Cortical reactivity and effective connectivity during REM sleep in humans

Permutation conditional mutual information to quantify TMS-evoked cortical connectivity in disorders of consciousness

Objective.To improve the understanding and diagnostic accuracy of disorders of consciousness (DOC) by quantifying transcranial magnetic stimulation (TMS) evoked electroencephalography connectivity using permutation conditional mutual information (PCMI).Approach.PCMI can characterize the functional connectivity between different brain regions. This study employed PCMI to analyze TMS-evoked cortical connectivity (TEC) in 154 DOC patients and 16 normal controls, focusing on optimizing parameter selection for PCMI (Data length, Order length, Time delay). We compared short-range and long-range PCMI values across different consciousness states-unresponsive wakefulness syndrome (UWS), minimally conscious state (MCS), and normal (NOR)-and assessed various feature selection and classification techniques to distinguish these states.Main results.(1) PCMI can quantify TEC. We found optimal parameters to be Data length: 500 ms; Order: 3; Time delay: 6 ms. (2) TMS evoked potentials (TEPs) for NOR showed a rich response, while MCS patients showed only a few components, and UWS patients had almost no significant components. The values of PCMI connectivity metrics demonstrated its usefulness for measuring cortical connectivity evoked by TMS. From NOR to MCS to UWS, the number and strength of TEC decreased. Quantitative analysis revealed significant differences in the strength and number of TEC in the entire brain, local regions and inter-regions among different consciousness states. (3) A decision tree with feature selection by mutual information performed the best (balanced accuracy: 87.0% and accuracy: 83.5%). This model could accurately identify NOR (100.0%), but had lower identification accuracy for UWS (86.5%) and MCS (74.1%).Significance.The application of PCMI in measuring TMS-evoked connectivity provides a robust metric that enhances our ability to differentiate between various states of consciousness in DOC patients. This approach not only aids in clinical diagnosis but also contributes to the broader understanding of cortical connectivity and consciousness.

The experimental study of consciousness: Is psychology travelling back to the future?

It was with the promise of rendering an experimental approach to consciousness that psychology started its trajectory as an independent science more than 150 years ago. Here, we will posit that the neurosciences were instrumental in leading psychology to resume the study of consciousness by projecting an empirical agenda for the future. First, we will start by showing how scientists were able to venture into the consciousness of supposedly unconscious patients, opening the door for the identification of important neural correlates of distinct consciousness states. Then, we will describe how different technological advances and elegant experimental paradigms helped in establishing important neuronal correlates of global consciousness (i.e., being conscious at all), perceptual consciousness (i.e., being conscious of something), and self-consciousness (i.e., being conscious of itself). Finally, we will illustrate how the study of complex consciousness experiences may contribute to the clarification of the mechanisms associated with global consciousness, the relationship between perceptual and self-consciousness, and the interface among distinct self-consciousness domains. In closing, we will elaborate on the road ahead of us for re-establishing psychology as a science of consciousness.

Behavioral and cortical arousal from sleep, muscimol-induced coma, and anesthesia by direct optogenetic stimulation of cortical neurons

The cerebral cortex is widely considered part of the neural substrate of consciousness, but direct causal evidence is missing. Here, we tested in mice whether optogenetic activation of cortical neurons in posterior parietal cortex (PtA) or medial prefrontal cortex (mPFC) is sufficient for arousal from three behavioral states characterized by progressively deeper unresponsiveness: sleep, a coma-like state induced by muscimol injection in the midbrain, and deep sevoflurane-dexmedetomidine anesthesia. We find that cortical stimulation always awakens the mice from both NREM sleep and REM sleep, with PtA requiring weaker/shorter light pulses than mPFC. Moreover, in most cases light pulses produce both cortical activation (decrease in low frequencies) and behavioral arousal (recovery of the righting reflex) from brainstem coma, as well as cortical activation from anesthesia. These findings provide evidence that direct activation of cortical neurons is sufficient for behavioral and/or cortical arousal from sleep, brainstem coma, and anesthesia.

Consciousness and sleep

Sleep is a universal, essential biological process. It is also an invaluable window on consciousness. It tells us that consciousness can be lost but also that it can be regained, in all its richness, when we are disconnected from the environment and unable to reflect. By considering the neurophysiological differences between dreaming and dreamless sleep, we can learn about the substrate of consciousness and understand why it vanishes. We also learn that the ongoing state of the substrate of consciousness determines the way each experience feels regardless of how it is triggered-endogenously or exogenously. Dreaming consciousness is also a window on sleep and its functions. Dreams tell us that the sleeping brain is remarkably lively, recombining intrinsic activation patterns from a vast repertoire, freed from the requirements of ongoing behavior and cognitive control.

Sleepiness and the transition from wakefulness to sleep

The transition from wakefulness to sleep is a progressive process that is reflected in the gradual loss of responsiveness, an alteration of cognitive functions, and a drastic shift in brain dynamics. These changes do not occur all at once. The sleep onset period (SOP) refers here to this period of transition between wakefulness and sleep. For example, although transitions of brain activity at sleep onset can occur within seconds in a given brain region, these changes occur at different time points across the brain, resulting in a SOP that can last several minutes. Likewise, the transition to sleep impacts cognitive and behavioral levels in a graded and staged fashion. It is often accompanied and preceded by a sensation of drowsiness and the subjective feeling of a need for sleep, also associated with specific physiological and behavioral signatures. To better characterize fluctuations in vigilance and the SOP, a multidimensional approach is thus warranted. Such a multidimensional approach could mitigate important limitations in the current classification of sleep, leading ultimately to better diagnoses and treatments of individuals with sleep and/or vigilance disorders. These insights could also be translated in real-life settings to either facilitate sleep onset in individuals with sleep difficulties or, on the contrary, prevent or control inappropriate sleep onsets.

Dissociations between spontaneous electroencephalographic features and the perturbational complexity index in the minimally conscious state

The analysis of spontaneous electroencephalogram (EEG) is a cornerstone in the assessment of patients with disorders of consciousness (DoC). Although preserved EEG patterns are highly suggestive of consciousness even in unresponsive patients, moderately or severely abnormal patterns are difficult to interpret. Indeed, growing evidence shows that consciousness can be present despite either large delta or reduced alpha activity in spontaneous EEG. Quantifying the complexity of EEG responses to direct cortical perturbations (perturbational complexity index [PCI]) may complement the observational approach and provide a reliable assessment of consciousness even when spontaneous EEG features are inconclusive. To seek empirical evidence of this hypothesis, we compared PCI with EEG spectral measures in the same population of minimally conscious state (MCS) patients (n = 40) hospitalized in rehabilitation facilities. We found a remarkable variability in spontaneous EEG features across MCS patients as compared with healthy controls: in particular, a pattern of predominant delta and highly reduced alpha power-more often observed in vegetative state/unresponsive wakefulness syndrome (VS/UWS) patients-was found in a non-negligible number of MCS patients. Conversely, PCI values invariably fell above an externally validated empirical cutoff for consciousness in all MCS patients, consistent with the presence of clearly discernible, albeit fleeting, behavioural signs of awareness. These results confirm that, in some MCS patients, spontaneous EEG rhythms may be inconclusive about the actual capacity for consciousness and suggest that a perturbational approach can effectively compensate for this pitfall with practical implications for the individual patient's stratification and tailored rehabilitation.

Multimodal approaches supporting the diagnosis, prognosis and investigation of neural correlates of disorders of consciousness: A systematic review

The limits of the standard, behaviour-based clinical assessment of patients with disorders of consciousness (DoC) prompted the employment of functional neuroimaging, neurometabolic, neurophysiological and neurostimulation techniques, to detect brain-based covert markers of awareness. However, uni-modal approaches, consisting in employing just one of those techniques, are usually not sufficient to provide an exhaustive exploration of the neural underpinnings of residual awareness. This systematic review aimed at collecting the evidence from studies employing a multimodal approach, that is, combining more instruments to complement DoC diagnosis, prognosis and better investigating their neural correlates. Following the PRISMA guidelines, records from PubMed, EMBASE and Scopus were screened to select peer-review original articles in which a multi-modal approach was used for the assessment of adult patients with a diagnosis of DoC. Ninety-two observational studies and 32 case reports or case series met the inclusion criteria. Results highlighted a diagnostic and prognostic advantage of multi-modal approaches that involve electroencephalography-based (EEG-based) measurements together with neuroimaging or neurometabolic data or with neurostimulation. Multimodal assessment deepened the knowledge on the neural networks underlying consciousness, by showing correlations between the integrity of the default mode network and the different clinical diagnosis of DoC. However, except for studies using transcranial magnetic stimulation combined with electroencephalography, the integration of more than one technique in most of the cases occurs without an a priori-designed multi-modal diagnostic approach. Our review supports the feasibility and underlines the advantages of a multimodal approach for the diagnosis, prognosis and for the investigation of neural correlates of DoCs.

Frequency-dependent connectivity in large-scale resting-state brain networks during sleep

Functional connectivity (FC) during sleep has been shown to break down as non-rapid eye movement (NREM) sleep deepens before returning to a state closer to wakefulness during rapid eye movement (REM) sleep. However, the specific spatial and temporal signatures of these fluctuations in connectivity patterns remain poorly understood. This study aimed to investigate how frequency-dependent network-level FC fluctuates during nocturnal sleep in healthy young adults using high-density electroencephalography (hdEEG). Specifically, we examined source-localized FC in resting-state networks during NREM2, NREM3 and REM sleep (sleep stages scored using a semi-automatic procedure) in the first three sleep cycles of 29 participants. Our results showed that FC within and between all resting-state networks decreased from NREM2 to NREM3 sleep in multiple frequency bands and all sleep cycles. The data also highlighted a complex modulation of connectivity patterns during the transition to REM sleep whereby delta and sigma bands hosted a persistence of the connectivity breakdown in all networks. In contrast, a reconnection occurred in the default mode and the attentional networks in frequency bands characterizing their organization during wake (i.e., alpha and beta bands, respectively). Finally, all network pairs (except the visual network) showed higher gamma-band FC during REM sleep in cycle three compared to earlier sleep cycles. Altogether, our results unravel the spatial and temporal characteristics of the well-known breakdown in connectivity observed as NREM sleep deepens. They also illustrate a complex pattern of connectivity during REM sleep that is consistent with network- and frequency-specific breakdown and reconnection processes.

Accelerated transcranial magnetic stimulation for major depressive disorder: A quick path to relief?

Transcranial magnetic stimulation (TMS) is a safe, tolerable, and evidence-based intervention for major depressive disorder (MDD). However, even after decades of research, nearly half of the patients with MDD fail to respond to conventional TMS, with responding slowly and requiring daily attendance at the treatment site for 4-6 weeks. To intensify antidepressant efficacy and shorten treatment duration, accelerated TMS protocols, which involve multiple sessions per day over a few days, have been proposed and evaluated for safety and viability. We reviewed and summarized the current knowledge in accelerated TMS, including stimulation parameters, antidepressant efficacy, anti-suicidal efficacy, safety, and adverse effects. Limitations and suggestions for future directions are also addressed, along with a brief discussion on the application of accelerated TMS during the COVID-19 pandemic. This article is categorized under: Neuroscience > Clinical Neuroscience.

Depth of sedation with dexmedetomidine increases transcranial magnetic stimulation-evoked potential amplitude non-linearly

BACKGROUND

Cortical excitability is higher in unconsciousness than in wakefulness, but it is unclear how this relates to anaesthesia. We investigated cortical excitability in response to dexmedetomidine, the effects of which are not fully known.

METHODS

We recorded transcranial magnetic stimulation (TMS) and EEG in frontal and parietal cortex of 20 healthy subjects undergoing dexmedetomidine sedation in four conditions (baseline, light sedation, deep sedation, recovery). We used the first component (0-30 ms) of the TMS-evoked potential (TEP) to measure cortical excitability (amplitude), slope, and positive and negative peak latencies (collectively, TEP indices). We used generalised linear mixed models to test the effect of condition, brain region, and responsiveness on TEP indices.

RESULTS

Compared with baseline, amplitude in the frontal cortex increased by 6.52 μV (P<0.001) in light sedation, 4.55 μV (P=0.003) in deep sedation, and 5.03 μV (P<0.001) in recovery. Amplitude did not change in the parietal cortex. Compared with baseline, slope increased in all conditions (P<0.02) in the frontal but not parietal cortex. The frontal cortex showed 5.73 μV higher amplitude (P<0.001), 0.63 μV ms-1 higher slope (P<0.001), and 2.2 ms shorter negative peak latency (P=0.001) than parietal areas. Interactions between dexmedetomidine and region had effects over amplitude (P=0.004) and slope (P=0.009), with both being higher in light sedation, deep sedation, and recovery compared with baseline.

CONCLUSIONS

Transcranial magnetic stimulation-evoked potential amplitude changes non-linearly as a function of depth of sedation by dexmedetomidine, with a region-specific paradoxical increase. Future research should investigate other anaesthetics to elucidate the link between cortical excitability and depth of sedation.

Reliability and Validity of Transcranial Magnetic Stimulation-Electroencephalography Biomarkers

Noninvasive brain stimulation and neuroimaging have revolutionized human neuroscience with a multitude of applications, including diagnostic subtyping, treatment optimization, and relapse prediction. It is therefore particularly relevant to identify robust and clinically valuable brain biomarkers linking symptoms to their underlying neural mechanisms. Brain biomarkers must be reproducible (i.e., have internal reliability) across similar experiments within a laboratory and be generalizable (i.e., have external reliability) across experimental setups, laboratories, brain regions, and disease states. However, reliability (internal and external) is not alone sufficient; biomarkers also must have validity. Validity describes closeness to a true measure of the underlying neural signal or disease state. We propose that these metrics, reliability and validity, should be evaluated and optimized before any biomarker is used to inform treatment decisions. Here, we discuss these metrics with respect to causal brain connectivity biomarkers from coupling transcranial magnetic stimulation (TMS) with electroencephalography (EEG). We discuss controversies around TMS-EEG stemming from the multiple large off-target components (noise) and relatively weak genuine brain responses (signal), as is unfortunately often the case in noninvasive human neuroscience. We review the current state of TMS-EEG recordings, which consist of a mix of reliable noise and unreliable signal. We describe methods for evaluating TMS-EEG biomarkers, including how to assess internal and external reliability across facilities, cognitive states, brain networks, and disorders and how to validate these biomarkers using invasive neural recordings or treatment response. We provide recommendations to increase reliability and validity, discuss lessons learned, and suggest future directions for the field.

About the compatibility between the perturbational complexity index and the global neuronal workspace theory of consciousness

This paper investigates the compatibility between the theoretical framework of the global neuronal workspace theory (GNWT) of conscious processing and the perturbational complexity index (PCI). Even if it has been introduced within the framework of a concurrent theory (i.e. Integrated Information Theory), PCI appears, in principle, compatible with the main tenet of GNWT, which is a conscious process that depends on a long-range connection between different cortical regions, more specifically on the amplification, global propagation, and integration of brain signals. Notwithstanding this basic compatibility, a number of limited compatibilities and apparent differences emerge. This paper starts from the description of brain complexity, a notion that is crucial for PCI, to then summary of the main features of PCI and the main tenets of GNWT. Against this background, the text explores the compatibility between PCI and GNWT. It concludes that GNWT and PCI are fundamentally compatible, even though there are some partial disagreements and some points to further examine.

Neuroprotection of Low-Frequency Repetitive Transcranial Magnetic Stimulation after Ischemic Stroke in Rats

OBJECTIVE

Stroke is a leading cause of human death and disability. Effective early treatments with reasonable therapeutic windows remain critically important to improve the outcomes of stroke. Transcranial magnetic stimulation (TMS) is an established noninvasive technique that has been applied clinically and in animal research for multiple brain disorders, but few studies have examined acute neuroprotection against ischemic stroke. The present investigation tested the novel approach of low-frequency repetitive TMS (rTMS) as an acute treatment after ischemic stroke.

METHODS

Adult male rats received focal ischemic surgery through occlusion of the right middle cerebral artery for 60 minutes. The rats received either rTMS or sham treatment with 1.5-, 3-, 4-, or 7-hour delay after the onset of stroke. Low-frequency and low-intensity rTMS was applied to the rat brain for two 30-minute episodes separated by a 1-hour interval.

RESULTS

Three days after stroke, compared to stroke controls, rats receiving rTMS treatment with a 1.5-hour delay showed a 35% reduction of infarct volume. Protective effects were also seen with 3- or 4-hour-delayed treatments by rTMS, shown as reduced infarct volume and cell death. rTMS treatment upregulated the antiapoptotic factor Bcl-2 and downregulated the proapoptotic caspase-3 cleavage, expressions of Bax and matrix metallopeptidase-9. In sensorimotor functional assessments 3 to 21 days after stroke, rats receiving rTMS treatment with a 1.5- or 3-hour delay showed significantly better performance compared to stroke controls.

INTERPRETATION

These results support the inference that low-frequency rTMS may be feasible as a neuroprotective acute treatment after ischemic stroke. ANN NEUROL 2023;93:336-347.

Unconscious integration: Current evidence for integrative processing under subliminal conditions

Integrative processing is traditionally believed to be dependent on consciousness. While earlier studies within the last decade reported many types of integration under subliminal conditions (i.e. without perceptual awareness), these findings are widely challenged recently. This review evaluates the current evidence for 10 types of subliminal integration that are widely studied: arithmetic processing, object-context integration, multi-word processing, same-different processing, multisensory integration and 5 different types of associative learning. Potential methodological issues concerning awareness measures are also taken into account. It is concluded that while there is currently no reliable evidence for subliminal integration, this does not necessarily refute 'unconscious' integration defined through non-subliminal (e.g. implicit) approaches.

Pedunculopontine-induced cortical decoupling as the neurophysiological locus of dissociation

Mounting evidence suggests an association between aberrant sleep phenomena and dissociative experiences. However, no wake-sleep boundary theory provides a compelling explanation of dissociation or specifies its physiological substrates. We present a theoretical account of dissociation that integrates theories and empirical results from multiple lines of research concerning the domain of dissociation and the regulation of rapid eye movement (REM) sleep. This theory posits that individual differences in the circuitry governing the REM sleep promoting Pedunculopontine Nucleus and Laterodorsal Tegmental Nucleus determine the degree of similarity in the cortical connectivity profiles of wakefulness and REM sleep. We propose that a latent trait characterized by elevated dissociative experiences emerges from the decoupling of frontal executive regions due to a REM sleep-like aminergic/cholinergic balance. The Pedunculopontine-Induced Cortical Decoupling Account of Dissociation (PICDAD) suggests multiple fruitful lines of inquiry and provides novel insights. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

In vivo low-intensity magnetic pulses durably alter neocortical neuron excitability and spontaneous activity

KEY POINTS

Repetitive transcranial magnetic stimulation (rTMS) is a promising technique to alleviate neurological and psychiatric disorders caused by alterations in cortical activity. Our knowledge of the cellular mechanisms underlying rTMS-based therapies remains limited. We combined in vivo focal application of low-intensity rTMS (LI-rTMS) to the rat somatosensory cortex with intracellular recordings of subjacent pyramidal neurons to characterize the effects of weak magnetic fields at single cell level. Ten minutes of LI-rTMS delivered at 10 Hz reliably evoked action potentials in cortical neurons during the stimulation period, and induced durable attenuation of their intrinsic excitability, synaptic activity, and spontaneous firing. These results help us better understand the mechanisms of weak magnetic stimulation and should allow optimizing the effectiveness of stimulation protocols for clinical use.

ABSTRACT

Magnetic brain stimulation is a promising treatment for neurological and psychiatric disorders. However, a better understanding of its effects at the individual neuron level is essential to improve its clinical application. We combined focal low-intensity repetitive transcranial magnetic stimulation (LI-rTMS) to the rat somatosensory cortex with intracellular recordings of subjacent pyramidal neurons in vivo. Continuous 10 Hz LI-rTMS reliably evoked firing at ∼4-5 Hz during the stimulation period and induced durable attenuation of synaptic activity and spontaneous firing in cortical neurons, through membrane hyperpolarization and a reduced intrinsic excitability. However, inducing firing in individual neurons by repeated intracellular current injection did not reproduce LI-rTMS effects on neuronal properties. These data provide novel understanding of mechanisms underlying magnetic brain stimulation showing that, in addition to inducing biochemical plasticity, even weak magnetic fields can activate neurons and enduringly modulate their excitability. Abstract figure legend We examined by means of in vivo intracellular recordings in the rodent the effects of low-intensity (10 mT) repetitive transcranial magnetic stimulation (LI-rTMS) on the functional properties of primary somatosensory cortex pyramidal neurons. After a baseline period, during which cortical spontaneous activity and excitability were measured (Pre), LI-rTMS was applied at 10 Hz for 10 minutes. Despite their low intensity, magnetic pulses reliably evoked action potentials in cortical neurons. Ten minutes of LI-rTMS induced a progressive and long-lasting hyperpolarization of the neuronal membrane and a marked decrease in cell firing rate (Post). This was associated with an altered intrinsic neuronal excitability, characterized by reduced membrane input resistance and increased minimal current required to induce neuronal firing. A portion of this figure was created with biorender.com. This article is protected by copyright. All rights reserved.

State-dependent effects of neural stimulation on brain function and cognition

Invasive and non-invasive brain stimulation methods are widely used in neuroscience to establish causal relationships between distinct brain regions and the sensory, cognitive and motor functions they subserve. When combined with concurrent brain imaging, such stimulation methods can reveal patterns of neuronal activity responsible for regulating simple and complex behaviours at the level of local circuits and across widespread networks. Understanding how fluctuations in physiological states and task demands might influence the effects of brain stimulation on neural activity and behaviour is at the heart of how we use these tools to understand cognition. Here we review the concept of such 'state-dependent' changes in brain activity in response to neural stimulation, and consider examples from research on altered states of consciousness (for example, sleep and anaesthesia) and from task-based manipulations of selective attention and working memory. We relate relevant findings from non-invasive methods used in humans to those obtained from direct electrical and optogenetic stimulation of neuronal ensembles in animal models. Given the widespread use of brain stimulation as a research tool in the laboratory and as a means of augmenting or restoring brain function, consideration of the influence of changing physiological and cognitive states is crucial for increasing the reliability of these interventions.

Measures of differentiation and integration: One step closer to consciousness

Interpreting empirical measures of integration and differentiation as indices of cortical performance and memory consolidation during wakefulness rather than consciousness per se is inconsistent with the literature. Recent studies show that these theory-inspired measures can dissociate from such processes and reliably index the brain's capacity for experience. We consider this as a positive trend in consciousness research.

Mapping the Unconscious Brain: Insights From Advanced Neuroimaging

SUMMARY

Recent advances in neuroimaging have been a preeminent factor in the scientific effort to unravel mechanisms of conscious awareness and the pathophysiology of disorders of consciousness. In the first part of this review, we selectively discuss operational models of consciousness, the biophysical signal that is measured using different imaging modalities, and knowledge on disorders of consciousness that has been gleaned with each neuroimaging modality. Techniques considered include diffusion-weighted imaging, diffusion tensor imaging, different types of nuclear medicine imaging, functional MRI, magnetoencephalography, and the combined transcranial magnetic stimulation-electroencephalography approach. In the second part of this article, we provide an overview of how advanced neuroimaging can be leveraged to support neurological prognostication, the use of machine learning to process high-dimensional imaging data, potential applications in clinical practice, and future directions.

Toward a coherent structuration of disorders of consciousness expertise at a country scale: A proposal for France

Probing consciousness and cognitive abilities in non-communicating patients is one of the most challenging diagnostic issues. A fast growing medical and scientific literature explores the various facets of this challenge, often coined under the generic expression of 'Disorders of Consciousness' (DoC). Crucially, a set of independent converging results demonstrated both (1) the diagnostic and prognostic importance of this expertise, and (2) the need to combine behavioural measures with brain structure and activity data to improve diagnostic and prognostication accuracy as well as potential therapeutic intervention. Thus, probing consciousness in DoC patients appears as a crucial activity rich of human, medical, economic and ethical consequences, but this activity needs to be organized in order to offer this expertise to each concerned patient. More precisely, diagnosis of consciousness differs in difficulty across patients: while a minimal set of data can be sufficient to reach a confident result, some patients need a higher level of expertise that relies on additional behavioural and brain activity and brain structure measures. In order to enable this service on a systematic mode, we present two complementary proposals in the present article. First, we sketch a structuration of DoC expertise at a country-scale, namely France. More precisely, we suggest that a 2-tiers network composed of local (Tier-1) and regional (Tier-2) centers backed by distant electronic databases and algorithmic centers could optimally enable the systematic implementation of DoC expertise in France. Second, we propose to create a national common register of DoC patients in order to better monitor this activity, to improve its performance on the basis of nation-wide collected evidence, and to promote rational decision-making.

Computational Modeling of Information Propagation during the Sleep–Waking Cycle

Simple Summary

During the deep phases of sleep we do not normally wake up by a thunder, but we nevertheless notice it when awake. The exact same sound gets to our ears and cortex through the thalamus and still, it triggers two very different responses. There is growing experimental evidence that these two states of the brain—sleep and wakefulness—distribute sensory information in different ways across the cortex. In particular, during sleep, neuronal responses remain local and do not spread out across distant synaptically connected regions. On the contrary, during wakefulness, stimuli are able to elicit a wider spatial response. We have used a computational model of coupled cortical columns to study how these two propagation modes arise. Moreover, the transition from sleep-like to waking-like dynamics occurs in agreement with the synaptic homeostasis hypothesis and only requires the increase of excitatory conductances. We have found that, in order to reproduce the aforementioned observations, this parameter change has to be selectively applied: synaptic conductances between distinct columns have to be potentiated over local ones.

Abstract

Non-threatening familiar sounds can go unnoticed during sleep despite the fact that they enter our brain by exciting the auditory nerves. Extracellular cortical recordings in the primary auditory cortex of rodents show that an increase in firing rate in response to pure tones during deep phases of sleep is comparable to those evoked during wakefulness. This result challenges the hypothesis that during sleep cortical responses are weakened through thalamic gating. An alternative explanation comes from the observation that the spatiotemporal spread of the evoked activity by transcranial magnetic stimulation in humans is reduced during non-rapid eye movement (NREM) sleep as compared to the wider propagation to other cortical regions during wakefulness. Thus, cortical responses during NREM sleep remain local and the stimulus only reaches nearby neuronal populations. We aim at understanding how this behavior emerges in the brain as it spontaneously shifts between NREM sleep and wakefulness. To do so, we have used a computational neural-mass model to reproduce the dynamics of the sensory auditory cortex and corresponding local field potentials in these two brain states. Following the synaptic homeostasis hypothesis, an increase in a single parameter, namely the excitatory conductance g¯AMPA, allows us to place the model from NREM sleep into wakefulness. In agreement with the experimental results, the endogenous dynamics during NREM sleep produces a comparable, even higher, response to excitatory inputs to the ones during wakefulness. We have extended the model to two bidirectionally connected cortical columns and have quantified the propagation of an excitatory input as a function of their coupling. We have found that the general increase in all conductances of the cortical excitatory synapses that drive the system from NREM sleep to wakefulness does not boost the effective connectivity between cortical columns. Instead, it is the inter-/intra-conductance ratio of cortical excitatory synapses that should raise to facilitate information propagation across the brain.

Consciousness and complexity: a consilience of evidence

Over the last years, a surge of empirical studies converged on complexity-related measures as reliable markers of consciousness across many different conditions, such as sleep, anesthesia, hallucinatory states, coma, and related disorders. Most of these measures were independently proposed by researchers endorsing disparate frameworks and employing different methods and techniques. Since this body of evidence has not been systematically reviewed and coherently organized so far, this positive trend has remained somewhat below the radar. The aim of this paper is to make this consilience of evidence in the science of consciousness explicit. We start with a systematic assessment of the growing literature on complexity-related measures and identify their common denominator, tracing it back to core theoretical principles and predictions put forward more than 20 years ago. In doing this, we highlight a consistent trajectory spanning two decades of consciousness research and provide a provisional taxonomy of the present literature. Finally, we consider all of the above as a positive ground to approach new questions and devise future experiments that may help consolidate and further develop a promising field where empirical research on consciousness appears to have, so far, naturally converged.

Heartbeat-Evoked Cortical Potential during Sleep and Interoceptive Sensitivity: A Matter of Hypnotizability

Individuals with different hypnotizability display different interoceptive sensitivity/awareness (IS) and accuracy (IA), likely sustained by morphofunctional differences in interoception-related brain regions and, thus, possibly also observable during sleep. We investigated the heartbeat-evoked cortical potential amplitude (HEP) during sleep, its association with IS, and the role of hypnotizability in such association. We performed a retrospective analysis of polysomnographic recordings of 39 healthy volunteers. Participants completed the Multidimensional Assessment of Interoceptive Awareness (MAIA), measuring IS and IA, and underwent hypnotic assessment via the Stanford Hypnotic Susceptibility Scale, form A. The amplitude of the early and late HEP components was computed at EEG frontal and central sites. In both regions, the early HEP component was larger in N3 than in N2 and REM, with no difference between N2 and REM. Greater HEP amplitude at frontal than at central sites was found for the late HEP component. HEP amplitudes were not influenced by the autonomic state assessed by heart rate variability in the frequency and time domains. We report for the first time a positive correlation between the central late HEP component and MAIA dimensions, which became non-significant after removing the effects of hypnotizability. Our findings indicate that hypnotizability sustains the correlation between IS and HEP amplitude during sleep.

Increased cortical excitability but stable effective connectivity index during attentional lapses

Modern lifestyle curtails sleep and increases nighttime work and leisure activities. This has a deleterious impact on vigilance and attention, exacerbating chances of committing attentional lapses, with potential dramatic outcomes. Here, we investigated the brain signature of attentional lapses and assessed whether cortical excitability and brain response propagation were modified during lapses and whether these modifications changed with aging. We compared electroencephalogram (EEG) responses to transcranial magnetic stimulation (TMS) during lapse and no-lapse periods while performing a continuous attentional/vigilance task at night, after usual bedtime. Data were collected in healthy younger (N = 12; 18-30 years) and older individuals (N = 12; 50-70 years) of both sexes. The amplitude and slope of the first component of the TMS-evoked potential were larger during lapses. In contrast, TMS response scattering over the cortical surface, as well as EEG response complexity, did not significantly vary between lapse and no-lapse periods. Importantly, despite qualitative differences, age did not significantly affect any of the TMS-EEG measures. These results demonstrate that attentional lapses are associated with a transient increase of cortical excitability. This initial change is not associated with detectable changes in subsequent effective connectivity-as indexed by response propagation-and are not markedly different between younger and older adults. These findings could contribute to develop models aimed to predicting and preventing lapses in real-life situations.

State-independent and state-dependent patterns in the rat default mode network

Resting-state studies have typically assumed constant functional connectivity (FC) between brain regions, and these parameters of interest provide meaningful descriptions of the functional organization of the brain. A number of studies have recently provided evidence pointing to dynamic FC fluctuations in the resting brain, especially in higher-order regions such as the default mode network (DMN). The neural activities underlying dynamic FC remain poorly understood. Here, we recorded electrophysiological signals from DMN regions in freely behaving rats. The dynamic FCs between signals within the DMN were estimated by the phase locking value (PLV) method with sliding time windows across vigilance states [quiet wakefulness (QW) and slow-wave and rapid eye movement sleep (SWS and REMS)]. Factor analysis was then performed to reveal the hidden patterns within the DMN. We identified distinct spatial FC patterns according to the similarities between their temporal dynamics. Interestingly, some of these patterns were vigilance state-dependent, while others were independent across states. The temporal contributions of these patterns fluctuated over time, and their interactive relationships were different across vigilance states. These spatial patterns with dynamic temporal contributions and combinations may offer a flexible framework for efficiently integrating information to support cognition and behavior. These findings provide novel insights into the dynamic functional organization of the rat DMN.

Neuromodulatory therapies for patients with prolonged disorders of consciousness

Background:

Reviving patients with prolonged disorders of consciousness (DOCs) has always been focused and challenging in medical research. Owing to the limited effectiveness of available medicine, recent research has increasingly turned towards neuromodulatory therapies, involving the stimulation of neural circuits. We summarised the progression of research regarding neuromodulatory therapies in the field of DOCs, compared the differences among different studies, in an attempt to explore optimal stimulation patterns and parameters, and analyzed the major limitations of the relevant studies to facilitate future research.

Methods:

We performed a search in the PubMed database, using the concepts of DOCs and neuromodulation. Inclusion criteria were: articles in English, published after 2002, and reporting clinical trials of neuromodulatory therapies in human patients with DOCs.

Results:

Overall, 187 published articles met the search criteria, and 60 articles met the inclusion criteria. There are differences among these studies regarding the clinical efficacies of neurostimulation techniques for patients with DOCs, and large-sample studies are still lacking.

Conclusions:

Neuromodulatory techniques were used as trial therapies for DOCs wherein their curative effects were controversial. The difficulties in detecting residual consciousness, the confounding effect between the natural course of the disease and therapeutic effect, and the heterogeneity across patients are the major limitations. Large-sample, well-designed studies, and innovations for both treatment and assessment are anticipated in future research.

Decreased Evoked Slow-Activity After tDCS in Disorders of Consciousness

Due to life-saving medical advances, the diagnosis and treatment of disorders of consciousness (DOC) has become a more commonly occurring clinical issue. One recently developed intervention option has been non-invasive transcranial direct current stimulation. This dichotomy of patient responders may be better understood by investigating the mechanism behind the transcranial direct current stimulation (tDCS) intervention. The combination of transcranial magnetic stimulation and electroencephalography (TMS-EEG) has been an important diagnostic tool in DOC patients. We therefore examined the neural response using TMS-EEG both before and after tDCS in seven DOC patients (four diagnosed as in a minimally conscious state and three with unresponsive wakefulness syndrome). tDCS was applied over the dorsolateral prefrontal cortex, while TMS pulses were applied to the premotor cortex. None of the seven patients showed relevant behavioral change after tDCS. We did, however, find that the overall evoked slow activity was reduced following tDCS intervention. We also found a positive correlation between the strength of the slow activity and the amount of high-frequency suppression. However, there was no significant pre-post tDCS difference in high frequencies. In the resting-state EEG, we observed that both the incidence of slow waves and the positive slope of the wave were affected by tDCS. Taken together, these results suggest that the tDCS intervention can reduce the slow-wave activity component of bistability, but this may not directly affect high-frequency activity. We hypothesize that while reduced slow activity may be necessary for the recovery of neural function, especially consciousness, this alone is insufficient.

Clinical and advanced neurophysiology in the prognostic and diagnostic evaluation of disorders of consciousness: review of an IFCN-endorsed expert group

The analysis of spontaneous EEG activity and evoked potentialsis a cornerstone of the instrumental evaluation of patients with disorders of consciousness (DoC). Thepast few years have witnessed an unprecedented surge in EEG-related research applied to the prediction and detection of recovery of consciousness after severe brain injury,opening up the prospect that new concepts and tools may be available at the bedside. This paper provides a comprehensive, critical overview of bothconsolidated and investigational electrophysiological techniquesfor the prognostic and diagnostic assessment of DoC.We describe conventional clinical EEG approaches, then focus on evoked and event-related potentials, and finally we analyze the potential of novel research findings. In doing so, we (i) draw a distinction between acute, prolonged and chronic phases of DoC, (ii) attempt to relate both clinical and research findings to the underlying neuronal processes and (iii) discuss technical and conceptual caveats.The primary aim of this narrative review is to bridge the gap between standard and emerging electrophysiological measures for the detection and prediction of recovery of consciousness. The ultimate scope is to provide a reference and common ground for academic researchers active in the field of neurophysiology and clinicians engaged in intensive care unit and rehabilitation.

Decoding the circuitry of consciousness: From local microcircuits to brain-scale networks

Identifying the physiological processes underlying the emergence and maintenance of consciousness is one of the most fundamental problems of neuroscience, with implications ranging from fundamental neuroscience to the treatment of patients with disorders of consciousness (DOCs). One major challenge is to understand how cortical circuits at drastically different spatial scales, from local networks to brain-scale networks, operate in concert to enable consciousness, and how those processes are impaired in DOC patients. In this review, we attempt to relate available neurophysiological and clinical data with existing theoretical models of consciousness, while linking the micro- and macrocircuit levels. First, we address the relationships between awareness and wakefulness on the one hand, and cortico-cortical and thalamo-cortical connectivity on the other hand. Second, we discuss the role of three main types of GABAergic interneurons in specific circuits responsible for the dynamical reorganization of functional networks. Third, we explore advances in the functional role of nested oscillations for neural synchronization and communication, emphasizing the importance of the balance between local (high-frequency) and distant (low-frequency) activity for efficient information processing. The clinical implications of these theoretical considerations are presented. We propose that such cellular-scale mechanisms could extend current theories of consciousness.

Sleep Differentially Affects Early and Late Neuronal Responses to Sounds in Auditory and Perirhinal Cortices

A fundamental feature of sleep is reduced behavioral responsiveness to external events, but the extent of processing along sensory pathways remains poorly understood. While responses are comparable across wakefulness and sleep in auditory cortex (AC), neuronal activity in downstream regions remains unknown. Here we recorded spiking activity in 435 neuronal clusters evoked by acoustic stimuli in the perirhinal cortex (PRC) and in AC of freely behaving male rats across wakefulness and sleep. Neuronal responses in AC showed modest (∼10%) differences in response gain across vigilance states, replicating previous studies. By contrast, PRC neuronal responses were robustly attenuated by 47% and 36% during NREM sleep and REM sleep, respectively. Beyond the separation according to cortical region, response latency in each neuronal cluster was correlated with the degree of NREM sleep attenuation, such that late (>40 ms) responses in all monitored regions diminished during NREM sleep. The robust attenuation of late responses prevalent in PRC represents a novel neural correlate of sensory disconnection during sleep, opening new avenues for investigating the mediating mechanisms.SIGNIFICANCE STATEMENT Reduced behavioral responsiveness to sensory stimulation is at the core of sleep's definition, but it is still unclear how the sleeping brain responds differently to sensory stimuli. In the current study, we recorded neuronal spiking responses to sounds along the cortical processing hierarchy of rats during wakefulness and natural sleep. Responses in auditory cortex only showed modest changes during sleep, whereas sleep robustly attenuated the responses of neurons in high-level perirhinal cortex. We also found that, during NREM sleep, the response latency predicts the degree of sleep attenuation in individual neurons above and beyond their anatomical location. These results provide anatomical and temporal signatures of sensory disconnection during sleep and pave the way to understanding the underlying mechanisms.

Probing dynamical cortical gating of attention with concurrent TMS-EEG

Attention facilitates the gating of information from the sending brain area to the receiving areas, with this being achieved by dynamical changes in effective connectivity, which refers to the directional influences between cortical areas. To probe the effective connectivity and cortical excitability modulated by covertly shifted attention, transcranial magnetic stimulation (TMS) was used to directly perturb the right retinotopic visual cortex with respect to attended and unattended locations, and the impact of this was tracked from the stimulated area to other areas by concurrent use of electroencephalography (EEG). TMS to the contralateral visual hemisphere led to a stronger evoked potential than stimulation to the ipsilateral hemisphere. Moreover, stronger beta- and gamma-band effective connectivities assessed as time-delayed phase synchronizations between stimulated areas and other areas were observed when TMS was delivered to the contralateral hemisphere. These effects were more enhanced when they preceded more prominent alpha lateralization, which is known to be associated with attentional gating. Our results indicate that attention-regulated cortical feedforward effective connectivity can be probed by TMS-EEG with direct cortical stimulation, thereby bypassing thalamic gating. These results suggest that cortical gating of the feedforward input is achieved by regulating the effective connectivity in the phase dynamics between cortical areas.

EEG connectivity across sleep cycles and age

STUDY OBJECTIVES

In young adults, sleep is associated with important changes in cerebral connectivity during the first cycle of non-rapid eye movement (NREM) sleep. Our study aimed to evaluate how electroencephalography (EEG) connectivity during sleep differs between young and older individuals, and across the sleep cycles.

METHODS

We used imaginary coherence to estimate EEG connectivity during NREM and rapid eye movement (REM) sleep in 30 young (14 women; 20-30 years) and 29 older (18 women; 50-70 years) individuals. We also explored the association between coherence and cognitive measures.

RESULTS

Older individuals showed lower EEG connectivity in stage N2 but higher connectivity in REM and stage N3 compared to the younger cohort. Age-related differences in N3 were driven by the first sleep cycle. EEG connectivity was lower in REM than N3, especially in younger individuals. Exploratory analyses, controlling for the effects of age, indicated that higher EEG connectivity in delta during N2 was associated with higher processing speed, whereas, during REM sleep, lower EEG connectivity in delta and sigma was associated with higher verbal memory performance and a higher global averaged intelligence quotient score.

CONCLUSION

Our results indicated that age modifies sleep EEG connectivity but the direction and the magnitude of these effects differ between sleep stages and cycles. Results in N3 and REM point to a reduced ability of the older brains to disconnect as compared to the younger ones. Our results also support the notion that cerebral functional connectivity during sleep may be associated with cognitive functions.

The physiological effects of noninvasive brain stimulation fundamentally differ across the human cortex

Transcranial magnetic stimulation (TMS) is a noninvasive method to modulate brain activity and behavior in humans. Still, stimulation effects substantially vary across studies and individuals, thereby restricting the large-scale application of TMS in research or clinical settings. We revealed that low-frequency stimulation had opposite impact on the functional connectivity of sensory and cognitive brain regions. Biophysical modeling then identified a neuronal mechanism underlying these region-specific effects. Stimulation of the frontal cortex decreased local inhibition and disrupted feedforward and feedback connections. Conversely, identical stimulation increased local inhibition and enhanced forward signaling in the occipital cortex. Last, we identified functional integration as a macroscale network parameter to predict the region-specific effect of stimulation in individual subjects. In summary, we revealed how TMS modulation critically depends on the connectivity profile of target regions and propose an imaging marker to improve sensitivity of noninvasive brain stimulation for research and clinical applications.

COALIA: A Computational Model of Human EEG for Consciousness Research

Understanding the origin of the main physiological processes involved in consciousness is a major challenge of contemporary neuroscience, with crucial implications for the study of Disorders of Consciousness (DOC). The difficulties in achieving this task include the considerable quantity of experimental data in this field, along with the non-intuitive, nonlinear nature of neuronal dynamics. One possibility of integrating the main results from the experimental literature into a cohesive framework, while accounting for nonlinear brain dynamics, is the use of physiologically-inspired computational models. In this study, we present a physiologically-grounded computational model, attempting to account for the main micro-circuits identified in the human cortex, while including the specificities of each neuronal type. More specifically, the model accounts for thalamo-cortical (vertical) regulation of cortico-cortical (horizontal) connectivity, which is a central mechanism for brain information integration and processing. The distinct neuronal assemblies communicate through feedforward and feedback excitatory and inhibitory synaptic connections implemented in a template brain accounting for long-range connectome. The EEG generated by this physiologically-based simulated brain is validated through comparison with brain rhythms recorded in humans in two states of consciousness (wakefulness, sleep). Using the model, it is possible to reproduce the local disynaptic disinhibition of basket cells (fast GABAergic inhibition) and glutamatergic pyramidal neurons through long-range activation of vasoactive intestinal-peptide (VIP) interneurons that induced inhibition of somatostatin positive (SST) interneurons. The model (COALIA) predicts that the strength and dynamics of the thalamic output on the cortex control the local and long-range cortical processing of information. Furthermore, the model reproduces and explains clinical results regarding the complexity of transcranial magnetic stimulation TMS-evoked EEG responses in DOC patients and healthy volunteers, through a modulation of thalamo-cortical connectivity that governs the level of cortico-cortical communication. This new model provides a quantitative framework to accelerate the study of the physiological mechanisms involved in the emergence, maintenance and disruption (sleep, anesthesia, DOC) of consciousness.

Fractal dimension analysis of states of consciousness and unconsciousness using transcranial magnetic stimulation

BACKGROUND AND OBJECTIVE

Knowing whether a subject is conscious or not is a current challenge with a deep potential clinical impact. Recent theoretical considerations suggest that consciousness is linked to the complexity of distributed interactions within the corticothalamic system. The fractal dimension (FD) is a quantitative parameter that has been extensively used to analyse the complexity of structural and functional patterns of the human brain. In this study we investigate FD to assess whether it can discriminate between consciousness and different states of unconsciousness in healthy individuals.

METHODS

We study 69 high-density electroencephalogram (hd-EEG) measurements after transcranial magnetic stimulation (TMS) in 18 healthy subjects progressing from wakefulness to non-rapid eye movement (NREM) sleep and sedation induced by different anaesthetic agents (xenon and propofol). We quantify the integration of thalamocortical networks by calculating the FD of a spatiotemporal voxelization obtained from the locations of all sources that are significantly activated by the perturbation (4DFD). Moreover, we study the temporal evolution of the evoked spatial distributions and compute a measure of the differentiation of the response by means of the Higuchi FD (HFD). Finally, a Fractal Dimension Index (FDI) of perturbational complexity is computed as the product of both quantities: integration FD (4DFD) and differentiation FD (HFD).

RESULTS

We found that FDI is significantly lower in sleep and sedation when compared to wakefulness and provides an almost perfect intra-subject discrimination between conscious and unconscious states.

CONCLUSIONS

These results support the combination of FD measures of cortical integration and cortical differentiation as a novel paradigm of tracking complex spatiotemporal dynamics in the brain that could provide further insights into the link between complexity and the brain's capacity to sustain consciousness.

The neural tides of sleep and consciousness revealed by single-pulse electrical brain stimulation

Wakefulness and sleep arise from global changes in brain physiology that may also govern the flow of neural activity between cortical regions responsible for perceptual processing versus planning and action. To test whether and how the sleep/wake cycle affects the overall propagation of neural activity in large-scale brain networks, we applied single-pulse electrical stimulation (SPES) in patients implanted with intracranial EEG electrodes for epilepsy surgery. SPES elicited cortico-cortical spectral responses at high-gamma frequencies (CCSRHG, 80-150 Hz), which indexes changes in neuronal population firing rates. Using event-related causality (ERC) analysis, we found that the overall patterns of neural propagation among sites with CCSRHG were different during wakefulness and different sleep stages. For example, stimulation of frontal lobe elicited greater propagation toward parietal lobe during slow-wave sleep than during wakefulness. During REM sleep, we observed a decrease in propagation within frontal lobe, and an increase in propagation within parietal lobe, elicited by frontal and parietal stimulation, respectively. These biases in the directionality of large-scale cortical network dynamics during REM sleep could potentially account for some of the unique experiential aspects of this sleep stage. Together these findings suggest that the regulation of conscious awareness and sleep is associated with differences in the balance of neural propagation across large-scale frontal-parietal networks.

Posterior cingulate cortex can be a regulatory modulator of the default mode network in task-negative state

In recent years, the regulation of brain networks and interactions between different brain regions have become important issues in neuroscience. Effective connectivity can be employed to understand the modulatory mechanisms of brain networks. Previous studies have used the task-positive mode to examine effective connectivity between brain regions and very few studies have considered the task-negative mode to explore effective connectivity using electroencephalography (EEG). In the present study, high-density EEG experiments were conducted in 85 participants to measure EEG effective connectivity in relevant default mode network (DMN) brain regions (i.e., the medial prefrontal cortex [mPFC], posterior cingulate cortex [PCC], precuneus, and right frontal and left occipital regions) to observe the effects of different task-negative modes (eyes-open/eyes-closed state) and personality traits (introversion/extroversion). The results showed that in the eyes-closed state, the PCC had significantly increased effective connectivity and played a prominent role as a regulatory modulator of outflow to other regions mediated by alpha rhythms. The mPFC was a regulatory modulator of outflow in the eyes-open state mediated by delta rhythms. The introvert group showed stronger co-modulations in the relevant DMN regions than the extrovert group.

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.

Increased heartbeat-evoked potential during REM sleep in nightmare disorder

Nightmares are characterized by the experience of strong negative emotions occurring mainly during REM sleep. Some people suffer from nightmare disorder, which is defined by the repeated occurrence of nightmares and by significant distress in wakefulness. Yet, whether frequent nightmares relate to a general increase in emotional reactivity or arousal during sleep remains unclear. To address this question, we recorded heartbeat-evoked potentials (HEPs) during wakefulness, NREM and REM sleep in patients with nightmare disorder and healthy participants. The HEP represents a cortical (EEG) response to the heartbeat and indexes brain-body interactions, such as interoceptive processing and intrinsic levels of arousal. HEP amplitude is typically increased during states of high emotional arousal and motivation, and is decreased in depression. Here we compared the amplitude of HEPs between nightmare patients and healthy controls separately during AWAKE, NREM, REM periods, and found higher HEP amplitude in nightmare patients compared to healthy controls over a cluster of frontal regions only during REM sleep. This effect was not paralleled by any group difference in cardiac control measures (e.g. heart rate variability, interbeat interval). These findings corroborate the notion that nightmares are essentially a REM pathology and suggest that increased emotional arousal during REM sleep, as measured by HEP, is a physiological condition responsible for frequent nightmares. This result also supports that HEP may be used as a biomarker of increased emotional and sensory processing during REM sleep in these patients.

Sleep-State Dependent Alterations in Brain Functional Connectivity under Urethane Anesthesia in a Rat Model of Early-Stage Parkinson's Disease

Parkinson's disease (PD) is characterized by the gradual degeneration of dopaminergic neurons in the substantia nigra, leading to striatal dopamine depletion. A partial unilateral striatal 6-hydroxydopamine (6-OHDA) lesion causes 40-60% dopamine depletion in the lesioned rat striatum, modeling the early stage of PD. In this study, we explored the connectivity between the brain regions in partially 6-OHDA lesioned male Wistar rats under urethane anesthesia using functional magnetic resonance imaging (fMRI) at 5 weeks after the 6-OHDA infusion. Under urethane anesthesia, the brain fluctuates between the two states, resembling rapid eye movement (REM) and non-REM sleep states. We observed clear urethane-induced sleep-like states in 8/19 lesioned animals and 8/18 control animals. 6-OHDA lesioned animals exhibited significantly lower functional connectivity between the brain regions. However, we observed these differences only during the REM-like sleep state, suggesting the involvement of the nigrostriatal dopaminergic pathway in REM sleep regulation. Corticocortical and corticostriatal connections were decreased in both hemispheres, reflecting the global effect of the lesion. Overall, this study describes a promising model to study PD-related sleep disorders in rats using fMRI.

Dreaming in NREM Sleep: A High-Density EEG Study of Slow Waves and Spindles

Dreaming can occur in both rapid eye movement (REM) and non-REM (NREM) sleep. We recently showed that in both REM and NREM sleep, dreaming is associated with local decreases in slow wave activity (SWA) in posterior brain regions. To expand these findings, here we asked how specific features of slow waves and spindles, the hallmarks of NREM sleep, relate to dream experiences. Fourteen healthy human subjects (10 females) underwent nocturnal high-density EEG recordings combined with a serial awakening paradigm. Reports of dreaming, compared with reports of no experience, were preceded by fewer, smaller, and shallower slow waves, and faster spindles, especially in central and posterior cortical areas. We also identified a minority of very steep and large slow waves in frontal regions, which occurred on a background of reduced SWA and were associated with high-frequency power increases (local "microarousals") heralding the successful recall of dream content. These results suggest that the capacity of the brain to generate experiences during sleep is reduced in the presence of neuronal off-states in posterior and central brain regions, and that dream recall may be facilitated by the intermittent activation of arousal systems during NREM sleep.SIGNIFICANCE STATEMENT By combining high-density EEG recordings with a serial awakening paradigm in healthy subjects, we show that dreaming in non-rapid eye movement sleep occurs when slow waves in central and posterior regions are sparse, small, and shallow. We also identified a small subset of very large and steep frontal slow waves that are associated with high-frequency activity increases (local "microarousals") heralding successful recall of dream content. These results provide noninvasive measures that could represent a useful tool to infer the state of consciousness during sleep.

Combined Transcranial Magnetic Stimulation and Electroencephalography of the Dorsolateral Prefrontal Cortex

Transcranial magnetic stimulation (TMS) is a non-invasive method that produces neural excitation in the cortex by means of brief, time-varying magnetic field pulses. The initiation of cortical activation or its modulation depends on the background activation of the neurons of the cortical region activated, the characteristics of the coil, its position and its orientation with respect to the head. TMS combined with simultaneous electrocephalography (EEG) and neuronavigation (nTMS-EEG) allows for the assessment of cortico-cortical excitability and connectivity in almost all cortical areas in a reproducible manner. This advance makes nTMS-EEG a powerful tool that can accurately assess brain dynamics and neurophysiology in test-retest paradigms that are required for clinical trials. Limitations of this method include artifacts that cover the initial brain reactivity to stimulation. Thus, the process of removing artifacts may also extract valuable information. Moreover, the optimal parameters for dorsolateral prefrontal (DLPFC) stimulation are not fully known and current protocols utilize variations from the motor cortex (M1) stimulation paradigms. However, evolving nTMS-EEG designs hope to address these issues. The protocol presented here introduces some standard practices for assessing neurophysiological functioning from stimulation to the DLPFC that can be applied in patients with treatment resistant psychiatric disorders that receive treatment such as transcranial direct current stimulation (tDCS), repetitive transcranial magnetic stimulation (rTMS), magnetic seizure therapy (MST) or electroconvulsive therapy (ECT).

REM sleep respiratory behaviours mental content in narcoleptic lucid dreamers

Breathing is irregular during rapid eye-movement (REM) sleep, whereas it is stable during non-REM sleep. Why this is so remains a mystery. We propose that irregular breathing has a cortical origin and reflects the mental content of dreams, which often accompany REM sleep. We tested 21 patients with narcolepsy who had the exceptional ability to lucid dream in REM sleep, a condition in which one is conscious of dreaming during the dream and can signal lucidity with an ocular code. Sleep and respiration were monitored during multiple naps. Participants were instructed to modify their dream scenario so that it involved vocalizations or an apnoea, -two behaviours that require a cortical control of ventilation when executed during wakefulness. Most participants (86%) were able to signal lucidity in at least one nap. In 50% of the lucid naps, we found a clear congruence between the dream report (e.g., diving under water) and the observed respiratory behaviour (e.g., central apnoea) and, in several cases, a preparatory breath before the respiratory behaviour. This suggests that the cortico-subcortical networks involved in voluntary respiratory movements are preserved during REM sleep and that breathing irregularities during this stage have a cortical/subcortical origin that reflects dream content.

Investigating the neurobiology of schizophrenia and other major psychiatric disorders with Transcranial Magnetic Stimulation

Characterizing the neurobiology of schizophrenia and other major psychiatric disorders is one of the main challenges of the current research in psychiatry. The availability of Transcranial Magnetic Stimulation (TMS) allows to directly probe virtually any cortical areas, thus providing a unique way to assess the neurophysiological properties of cortical neurons. This article presents a review of studies employing TMS in combination with Motor Evoked Potentials (TMS/MEPs) and high density Electroencephalogram (TMS/hd-EEG) in schizophrenia and other major psychiatric disorders. Studies were identified by conducting a PubMed search using the following search item: "transcranial magnetic stimulation and (Schizophrenia or OCD or MDD or ADHD)". Studies that utilized TMS/MEP and/or TMS/hd-EEG measures to characterize cortical excitability, inhibition, oscillatory activity, and/or connectivity in psychiatric patients were selected. Across disorders, patients displayed a pattern of reduced cortical inhibition, and to a lesser extent increased excitability, in the motor cortex, which was most consistently established in Schizophrenia. Furthermore, psychiatric patients showed abnormalities in a number of TMS-evoked EEG oscillations, which was most prominent in the prefrontal cortex of Schizophrenia relative to healthy comparison subjects. Overall, results from this review point to significant impairments in cortical excitability, inhibition, and oscillatory activity, especially in frontal areas, in several major psychiatric disorders. Building on these findings, future studies employing TMS-based experimental paradigms may help elucidating the neurobiology of these psychiatric disorders, and may assess the contribution of TMS-related measures in monitoring and possibly maximizing the effectiveness of treatment interventions in psychiatric populations.