EEG-fMRI Methods for the Study of Brain Networks during Sleep

Sleep defined by arousal threshold reveals decreases in corticocortical functional correlations independently from the conventional sleep stages

Sleep research and sleep medicine have benefited from the use of polysomnography but have also suffered from an overreliance on the conventional, polysomnography-defined sleep stages. For example, reports of sleep-specific brain activity patterns have, with few exceptions, been constrained by assessing brain function as it relates to the conventional sleep stages. This limits the variety of sleep states and underlying activity patterns that one can discover. If undiscovered brain activity patterns exist during sleep, then removing the constraint of a stage-specific analysis may uncover them. The current study used all-night functional magnetic resonance imaging sleep data and defined sleep behaviorally with auditory arousal threshold (AAT) to begin to search for new brain states. It was hypothesized that, during sleep compared to wakefulness, corticocortical functional correlations would decrease. Functional correlation values calculated in a window immediately before the determination of AAT were entered into a linear mixed effects model, allowing multiple arousals across the night per subject into the analysis. The hypothesis was supported using both correlation matrices of brain networks and single seed-region analyses showing whole-brain maps. This represents a novel approach to studying the neuroanatomical correlates of sleep with high spatial resolution by defining sleep in a way that was independent from the conventional sleep stages. This work provides initial evidence to justify searching for sleep stages that are more neuroanatomically localized and unrelated to the conventional sleep stages.

Scratching the structure of moral agency: insights from philosophy applied to neuroscience

This paper explores the intersection between neuroscience and philosophy, particularly in the areas of moral philosophy and philosophy of mind. While traditional philosophical questions, such as those relating to free will and moral motivation, have been subject to much debate, the rise of neuroscience has led to a reinterpretation of these questions considering empirical evidence. This has led to tensions between those who believe neuroscience can provide definitive answers to very complex philosophical questions and those who are skeptical about the scope of these studies. However, the paper argues that neuroscientists and philosophers can work together to generate major scientific and social advances. To contribute to bridge the gap, in this paper we expose the complexity of moral experience from a philosophical point of view and point to two great challenges and gaps to cover from neurosciences.

Safety and data quality of EEG recorded simultaneously with multi-band fMRI

PURPOSE

Simultaneously recorded electroencephalography and functional magnetic resonance imaging (EEG-fMRI) is highly informative yet technically challenging. Until recently, there has been little information about EEG data quality and safety when used with newer multi-band (MB) fMRI sequences. Here, we measure the relative heating of a MB protocol compared with a standard single-band (SB) protocol considered to be safe. We also evaluated EEG quality recorded concurrently with the MB protocol on humans.

MATERIALS AND METHODS

We compared radiofrequency (RF)-related heating at multiple electrodes and magnetic field magnitude, B1+RMS, of a MB fMRI sequence with whole-brain coverage (TR = 440 ms, MB factor = 4) against a previously recommended, safe SB sequence using a phantom outfitted with a 64-channel EEG cap. Next, 9 human subjects underwent eyes-closed resting state EEG-fMRI using the MB sequence. Additionally, in three of the subjects resting state EEG was recorded also during the SB sequence and in an fMRI-free condition to directly compare EEG data quality across scanning conditions. EEG data quality was assessed by the ability to remove gradient and cardioballistic artifacts along with a clean spectrogram.

RESULTS

The heating induced by the MB sequence was lower than that of the SB sequence by a factor of 0.73 ± 0.38. This is consistent with an expected heating ratio of 0.64, calculated from the square of the ratio of B1+RMS values of the sequences. In the resting state EEG data, gradient and cardioballistic artifacts were successfully removed using traditional template subtraction. All subjects showed an individual alpha peak in the spectrogram with a posterior topography characteristic of eyes-closed EEG. The success of artifact rejection for the MB sequence was comparable to that in traditional SB sequences.

CONCLUSIONS

Our study shows that B1+RMS is a useful indication of the relative heating of fMRI protocols. This observation indicates that simultaneous EEG-fMRI recordings using this MB sequence can be safe in terms of RF-related heating, and that EEG data recorded using this sequence is of acceptable quality after traditional artifact removal techniques.

Multimodal EEG-fMRI: advancing insight into large-scale human brain dynamics

Advances in the acquisition and analysis of functional magnetic resonance imaging (fMRI) data are revealing increasingly rich spatiotemporal structure across the human brain. Nonetheless, uncertainty surrounding the origins of fMRI hemodynamic signals, and in the link between large-scale fMRI patterns and ongoing functional states, presently limits the neurobiological conclusions one can draw from fMRI alone. Electroencephalography (EEG) provides complementary information about neural electrical activity and state change, and simultaneously acquiring EEG together with fMRI presents unique opportunities for studying large-scale brain activity and gaining more information from fMRI itself. Here, we discuss recent progress in the use of concurrent EEG-fMRI to enrich the investigation of neural and physiological states and clarify the origins of fMRI hemodynamic signals. Throughout, we outline perspectives on future directions and open challenges.

Abnormal Brain Network Topology During Non-rapid Eye Movement Sleep and Its Correlation With Cognitive Behavioral Abnormalities in Narcolepsy Type 1

Objective: Simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) were applied to investigate the abnormalities in the topological characteristics of functional brain networks during non-rapid eye movement(NREM)sleep. And we investigated its relationship with cognitive abnormalities in patients with narcolepsy type 1 (NT1) disorder in the current study. Methods: The Beijing version of the Montreal Cognitive Assessment (MoCA-BJ) and EEG-fMRI were applied in 25 patients with NT1 and 25 age-matched healthy controls. All subjects participated in a nocturnal video polysomnography(PSG)study, and total sleep time (TST), percentage of TST (%TST) for each sleep stage and arousal index were calculated. The Epworth Sleepiness Score (ESS) was used to measure the degree of daytime sleepiness. The EEG-fMRI study was performed simultaneously using a 3T MRI system and a 32-channel MRI-compatible EEG system during sleep. Visual scoring of EEG data was used for sleep staging. Cognitive function was assessed for all subjects using the MoCA-BJ. The fMRI data were applied to establish a whole-brain functional connectivity network for all subjects, and the topological characteristics of the whole-brain functional network were analyzed using a graph-theoretic approach. The topological parameters were compared between groups. Lastly, the correlation between topological parameters and the assessment scale using Montreal Cognition was analyzed. Results: The MoCA-BJ scores were lower in patients with NT1 than in normal controls. Whole-brain global efficiency during stage N2 sleep in patients with NT1 displayed significantly lower small-world properties than in normal controls. Whole-brain functional network global efficiency in patients with NT1 was significantly correlated with MoCA-BJ scores. Conclusion: The global efficiency of the functional brain network during stage N2 sleep in patients with NT1 and the correspondingly reduced small-world attributes were associated with cognitive impairment.

Brain functional connectivity upon awakening from sleep predicts interindividual differences in dream recall frequency

Why do some individuals recall dreams every day while others hardly ever recall one? We hypothesized that sleep inertia-the transient period following awakening associated with brain and cognitive alterations-could be a key mechanism to explain interindividual differences in dream recall at awakening. To test this hypothesis, we measured the brain functional connectivity (combined electroencephalography-functional magnetic resonance imaging) and cognition (memory and mental calculation) of high dream recallers (HR, n = 20) and low dream recallers (LR, n = 18) in the minutes following awakening from an early-afternoon nap. Resting-state scans were acquired just after or before a 2 min mental calculation task, before the nap, 5 min after awakening from the nap, and 25 min after awakening. A comic was presented to the participants before the nap with no explicit instructions to memorize it. Dream(s) and comic recall were collected after the first post-awakening scan. As expected, between-group contrasts of the functional connectivity at 5 min post-awakening revealed a pattern of enhanced connectivity in HR within the default mode network (DMN) and between regions of the DMN and regions involved in memory processes. At the behavioral level, a between-group difference was observed in dream recall, but not comic recall. Our results provide the first evidence that brain functional connectivity right after awakening is associated with interindividual trait differences in dream recall and suggest that the brain connectivity of HR at awakening facilitates the maintenance of the short-term memory of the dream during the sleep-wake transition.

Simultaneous fMRI-EEG-Based Characterisation of NREM Parasomnia Disease: Methods and Limitations

Functional magnetic resonance imaging (fMRI) techniques and electroencephalography (EEG) were used to investigate sleep with a focus on impaired arousal mechanisms in disorders of arousal (DOAs). With a prevalence of 2–4% in adults, DOAs are significant disorders that are currently gaining attention among physicians. The paper describes a simultaneous EEG and fMRI experiment conducted in adult individuals with DOAs (n=10). Both EEG and fMRI data were validated by reproducing well established EEG and fMRI associations. A method for identification of both brain functional areas and EEG rhythms associated with DOAs in shallow sleep was designed. Significant differences between patients and controls were found in delta, theta, and alpha bands during awakening epochs. General linear models of the blood-oxygen-level-dependent signal have shown the secondary visual cortex and dorsal posterior cingulate cortex to be associated with alpha spectral power fluctuations, and the precuneus with delta spectral power fluctuations, specifically in patients and not in controls. Future EEG–fMRI sleep studies should also consider subject comfort as an important aspect in the experimental design.

Abnormal Thalamic Functional Connectivity During Light Non-Rapid Eye Movement Sleep in Children With Primary Nocturnal Enuresis

OBJECTIVE

To investigate abnormalities of thalamocortical and intrathalamic functional connectivity (FC) in children with primary nocturnal enuresis (PNE) during light non-rapid eye movement (NREM) sleep using a simultaneous electroencephalography (EEG)-functional magnetic resonance imaging (fMRI) method.

METHOD

Polysomnographic and EEG-fMRI data were obtained during sleep from 61 children with PNE (age 10.2 ± 1.7 years, 59% boys) and 61 age-matched controls (age 10.1 ± 1.4 years, 54% boys). All subjects first participated in one overnight video-polysomnographic study. Total sleep time, percentage of total sleep time in each sleep stage, arousal index, and awakening index were calculated. Simultaneous EEG-fMRI studies were then performed using a 3T MRI system with a 32-channel MRI-compatible EEG system. Visual scoring of EEG data permitted sleep staging. Thalamocortical and intrathalamic FCs in the waking state and at different stages of light sleep were calculated and compared.

RESULTS

Children with PNE had a higher percentage of total sleep time in light sleep and a higher arousal index compared with controls. Abnormal thalamocortical FCs were detected in the lateral prefrontal cortex, medial prefrontal cortex, and inferior parietal lobule during light NREM sleep. Abnormal intrathalamic FCs were also detected during light NREM sleep among the motor, occipital, prefrontal, and temporal subdivisions of the thalamus.

CONCLUSION

Abnormal prefrontal and parietal thalamocortical FCs, accompanied by abnormal intrathalamic FCs among the motor, occipital, prefrontal, and temporal subdivision of thalamus during light NREM sleep, may be related to abnormal sleep and enuresis in children with PNE.

Neuroimaging the sleeping brain: Insight on memory functioning in infants and toddlers

Episodic memory, or the ability to remember past events with specific detail, is central to the human experience and is related to learning and adaptive functioning in a variety of domains. In typically developing children, episodic memory emerges during infancy and improves during early childhood and beyond. Developmental processes within the hippocampus are hypothesized to be primarily responsible for both the early emergence and persistence of episodic memory in late infancy and early childhood. However, these hypotheses are based on non-human models. In-vivo investigations in early human development of hippocampal processes have been significantly limited by methodological challenges in acquiring neuroimaging data, particularly task-related functional neuroimaging data, from infants and toddlers. Recent studies in adults have shown neural activity in the brain regions supporting episodic memory during slow-wave sleep using functional magnetic resonance imaging (fMRI), and fMRI has been increasingly utilized in infancy and early childhood to address other research questions. We review initial evidence and present preliminary data showing the promise of this approach for examining hippocampal contribution to how infants and toddlers remember individual events, and their association with information about the context in which the event occurred. Overall, our review, integrated with the presentation of some preliminary data provides insight on leveraging sleep to gain new perspectives on early memory functioning.

qEEG Measures of Attentional and Memory Network Functions in Medical Students: Novel Targets for Pharmacopuncture to Improve Cognition and Academic Performance

Objectives

Attentional and memory functions are important aspects of neural plasticity that, theoretically, should be amenable to pharmacopuncture treatments. A previous study from our laboratory suggested that quantitative electroencephalographic (qEEG) measurements of theta/beta ratio (TBR), an index of attentional control, may be indicative of academic performance in a first-semester medical school course. The present study expands our prior report by extracting and analyzing data on frontal theta and beta asymmetries. We test the hypothesis that the amount of frontal theta and beta asymmetries (fTA, fBA), are correlated with TBR and academic performance, thereby providing novel targets for pharmacopuncture treatments to improve cognitive performance.

Methods

Ten healthy male volunteers were subjected to 5–10 min of qEEG measurements under eyes-closed conditions. The qEEG measurements were performed 3 days before each of first two block examinations in anatomy-physiology, separated by five weeks. Amplitudes of the theta and beta waveforms, expressed in μV, were used to compute TBR, fTA and fBA. Significance of changes in theta and beta EEG wave amplitude was assessed by ANOVA with post-hoc t-testing. Correlations between TBR, fTA, fBA and the raw examination scores were evaluated by Pearson’s product-moment coefficients and linear regression analysis.

Results

fTA and fBA were found to be negatively correlated with TBR (P<0.03, P<0.05, respectively) and were positively correlated with the second examination score (P<0.03, P=0.1, respectively).

Conclusion

Smaller fTA and fBA were associated with lower academic performance in the second of two first-semester medical school anatomy-physiology block examination. Future studies should determine whether these qEEG metrics are useful for monitoring changes associated with the brain’s cognitive adaptations to academic challenges, for predicting academic performance and for targeting phamacopuncture treatments to improve cognitive performance.

Hydrogel-Based Organic Subdural Electrode with High Conformability to Brain Surface

A totally soft organic subdural electrode has been developed by embedding an array of poly(3,4-ethylenedioxythiophene)-modified carbon fabric (PEDOT-CF) into the polyvinyl alcohol (PVA) hydrogel substrate. The mesh structure of the stretchable PEDOT-CF allowed stable structural integration with the PVA substrate. The electrode performance for monitoring electrocorticography (ECoG) was evaluated in saline solution, on ex vivo brains, and in vivo animal experiments using rats and porcines. It was demonstrated that the large double-layer capacitance of the PEDOT-CF brings low impedance at the frequency of brain wave including epileptic seizures, and PVA hydrogel substrate minimized the contact impedance on the brain. The most important unique feature of the hydrogel-based ECoG electrode was its shape conformability to enable tight adhesion even to curved, grooved surface of brains by just being placed. In addition, since the hydrogel-based electrode is totally organic, the simultaneous ECoG-fMRI measurements could be conducted without image artifacts, avoiding problems induced by conventional metallic electrodes.

Dynamic functional connectivity states characterize NREM sleep and wakefulness

According to recent neuroimaging studies, temporal fluctuations in functional connectivity patterns can be clustered into dynamic functional connectivity (DFC) states and correspond to fluctuations in vigilance. However, whether there consistently exist DFC states associated with wakefulness and sleep stages and what are the characteristics and electrophysiological origin of these states remain unclear. The aims of the current study were to investigate the properties of DFC in different sleep stages and to explore the relationship between the characteristics of DFC and slow‐wave activity. We collected both eyes‐closed wakefulness and sleep data from 48 healthy young volunteers with simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) recordings. EEG data were employed as the gold standard of sleep stage scoring, and DFC states were estimated based on fMRI data. The results demonstrated that DFC states of the fMRI signals consistently corresponded to wakefulness and nonrapid eye movement sleep stages independent of the number of clusters. Furthermore, the mean dwell time of these states significantly correlated with slow‐wave activity. The inclusion or omission of regression of the global signal and the selection of parcellation schemes exerted minimal effects on the current findings. These results provide strong evidence that DFC states underlying fMRI signals match the fluctuations of vigilance and suggest a possible electrophysiological source of DFC states corresponding to vigilance states.

All-night functional magnetic resonance imaging sleep studies

BACKGROUND

Previous functional magnetic resonance imaging (fMRI) sleep studies have been hampered by the difficulty of obtaining extended amounts of sleep in the sleep-adverse environment of the scanner and often have resorted to manipulations such as sleep depriving subjects before scanning. These manipulations limit the generalizability of the results.

NEW METHOD

The current study is a methodological validation of procedures aimed at obtaining all-night fMRI data in sleeping subjects with minimal exposure to experimentally induced sleep deprivation. Specifically, subjects slept in the scanner on two consecutive nights, allowing the first night to serve as an adaptation night.

RESULTS/COMPARISON WITH EXISTING METHOD(S)

Sleep scoring results from simultaneously acquired electroencephalography data on Night 2 indicate that subjects (n = 12) reached the full spectrum of sleep stages including slow-wave (M = 52.1 min, SD = 26.5 min) and rapid eye movement (REM, M = 45.2 min, SD = 27.9 min) sleep and exhibited a mean of 2.1 (SD = 1.1) nonREM-REM sleep cycles.

CONCLUSIONS

It was found that by diligently applying fundamental principles and methodologies of sleep and neuroimaging science, performing all-night fMRI sleep studies is feasible. However, because the two nights of the study were performed consecutively, some sleep deprivation from Night 1 as a cause of the Night 2 results is likely, so consideration should be given to replicating the current study with a washout period. It is envisioned that other laboratories can adopt the core features of this protocol to obtain similar results.

Objective and subjective measures of prior sleep-wake behavior predict functional connectivity in the default mode network during NREM sleep

INTRODUCTION

Prior sleep behavior has been shown to correlate with waking resting-state functional connectivity (FC) in the default mode network (DMN). However, the impact of sleep history on FC during sleep has not been investigated. The aim of this study was to establish whether there is an association between intersubject variability in habitual sleep behaviors and the strength of FC within the regions of the DMN during non-rapid eye movement (NREM) sleep.

METHODS

Wrist actigraphy and sleep questionnaires were used as objective and subjective measures of habitual sleep behavior, and EEG-functional MRI during NREM sleep was used to quantify sleep.

RESULTS

There was a significant, regionally specific association between the interindividual variability in objective (total sleep time on the night before scanning) and subjective (Insomnia Severity Index) measures of prior sleep-wake behavior and the strength of DMN FC during subsequent wakefulness and NREM sleep. In several cases, FC was related to sleep measures independently of sleep stage, suggesting that previous sleep history effects sleep FC globally across the stages.

CONCLUSIONS

This work highlights the need to consider a subject's prior sleep history in studies utilizing FC analysis during wakefulness and sleep, and indicates the complexity of the impact of sleep on the brain both in the short and long term.

Study of Resting-State Functional Connectivity Networks Using EEG Electrodes Position As Seed

Electroencephalography (EEG) is the standard diagnosis method for a wide variety of diseases such as epilepsy, sleep disorders, encephalopathies, and coma, among others. Resting-state functional magnetic resonance (rs-fMRI) is currently a technique used in research in both healthy individuals as well as patients. EEG and fMRI are procedures used to obtain direct and indirect measurements of brain neural activity: EEG measures the electrical activity of the brain using electrodes placed on the scalp, and fMRI detects the changes in blood oxygenation that occur in response to neural activity. EEG has a high temporal resolution and low spatial resolution, while fMRI has high spatial resolution and low temporal resolution. Thus, the combination of EEG with rs-fMRI using different methods could be very useful for research and clinical applications. In this article, we describe and show the results of a new methodology for processing rs-fMRI using seeds positioned according to the 10-10 EEG standard. We analyze the functional connectivity and adjacency matrices obtained using 65 seeds based on 10-10 EEG scheme and 21 seeds based on 10-20 EEG. Connectivity networks are created using each 10-20 EEG seeds and are analyzed by comparisons to the seven networks that have been found in recent studies. The proposed method captures high correlation between contralateral seeds, ipsilateral and contralateral occipital seeds, and some in the frontal lobe.

The Advents of Hybrid Imaging Modalities: A New Era in Neuroimaging Applications

Hybrid Imaging modalities have shown great potential in medical imaging and diagnosis. A more comprehensive and targeted view of neurological disorders can be achieved by blending the anatomical and functional perspectives through hybridization. With consistently improving technologies, there have been many developments in fused imaging techniques over the past few decades. This article provides an overview of various bimodal and trimodal hybrid imaging techniques being developed and explored for neuroimaging applications. Recent advancements and potentials are discussed for single photon emission computed tomography-computed tomography (SPECT-CT), positron emission tomography-CT (PET-CT), PET-magnetic resonance imaging (PET-MRI), electroencephalography-functional magnetic resonance imaging (EEG-fMRI), magnetoencephalography-fMRI (MEG-fMRI), EEG-near-infrared spectroscopy (EEG-NIRS), magnetic resonance-PET-EEG (MR-PET-EEG) and MR-PET-CT in the perspective of neuroimaging. A comparison of these hybrid approaches is provided on a single platform to analyze their performance on the basis of several common factors essential for imaging and analyzing neurological disorders and in vivo molecular processes. This article also provides an overview of recently developed advanced imaging technologies that are being hybridized with other imaging modalities and being explored as potential techniques for neuroscience. Novel approaches and clinical applications of hybrid neuroimaging are anticipated with inclusion of new technologies, better sensing capabilities, multimodal probes, and improved hybridization.

Altered thalamocortical and intra-thalamic functional connectivity during light sleep compared with wake

The transition from wakefulness into sleep is accompanied by modified activity in the brain's thalamocortical network. Sleep-related decreases in thalamocortical functional connectivity (FC) have previously been reported, but the extent to which these changes differ between thalamocortical pathways, and patterns of intra-thalamic FC during sleep remain untested. To non-invasively investigate thalamocortical and intra-thalamic FC as a function of sleep stage we recorded simultaneous EEG-fMRI data in 13 healthy participants during their descent into light sleep. Visual scoring of EEG data permitted sleep staging. We derived a functional thalamic parcellation during wakefulness by computing seed-based FC, measured between thalamic voxels and a set of pre-defined cortical regions. Sleep differentially affected FC between these distinct thalamic subdivisions and their associated cortical projections, with significant increases in FC during sleep restricted to sensorimotor connections. In contrast, intra-thalamic FC, both within and between functional thalamic subdivisions, showed significant increases with advancement into sleep. This work demonstrates the complexity and state-specific nature of functional thalamic relationships--both with the cortex and internally--over the sleep/wake cycle, and further highlights the importance of a thalamocortical focus in the study of sleep mechanisms.

Influence of epoch length on measurement of dynamic functional connectivity in wakefulness and behavioural validation in sleep

Conventional functional connectivity (FC) analysis of fMRI data derives a single measurement from the entire scan, generally several minutes in duration, which neglects the brain's dynamic behaviour and potentially loses important temporal information. Short-interval dynamic FC is an attractive proposition if methodological issues can be resolved and the approach validated. This was addressed in two ways; firstly we assessed FC of the posterior cingulate cortex (PCC) node of the default mode network (DMN) using differing temporal intervals (8s to 5min) in the waking-resting state. We found that 30-second intervals and longer produce spatially similar correlation topography compared to 15-minute static FC measurements, while providing increased temporal information about changes in FC that were consistent across interval lengths. Secondly, we used NREM sleep as a behavioural validation for the use of 30-second temporal intervals due to the known fMRI FC changes with sleep stage that have been observed in previous studies using intervals of several minutes. We found significant decreases in DMN FC with sleep depth which were most pronounced during stage N2 and N3. Additionally, both the proportion of time with strong PCC-DMN connectivity and the variability in dynamic FC decreased with sleep. We therefore show that dynamic FC with epochs as short as tens of seconds is a viable method for characterising intrinsic brain activity.

Decreased connectivity between the thalamus and the neocortex during human nonrapid eye movement sleep

STUDY OBJECTIVES

To determine whether thalamocortical signaling between the thalamus and the neocortex decreases from wakefulness to nonrapid eye movement (NREM) sleep.

DESIGN

Electroencephalography and functional magnetic resonance imaging data were collected simultaneously at 02:30 after 44 h of sleep deprivation.

SETTING

Clinical research hospital.

PARTICIPANTS

There were six volunteers (mean age 24.2 y, one male) who yielded sufficient amounts of usable, artifact-free data. All were healthy, right-handed native English speakers who consumed less than 710 mL of caffeinated beverages per day. Psychiatric, neurological, circadian, and sleep disorders were ruled out by reviewing each patient's clinical history. A standard clinical nocturnal polysomnogram was negative for sleep disorders.

INTERVENTIONS

N/A.

MEASUREMENTS AND RESULTS

A functional connectivity analysis was performed using the centromedian nucleus as the seed region. We determined the statistical significance of the difference between correlations obtained during wakefulness and during slow wave sleep. Neocortical regions displaying decreased thalamic connectivity were all heteromodal regions (e.g., medial frontal gyrus and posterior cingulate/precuneus), whereas there was a complete absence of neocortical regions displaying increased thalamic connectivity. Although more clusters of significant decreases were observed in stage 2 sleep, these results were similar to the results for slow wave sleep.

CONCLUSIONS

Results of this study provide evidence of a functional deafferentation of the neocortex during nonrapid eye movement (NREM) sleep in humans. This deafferentation likely accounts for increased sensory awareness thresholds during NREM sleep. Decreased thalamocortical connectivity in regions such as the posterior cingulate/precuneus also are observed in coma and general anesthesia, suggesting that changes in thalamocortical connectivity may act as a universal "control switch" for changes in consciousness that are observed in coma, general anesthesia, and natural sleep.

Present status and future challenges of electroencephalography- and magnetic resonance imaging-based monitoring in preclinical models of focal cerebral ischemia

Animal models are useful tools for better understanding the mechanisms underlying neurological deterioration after an ischemic insult as well as subsequent evolution of changes and recovery of functions. In response to the updated requirements for preclinical investigations of stroke to include relevant functional measurement techniques and biomarker endpoints, we here review the state of knowledge on application of some translational electrophysiological and neuroimaging methods, and in particular, electroencephalography monitoring and magnetic resonance imaging in rodent models of ischemic stroke. This may lead to improvement of diagnostic methods and identification of new therapeutic targets, which would considerably advance the translational value of preclinical stroke research.

Dynamic functional connectivity: promise, issues, and interpretations

The brain must dynamically integrate, coordinate, and respond to internal and external stimuli across multiple time scales. Non-invasive measurements of brain activity with fMRI have greatly advanced our understanding of the large-scale functional organization supporting these fundamental features of brain function. Conclusions from previous resting-state fMRI investigations were based upon static descriptions of functional connectivity (FC), and only recently studies have begun to capitalize on the wealth of information contained within the temporal features of spontaneous BOLD FC. Emerging evidence suggests that dynamic FC metrics may index changes in macroscopic neural activity patterns underlying critical aspects of cognition and behavior, though limitations with regard to analysis and interpretation remain. Here, we review recent findings, methodological considerations, neural and behavioral correlates, and future directions in the emerging field of dynamic FC investigations.

Sleep and the functional connectome

Sleep and the functional connectome are research areas with considerable overlap. Neuroimaging studies of sleep based on EEG-PET and EEG-fMRI are revealing the brain networks that support sleep, as well as networks that may support the roles and processes attributed to sleep. For example, phenomena such as arousal and consciousness are substantially modulated during sleep, and one would expect this modulation to be reflected in altered network activity. In addition, recent work suggests that sleep also has a number of adaptive functions that support waking activity. Thus the study of sleep may elucidate the circuits and processes that support waking function and complement information obtained from fMRI during waking conditions. In this review, we will discuss examples of this for memory, arousal, and consciousness after providing a brief background on sleep and on studying it with fMRI.

EEG acquisition in ultra-high static magnetic fields up to 9.4 T

The simultaneous acquisition of electroencephalographic (EEG) and functional magnetic resonance imaging (fMRI) data has gained momentum in recent years due to the synergistic effects of the two modalities with regard to temporal and spatial resolution. Currently, only EEG-data recorded in fields of up to 7 T have been reported. We investigated the feasibility of recording EEG inside a 9.4 T static magnetic field, specifically to determine whether meaningful EEG information could be recovered from the data after removal of the cardiac-related artefact. EEG-data were recorded reliably and reproducibly at 9.4 T and the cardiac-related artefact increased in amplitude with increasing B0, as expected. Furthermore, we were able to correct for the cardiac-related artefact and identify auditory event related responses at 9.4 T in 75% of subjects using independent component analysis (ICA). Also by means of ICA we detected event related spectral perturbations (ERSP) in subjects at 9.4 T in response to opening/closing the eyes comparable with the response at 0 T. Overall our results suggest that it is possible to record meaningful EEG data at ultra-high magnetic fields. The simultaneous EEG-fMRI approach at ultra-high-fields opens up the horizon for investigating brain dynamics at a superb spatial resolution and a temporal resolution in the millisecond domain.