Changes in distinct brain systems identified with fMRI during smoking cessation treatment with varenicline: a review.

BACKGROUND: Varenicline is considered one of the most effective treatment options for smoking cessation. Nonetheless, it is only modestly effective. A deeper comprehension of the effects of varenicline by means of the in-depth review of relevant fMRI studies may assist in paving the development of more targeted and effective treatments. METHODOLOGY: A search of PubMed and Google Scholar databases was conducted with the keywords "functional magnetic resonance imaging" or "fMRI", and "varenicline". All peer-reviewed articles regarding the assessment of smokers with fMRI while undergoing treatment with varenicline and meeting the predefined criteria were included. RESULTS: Several studies utilizing different methodologies and targeting different aspects of brain function were identified. During nicotine withdrawal, decreased mesocorticolimbic activity and increased amygdala activity, as well as elevated amygdala-insula and insula-default-mode-network functional connectivity are alleviated by varenicline under specific testing conditions. However, other nicotine withdrawal-induced changes, including the decreased reward responsivity of the ventral striatum, the bilateral dorsal striatum and the anterior cingulate cortex are not influenced by varenicline suggesting a task-dependent divergence in neurocircuitry activation. Under satiety, varenicline treatment is associated with diminished cue-induced activation of the ventral striatum and medial orbitofrontal cortex concomitant with reduced cravings; during the resting state, varenicline induces activation of the lateral orbitofrontal cortex and suppression of the right amygdala. CONCLUSIONS: The current review provides important clues with regard to the neurobiological mechanism of action of varenicline and highlights promising research opportunities regarding the development of more selective and effective treatments and predictive biomarkers for treatment efficacy.

The Emergence of Spindles and K-Complexes and the Role of the Dorsal Caudal Part of the Anterior Cingulate as the Generator of K-Complexes.

The large multicomponent K-complex (KC) and the rhythmic spindle are the hallmarks of non-rapid eye movement (NREM)-2 sleep stage. We studied with magnetoencephalography (MEG) the progress of light sleep (NREM-1 and NREM-2) and emergence of KCs and spindles. Seven periods of interest (POI) were analyzed: wakefulness, the two quiet "core" periods of light sleep (periods free from any prominent phasic or oscillatory events) and four periods before and during spindles and KCs. For each POI, eight 2-s (1250 time slices) segments were used. We employed magnetic field tomography (MFT) to extract an independent tomographic estimate of brain activity from each MEG data sample. The spectral power was then computed for each voxel in the brain for each segment of each POI. The sets of eight maps from two POIs were contrasted using a voxel-by-voxel t-test. Only increased spectral power was identified in the four key contrasts between POIs before and during spindles and KCs versus the NREM2 core. Common increases were identified for all four subjects, especially within and close to the anterior cingulate cortex (ACC). These common increases were widespread for low frequencies, while for higher frequencies they were focal, confined to specific brain areas. For the pre-KC POI, only one prominent increase was identified, confined to the theta/alpha bands in a small area in the dorsal caudal part of ACC (dcACC). During KCs, the activity in this area grows in intensity and extent (in space and frequency), filling the space between the areas that expanded their low frequency activity (in the delta band) during NREM2 compared to NREM1. Our main finding is that prominent spectral power increases before NREM2 graphoelements are confined to the dcACC, and only for KCs, sharing common features with changes of activity in dcACC of the well-studied error related negativity (ERN). ERN is seen in awake state, in perceptual conflict and situations where there is a difference between expected and actual environmental or internal events. These results suggest that a KC is the sleep side of the awake state ERN, both serving their putative sentinel roles in the frame of the saliency network.

A hemodynamic network involving the insula, the cingulate, and the basal forebrain correlates with EEG synchronization phases of sleep instability.

The cyclic alternating pattern (CAP) encompasses the pseudoperiodic appearance of synchronized brain waves and rhythms and is considered a regulator of the nonrapid eye movement (NREM) sleep vigilance level, reflecting sleep instability. To determine the brain regions responsible for this phenomenon, we scored and analyzed sleep functional magnetic resonance imaging data acquired with simultaneous electroencephalography (EEG-fMRI). Group analysis revealed a set of brain areas showing statistically significant blood oxygen-level dependent signal correlated positively with the synchronization phase of the CAP, most prominent being the insula, the middle cingulate gyrus, and the basal forebrain. These areas may form a network acting as a synchronization pacemaker, controlling the level of NREM sleep vigilance and the sleeper's arousability.

Cross-subject network investigation of the EEG microstructure: A sleep spindles study.

BACKGROUND: The microstructural EEG elements and their functional networks relate to many neurophysiological functions of the brain and can reveal abnormalities. Despite the blooming variety of methods for estimating connectivity in the EEG of a single subject, a common pitfall is seen in relevant studies; grand averaging is used for estimating the characteristic connectivity patterns of a group of subjects. This averaging may distort results and fail to account for the internal variability of connectivity results across the subjects of a group. NEW METHOD: In this study, we propose a novel methodology for the cross-subject network investigation of EEG graphoelements. We used dimensionality reduction techniques in order to reveal internal connectivity properties and to examine how consistent these are across a number of subjects. In addition, graph theoretical measures were utilized to prioritize regions according to their network attributes. RESULTS: As proof of concept, we applied this method on fast sleep spindles across 10 healthy subjects. Neurophysiological findings revealed subnetworks of the spindle events across subjects, highlighting a predominance for occipito-parietal areas and their connectivity with frontal regions. COMPARISON WITH EXISTING METHODS: This is a new approach for the examination of within-group connectivities in EEG research. The results accounted for more than 85% of the overall data variance and the detected subnetworks were found to be meaningful down-projections of the grand average of the group, suggesting sufficient performance for the proposed methodology. CONCLUSION: We conclude that the proposed methodology can serve as an observatory tool for the EEG connectivity patterns across subjects, providing a supplementary analysis of the existing topography techniques.

Using MEG to Understand the Progression of Light Sleep and the Emergence and Functional Roles of Spindles and K-Complexes.

We used tomographic analysis of MEG signals to characterize regional spectral changes in the brain at sleep onset and during light sleep. We identified two key processes that may causally link to loss of consciousness during the quiet or "core" periods of NREM1. First, active inhibition in the frontal lobe leads to delta and theta spectral power increases. Second, activation suppression leads to sharp drop of spectral power in alpha and higher frequencies in posterior parietal cortex. During NREM2 core periods, the changes identified in NREM1 become more widespread, but focal increases also emerge in alpha and low sigma band power in frontal midline cortical structures, suggesting reemergence of some monitoring of internal and external environment. Just before spindles and K-complexes (KCs), the hallmarks of NREM2, we identified focal spectral power changes in pre-frontal cortex, mid cingulate, and areas involved in environmental and internal monitoring, i.e., the rostral and sub-genual anterior cingulate. During both spindles and KCs, alpha and low sigma bands increases. Spindles emerge after further active inhibition (increase in delta power) of the frontal areas responsible for environmental monitoring, while in posterior parietal cortex, power increases in low and high sigma bands. KCs are correlated with increase in alpha power in the monitoring areas. These specific regional changes suggest strong and varied vigilance changes for KCs, but vigilance suppression and sharpening of cognitive processing for spindles. This is consistent with processes designed to ensure accurate and uncorrupted memory consolidation. The changes during KCs suggest a sentinel role: evaluation of the salience of provoking events to decide whether to increase processing and possibly wake up, or to actively inhibit further processing of intruding influences. The regional spectral patterns of NREM1, NREM2, and their dynamic changes just before spindles and KCs reveal an edge effect facilitating the emergence of spindles and KCs and defining the precise loci where they might emerge. In the time domain, the spindles are seen in widespread areas of the cortex just as reported from analysis of intracranial data, consistent with the emerging consensus of a differential topography that depends on the kind of memory stored.

Spatiotemporal propagation patterns of generalized ictal spikes in childhood absence epilepsy.

OBJECTIVE: This work investigates the spatial distribution in time of generalized ictal spikes in the typical absences of childhood absence epilepsy (CAE). METHODS: We studied twelve children with CAE, who had more than two typical absences during their routine video-EEG. Seizures were identified, and ictal spikes were marked over the maximum electronegative peak, clustered, waveform-averaged and spatiotemporaly analyzed in 2D electrode space. RESULTS: Consistency of spatiotemporal patterns of ictal spikes was high between the absences of the same child, but low between children. Three main discharge patterns were identified: of anterio-posterior propagation, of posterio-anterior propagation and confined to the frontal/prefrontal regions. In 4 patients, the propagation patterns transformed during the seizure into either a lateralized diminished or a non-lateralized reverse direction form. Most spikes originated fronto-temporaly, all maximized over the frontal/prefrontal electrodes and mostly decayed prefrontaly. In 4 patients, lateralized propagation patterns were identified. CONCLUSIONS: Ictal spike propagation patterns suggest that epileptogenic CAE networks are personalized, interconnect distal areas in the brain - not the entire cortex - with a tendency to generate bilateral symmetrical discharges, sometimes unsuccessfully. The transformation of propagation patterns during the seizure indicates the existence of dynamic interplay within epileptogenic networks. SIGNIFICANCE: Our results support the revised concept of ictogenesis of ILAE definition in genetic (also known as idiopathic) generalized epilepsies. Understanding the focal features in CAE avoids misdiagnosis as focal epilepsy and inappropriate treatment.

Connectivity Measures in EEG Microstructural Sleep Elements.

During Non-Rapid Eye Movement sleep (NREM) the brain is relatively disconnected from the environment, while connectedness between brain areas is also decreased. Evidence indicates, that these dynamic connectivity changes are delivered by microstructural elements of sleep: short periods of environmental stimuli evaluation followed by sleep promoting procedures. The connectivity patterns of the latter, among other aspects of sleep microstructure, are still to be fully elucidated. We suggest here a methodology for the assessment and investigation of the connectivity patterns of EEG microstructural elements, such as sleep spindles. The methodology combines techniques in the preprocessing, estimation, error assessing and visualization of results levels in order to allow the detailed examination of the connectivity aspects (levels and directionality of information flow) over frequency and time with notable resolution, while dealing with the volume conduction and EEG reference assessment. The high temporal and frequency resolution of the methodology will allow the association between the microelements and the dynamically forming networks that characterize them, and consequently possibly reveal aspects of the EEG microstructure. The proposed methodology is initially tested on artificially generated signals for proof of concept and subsequently applied to real EEG recordings via a custom built MATLAB-based tool developed for such studies. Preliminary results from 843 fast sleep spindles recorded in whole night sleep of 5 healthy volunteers indicate a prevailing pattern of interactions between centroparietal and frontal regions. We demonstrate hereby, an opening to our knowledge attempt to estimate the scalp EEG connectivity that characterizes fast sleep spindles via an "EEG-element connectivity" methodology we propose. The application of the latter, via a computational tool we developed suggests it is able to investigate the connectivity patterns related to the occurrence of EEG microstructural elements. Network characterization of specified physiological or pathological EEG microstructural elements can potentially be of great importance in the understanding, identification, and prediction of health and disease.

Acute and chronic pharmacological models of generalized absence seizures.

This article reviews the contribution of pharmacologically induced acute and chronic animal models to our understanding of epilepsies featuring non-convulsive generalized seizures, the typical and atypical absence seizures. Typical absences comprise about 5% of all epilepsies regardless of age and the atypical ones are even more common. Although absence epilepsy was thought to be relatively benign, children with childhood epilepsy (CAE) turn out to have a high rate of pretreatment attention deficits that persist despite seizure freedom. The phenomenon of the absence seizure has long attracted research interest because of the clear temporal relationship of the conspicuous EEG rhythm of 3 Hz generalized spike and wave discharges (GSWD) and the parallel transient "loss of consciousness" characterizing these seizures which is time-locked with the GSWD. Indeed, clinical epileptologists, basic scientists and neurophysiologists have long recognized in GSWD a unique electrographic and behavioral marker of the genetic predisposition to most types of epilepsy. Interestingly, the subject is still controversial since it has recently been proposed that both classification terms of CAE currently in use: idiopathic and primary generalized, be abandoned - a point of debate. Both issues - underlying mechanisms and focal origin of absence seizures - may be further enlightened by observations in valid animal models.

Semi-automatic sleep EEG scoring based on the hypnospectrogram.

BACKGROUND: Sleep EEG organization is revealed by sleep scoring, a time-consuming process based on strictly defined visual criteria. NEW METHOD: We explore the possibility of sleep scoring using the whole-night time-frequency analysis, termed hypnospectrogram, with a computer-assisted K-means clustering method. RESULTS: Hypnograms were derived from 10 whole-night sleep EEG recordings using either standard visual scoring under the Rechtshaffen and Kales criteria or semi-automated analysis of the hypnospectrogram derived from a single EEG electrode. We measured substantial agreement between the two approaches with Cohen's kappa considering all 7 stages at 0.61. COMPARISON WITH EXISTING METHODS: A number of existing automated procedures have reached the level of human inter-rater agreement using the standard criteria. However, our approach offers the scorer the opportunity to exploit the information-rich graphic representation of the whole night sleep upon which the automated method works. CONCLUSION: This work suggests that the hypnospectrogram can be used as an objective graphical rep-resentation of sleep architecture upon which sleep scoring can be performed with computer-assisted methods.

One-class classification of temporal EEG patterns for K-complex extraction.

The purpose of this study was to detect one of the constituent brain waveforms in electroencephalography (EEG), the K-complex (KC). The role and significance of the KC include its engagement in information processing, sleep protection, and memory consolidation [1]. The method applies a two-step methodology in which first all the candidate KC waves are extracted based on fundamental morphological features imitating visual criteria. Subsequently each candidate wave is classified as KC or outlier according to its similarity to a set of different patterns (clusters) of annotated KCs. The different clusters are constructed by applying graph partitioning on the training set based on spectral clustering and exhibit temporal similarities in both signal and frequency content. The method was applied in whole-night sleep activity recorded using multiple EEG electrodes. Cross-validation was performed against visual scoring of singular generalized KCs during all sleep cycles and showed high sensitivity in KC detection.

An intra-K-complex oscillation with independent and labile frequency and topography in NREM sleep.

NREM sleep is characterized by K-complexes (KCs), over the negative phase of which we identified brief activity in the theta range. We recorded high resolution EEG of whole-night sleep from seven healthy volunteers and visually identified 2nd and 3rd stage NREM spontaneous KCs. We identified three major categories: (1) KCs without intra-KC-activity (iKCa), (2) KCs with non-oscillatory iKCa, and (3) KCs with oscillatory iKCa. The latter group of KCs with intra-KC-oscillation (iKCo), was clustered according to the duration of the iKCo. iKCa was observed in most KCs (1150/1522, 75%). iKCos with 2, 3, and 4 waves were observed in 52% (786/1522) of KCs in respective rates of 49% (386/786), 44%, and 7%. Successive waves of iKCos showed on average a shift of their maximal amplitude in the anterio-posterior axis, while the average amplitude of the slow KC showed no spatial shift in time. The iKCo spatial shift was accompanied by transient increases in instantaneous frequency from the theta band toward the alpha band, followed by decreases to upper theta. The study shows that the KC is most often concurrently accompanied by an independent brief iKCo exhibiting topographical relocation of amplitude maxima with every consecutive peak and transient increases in frequency. The iKCo features are potentially reflecting arousing processes taking place during the KC.

Spatiotemporal profiles of focal and generalised spikes in childhood absence epilepsy.

The EEG in childhood absence epilepsy (CAE) may contain focal and generalised spike-wave discharges (SWDs) with focal, mainly frontal, "lead-in". The term "frontal absence" has been used to imply fast, secondary, 3-Hz generalisation from occult frontal foci with potential impact on clinical EEG interpretation and syndrome classification. The aim of this study was to investigate the relationship between focal and generalised SWDs. We studied five children with CAE and examined a sufficient number of focal ("interictal") and generalised SWDs in order to obtain reliable analysis. All generalised SWDs with focal lead-in were "decomposed" into their "pre-generalisation" focal and "generalised" constituents, which were studied separately. Two types of focal SWD ("interictal" and "pre-generalisation") and generalised SWD were visually clustered into groups, waveform-averaged, and plotted in the 2D-electrode space. Spatiotemporal analysis demonstrated a variety (mean: 4.2 per child; SD: 2.12) of mainly frontal and occipital locations for pre-generalisation focal SWDs with propagation along the longitudinal axis in either direction and across homologous sites. Interictal focal SWDs demonstrated similar spatiotemporal characteristics. In contrast, the topography and propagation patterns of the first generalised spike of the SWD showed less variability (mean: 2.5 per child; SD: 2.07), mainly involved the fronto-temporal/temporal areas, and correlated poorly (<10%) with that of the pre-generalisation focal SWD. Our findings suggest that the process of generalised epileptogenesis in genetic epilepsies with electrographic "frontal absences" is far more complex than that proposed by the model for occult frontal focus with fast secondary generalisation. (Published with Supplemental data).

Spindle power is not affected after spontaneous K-complexes during human NREM sleep.

K-complexes and sleep spindles often grouped together characterize the second stage of NREM sleep and interest has been raised on a possible interaction of their underlying mechanisms. The reported inhibition of spindles power for about 15 seconds following evoked K-complexes has implications on their role in arousal. Our objective was to assess this inhibition following spontaneous K-complexes. We used time-frequency analysis of spontaneous K-complexes selected from whole-night EEG recordings of normal subjects. Our results show that spindles are most often observed at the positive phase following the peak of a spontaneous KC (70%). At latencies of 1-3 s following the peak of the K-complex, spindles almost disappear. Compared to long-term effects described for evoked KCs, sleep spindle power is not affected by spontaneous KCs for latencies of 5-15 s. Observation of the recurrence rate of sporadic spindles suggests that the reduction of power at 1-3 s most likely reflects a refractory period of spindles lasting for 1-2 s, rather than an effect of KCs. These results suggest that the mechanisms underlying spontaneous KCs do not affect spindle power as in the case of evoked KCs.

Focal and generalized EEG paroxysms in childhood absence epilepsy: topographic associations and distinctive behaviors during the first cycle of non-REM sleep.

PURPOSE: To better understand the nature of the focal spike-wave discharges (FSWDs) and focally led generalized spike-wave discharges (GSWDs) in typical childhood absence epilepsy (CAE) and by implication their nosologic and taxonomic significance. METHODS: Twenty-four abnormal video-electroencephalography (EEG) studies from 13 consecutive children with CAE and good response to appropriate antiepileptic drugs (AEDs) were analyzed. We studied the association between the topography of absence onset and the ictal automatisms, and the topographic correlation between FSWDs and GSWDs and their respective behavior during hyperventilation and the different states of phasic and nonphasic non-rapid eye movement (NREM) sleep. GSWDs were considered as of "focal" onset if a lead-in could be visibly recognized at a paper speed of 60 mm/s, and were classified by their topography. KEY FINDINGS: (1) Multifocal absences occurred in 10 children; anterior onset was noted in 81 absences (73.6%) from 12 children and posterior in 18 (16.4%) from 7 children; there was no association between topography of absence onset and ictal automatisms; (2) FSWDs occurred in 85% of children and were multifocal in 73% of them; 85% of FSWDs were anterior and 14% posterior; (3) there was good topographic association between FSWDs and the leading spike of GSWDs of "focal" onset in all children with FSWDs; (4) both FSWDs and GSWDs increased during hyperventilation; (5) FSWDs occurred mainly during noncyclical NREM sleep and during periods of reduced vigilance of cyclical NREM sleep, whereas GSWDs occurred during the periods of enhanced vigilance of NREM sleep; GSWDs occurred significantly more frequently than FSWDs at the transition from reduced to enhanced vigilance of NREM sleep. SIGNIFICANCE: Our findings suggest that in CAE focal EEG paroxysms reflect a system of multifocal nonlocalizing electrically unstable cortical areas that under the facilitatory influence of exogenous or endogenous factors like sleep instability can foster a corticothalamic response of sufficient strength to generate 3-Hz GSWDs that are conditionally sustainable and potentially ictal. FSWDs can be viewed as incomplete forms of the GSWDs; together they define the EEG identity of idiopathic "generalized" epileptogenesis.

Human non-rapid eye movement stage II sleep spindles are blocked upon spontaneous K-complex coincidence and resume as higher frequency spindles afterwards.

The purpose of this study was to investigate a potential relation between the K-complex (KC) and sleep spindles of non-rapid eye movement (NREM) stage II of human sleep. Using 58 electroencephalogram electrodes, plus standard electrooculogram and electromyogram derivations for sleep staging, brain activity during undisturbed whole-night sleep was recorded in six young adults (one of them participated twice). NREM stage II spindles (1256 fast and 345 slow) and 1131 singular generalized KCs were selected from all sleep cycles. The negative peak of the KC, the positive peak of the KC (where applicable), and the prominent negative wave peak of slow and fast spindles were marked as events of reference. Fast Fourier transform-based time-frequency analysis was performed over the marked events, which showed that: (a) fast spindles that happen to coincide with KC are interrupted (100% of 403 cases) and in their place a slower rhythmic oscillation often (80%) appears; and (b) spindles that are usually (72% of 1131) following KCs always have a higher frequency (by ∼1 Hz) than both the interrupted spindles and the individual fast spindles that are not in any way associated with a KC. This enhancement of spindle frequency could not be correlated to any of the KC parameters studied. The results of this study reveal a consistent interaction between the KC and the sleep spindle during NREM stage II in human sleep.

The hypnospectrogram: an EEG power spectrum based means to concurrently overview the macroscopic and microscopic architecture of human sleep.

This study introduces a complementary tool for the description and evaluation of human sleep. The nocturnal sleep electroencephalographic (EEG) time-frequency analysis (TFA) plot (hypnospectrogram for short) is hereby proposed as a means to visualize both the macroscopic and the microscopic architecture of human sleep. It provides the ability to concurrently visually inspect the coarse sleep architecture, that is, the time-course of non-rapid eye movement (NREM) and REM stages, along with finer sleep elements such as slow and fast spindles, NREM delta distribution, REM alpha and beta, microarousals (MAs), and NREM cyclic alternating patterns (CAPs). Furthermore, the hypnospectrogram has the potential to provide visual quality of sleep (QoS) evaluation, as well as reveal the dominant rhythms and their transitions for every cerebral locus - as represented at the electrode space - during the night.

MEG identifies dorsal medial brain activations during sleep.

All sleep stages contain epochs with high-amplitude electrophysiological phasic events, alternating with quieter "core periods." High-amplitude and core state properties cannot be disentangled with PET and fMRI. Here from high temporal resolution magnetoencephalography data, regional changes in neuronal activity were extracted during core periods in different frequency bands for each sleep stage and waking. We found that gamma-band activity increases in precuneus during light sleep (stages 1/2) and in the left dorso-medial prefrontal cortex (L-DMPFC) during deep sleep (stages 3/4). The L-DMPFC activated area expands laterally during rapid eye movement (REM) sleep, into a volume of about 5 cm(3) bounded by regions attributed to Theory of Mind (ToM) and default systems, both involved in introspection. Gamma band activity in this area was higher during REM sleep than other sleep stages and active wakefulness. There is a tantalizing correspondence between increased wide-band activity (dominated by low frequencies) in early non-REM (NREM) sleep stages and increases in gamma-band activity in late NREM and REM periods that we attribute to a lateral disinhibition mechanism. The results provide a description of regional electrophysiological changes in awake state, light and deep sleep, and REM sleep. These changes are most pronounced in the L-DMPFC and the other areas around the dorsal midline that are close to, but do not overlap with areas of the default and ToM systems, suggesting that the DMPFC, particularly in the left hemisphere, plays an important role in late NREM stages, in REM and possibly in dreaming.

Clustering of early cortical responses to median nerve stimulation from average and single trial MEG and EEG signals.

Median nerve electrical stimulation (MNES) produces early and strong averaged magnetoencephalography (MEG) or electroencephalography (EEG) signals, despite considerable single trial (ST) variability, demonstrated in separate MEG and EEG studies. Here, simultaneous MEG/EEG recordings are used to assess whether same or different aspects of ST variability are influencing EEG and MEG. Clustering techniques provided groupings for the ST timeseries for cortical responses to MNES derived from one modality. These groupings were applied to the corresponding ST timeseries derived from the other modality to quantify the similarity in variability captured by MEG and EEG signals. Estimates of early cortical activity elicited by MNES derived from MEG and EEG signals were very similar, provided ongoing mu rhythm was removed. Similarity between EEG and MEG estimates included both results based on average signals and measures of ST variability. Either MEG or EEG can provide a robust measure of the early cortical activity elicited by MNES as well as of its variability. Reliable indices of early cortical responses to MNES can be derived from either MEG or EEG data. These indices can be based on average signals, as is routinely done with clinical EEG, but it could also rely on hitherto little utilized measures of ST variability.