleep

The occurrence of dynamic changes in spontaneous electroencephalogram (EEG) rhythms in the awake state or sleep is highly variable. These rhythms can be externally modulated during transcranial magnetic stimulation (TMS) with a perturbation method to trigger oscillatory brain activity. EEG-TMS co-registration was performed during standard wake, during wake after sleep deprivation and in sleep in six healthy subjects. Dynamic changes in the regional neural oscillatory activity of the cortical areas were characterized using time-frequency analysis based on the wavelet method, and the modulation of induced oscillations were related to different vigilance states. A reciprocal synchronizing/desynchronizing effect on slow and fast oscillatory activity was observed in response to focal TMS after sleep deprivation and sleep. We observed a sleep-related slight desynchronization of alpha mainly over the frontal areas, and a widespread increase in theta synchronization. These findings could be interpreted as proof of the interference external brain stimulation can exert on the cortex, and how this could be modulated by the vigilance state. Potential clinical applications may include evaluation of hyperexcitable states such as epilepsy or disturbed states of consciousness such as minimal consciousness.

Numerical modelling of plasticity induced by transcranial magnetic stimulation

We use neural field theory and spike-timing dependent plasticity to make a simple but biophysically reasonable model of long-term plasticity changes in the cortex due to transcranial magnetic stimulation (TMS). We show how common TMS protocols can be captured and studied within existing neural field theory. Specifically, we look at repetitive TMS protocols such as theta burst stimulation and paired-pulse protocols. Continuous repetitive protocols result mostly in depression, but intermittent repetitive protocols in potentiation. A paired pulse protocol results in depression at short ( < ∼ 10 ms) and long ( > ∼ 100 ms) interstimulus intervals, but potentiation for mid-range intervals. The model is sensitive to the choice of neural populations that are driven by the TMS pulses, and to the parameters that describe plasticity, which may aid interpretation of the high variability in existing experimental results. Driving excitatory populations results in greater plasticity changes than driving inhibitory populations. Modelling also shows the merit in optimizing a TMS protocol based on an individual's electroencephalogram. Moreover, the model can be used to make predictions about protocols that may lead to improvements in repetitive TMS outcomes.