The human K-complex represents an isolated cortical down-state

Neurophysiological Basis of Sleep's Function on Memory and Cognition

A wealth of recent studies support a function of sleep on memory and cognitive processing. At a physiological level, sleep supports memory in a number of ways including neural replay and enhanced plasticity in the context of reduced ongoing input. This paper presents behavioral evidence for sleep's role in selective remembering and forgetting of declarative memories, in generalization of these memories, and in motor skill consolidation. Recent physiological data reviewed suggests how these behavioral changes might be supported by sleep. Importantly, in reviewing these findings, an integrated view of how distinct sleep stages uniquely contribute to memory processing emerges. This model will be useful in developing future behavioral and physiological studies to test predictions that emerge.

Distinct roles of GABAB1a- and GABAB1b-containing GABAB receptors in spontaneous and evoked termination of persistent cortical activity

During slow-wave sleep, cortical neurons display synchronous fluctuations between periods of persistent activity (‘UP states’) and periods of relative quiescence (‘DOWN states’). Such UP and DOWN states are also seen in isolated cortical slices. Recently, we reported that both spontaneous and evoked termination of UP states in slices from the rat medial entorhinal cortex (mEC) involves GABA_B receptors. Here, in order to dissociate the roles of GABA_B1a- and GABA_B1b-containing receptors in terminating UP states, we used mEC slices from mice in which either the GABA_B1a or the GABA_B1b subunit had been genetically ablated. Pharmacological blockade of GABA_B receptors using the antagonist CGP55845 prolonged the UP state duration in both wild-type mice and those lacking the GABA_B1b subunit, but not in those lacking the GABA_B1a subunit. Conversely, electrical stimulation of layer 1 could terminate an ongoing UP state in both wild-type mice and those lacking the GABA_B1a subunit, but not in those lacking the GABA_B1b subunit. Together with previous reports, indicating a preferential presynaptic location of GABA_B1a- and postsynaptic location of GABA_B1b-containing receptors, these results suggest that presynaptic GABA_B receptors contribute to spontaneous DOWN state transitions, whilst postsynaptic GABA_B receptors are essential for the afferent termination of the UP state. Inputs to layer 1 from other brain regions could thus provide a powerful mechanism for synchronizing DOWN state transitions across cortical areas via activation of GABAergic interneurons targeting postsynaptic GABA_B receptors.

On noninvasive source imaging of the human K-complex

OBJECTIVE

To assess whether existing noninvasive source localization techniques can provide valid solutions for large extended cortical sources we tested the capability of various methods of EEG source imaging (ESI) and magnetic source imaging (MSI) to localize the large superficial cortical generator of the human K-complex.

METHODS

We recently determined the intracranial distribution of the K-complex in a study of 6 patients with epilepsy (Clin. Neurophysiol. 121 (2010) 1176). Here we use the simultaneously acquired scalp EEG data to evaluate the validity and reliability of different ESI techniques. MEG recordings were acquired in 3 of the 6 patients, and K-complexes were recorded with high density EEG and MEG in an additional subject without epilepsy. ESI forward models included finite element method and boundary element method (BEM) volume conductors; for MSI, single sphere and BEM models were assessed. Inverse models included equivalent current dipole mapping and distributed current source modeling algorithms.

RESULTS

ESI and MSI provided physiologically invalid source solutions in all subjects, incorrectly localizing K-complex generators to deep midline structures. ESI provided consistent localization results across subjects for individual and averaged K-complexes, indicating solutions were not influenced by random noise or choice of model parameters. MEG K-complexes were lower in amplitude relative to baseline than EEG K-complexes, with less consistent localization results even after signal averaging, likely due to MEG-specific signal cancellation and sensitivity to source orientation. Distributed source modeling did not resolve the known problem of excessively deep fitting of single dipole locations for extended cortical sources.

CONCLUSIONS

Various noninvasive ESI and MSI techniques tested did not provide localization results for individual or averaged K-complexes that were physiologically meaningful or concordant with source locations indicated by intracranial recordings. Distributed source algorithms, though theoretically more appropriate for localizing extended cortical sources, showed the same propensity as dipole mapping to provide deep midline solutions for an extended superficial cortical source. Further studies are needed to determine appropriate modeling approaches for these large electrographic events.

SIGNIFICANCE

Existing noninvasive source localization techniques may not provide valid solutions for large extended cortical sources such as the human K-complex.

Rapid fragmentation of neuronal networks at the onset of propofol-induced unconsciousness

The neurophysiological mechanisms by which anesthetic drugs cause loss of consciousness are poorly understood. Anesthetic actions at the molecular, cellular, and systems levels have been studied in detail at steady states of deep general anesthesia. However, little is known about how anesthetics alter neural activity during the transition into unconsciousness. We recorded simultaneous multiscale neural activity from human cortex, including ensembles of single neurons, local field potentials, and intracranial electrocorticograms, during induction of general anesthesia. We analyzed local and global neuronal network changes that occurred simultaneously with loss of consciousness. We show that propofol-induced unconsciousness occurs within seconds of the abrupt onset of a slow (<1 Hz) oscillation in the local field potential. This oscillation marks a state in which cortical neurons maintain local patterns of network activity, but this activity is fragmented across both time and space. Local (<4 mm) neuronal populations maintain the millisecond-scale connectivity patterns observed in the awake state, and spike rates fluctuate and can reach baseline levels. However, neuronal spiking occurs only within a limited slow oscillation-phase window and is silent otherwise, fragmenting the time course of neural activity. Unexpectedly, we found that these slow oscillations occur asynchronously across cortex, disrupting functional connectivity between cortical areas. We conclude that the onset of slow oscillations is a neural correlate of propofol-induced loss of consciousness, marking a shift to cortical dynamics in which local neuronal networks remain intact but become functionally isolated in time and space.

Localization of dense intracranial electrode arrays using magnetic resonance imaging

Intracranial electrode arrays are routinely used in the pre-surgical evaluation of patients with medically refractory epilepsy, and recordings from these electrodes have been increasingly employed in human cognitive neurophysiology due to their high spatial and temporal resolution. For both researchers and clinicians, it is critical to localize electrode positions relative to the subject-specific neuroanatomy. In many centers, a post-implantation MRI is utilized for electrode detection because of its higher sensitivity for surgical complications and the absence of radiation. However, magnetic susceptibility artifacts surrounding each electrode prohibit unambiguous detection of individual electrodes, especially those that are embedded within dense grid arrays. Here, we present an efficient method to accurately localize intracranial electrode arrays based on pre- and post-implantation MR images that incorporates array geometry and the individual's cortical surface. Electrodes are directly visualized relative to the underlying gyral anatomy of the reconstructed cortical surface of individual patients. Validation of this approach shows high spatial accuracy of the localized electrode positions (mean of 0.96 mm ± 0.81 mm for 271 electrodes across 8 patients). Minimal user input, short processing time, and utilization of radiation-free imaging are strong incentives to incorporate quantitatively accurate localization of intracranial electrode arrays with MRI for research and clinical purposes. Co-registration to a standard brain atlas further allows inter-subject comparisons and relation of intracranial EEG findings to the larger body of neuroimaging literature.

Induction of slow oscillations by rhythmic acoustic stimulation

Slow oscillations are electrical potential oscillations with a spectral peak frequency of ∼0.8 Hz, and hallmark the electroencephalogram during slow-wave sleep. Recent studies have indicated a causal contribution of slow oscillations to the consolidation of memories during slow-wave sleep, raising the question to what extent such oscillations can be induced by external stimulation. Here, we examined whether slow oscillations can be effectively induced by rhythmic acoustic stimulation. Human subjects were examined in three conditions: (i) with tones presented at a rate of 0.8 Hz ('0.8-Hz stimulation'); (ii) with tones presented at a random sequence ('random stimulation'); and (iii) with no tones presented in a control condition ('sham'). Stimulation started during wakefulness before sleep and continued for the first ∼90 min of sleep. Compared with the other two conditions, 0.8-Hz stimulation significantly delayed sleep onset. However, once sleep was established, 0.8-Hz stimulation significantly increased and entrained endogenous slow oscillation activity. Sleep after the 90-min period of stimulation did not differ between the conditions. Our data show that rhythmic acoustic stimulation can be used to effectively enhance slow oscillation activity. However, the effect depends on the brain state, requiring the presence of stable non-rapid eye movement sleep.

Long-term relationships between cholinergic tone, synchronous bursting and synaptic remodeling

Cholinergic neuromodulation plays key roles in the regulation of neuronal excitability, network activity, arousal, and behavior. On longer time scales, cholinergic systems play essential roles in cortical development, maturation, and plasticity. Presumably, these processes are associated with substantial synaptic remodeling, yet to date, long-term relationships between cholinergic tone and synaptic remodeling remain largely unknown. Here we used automated microscopy combined with multielectrode array recordings to study long-term relationships between cholinergic tone, excitatory synapse remodeling, and network activity characteristics in networks of cortical neurons grown on multielectrode array substrates. Experimental elevations of cholinergic tone led to the abrupt suppression of episodic synchronous bursting activity (but not of general activity), followed by a gradual growth of excitatory synapses over hours. Subsequent blockage of cholinergic receptors led to an immediate restoration of synchronous bursting and the gradual reversal of synaptic growth. Neither synaptic growth nor downsizing was governed by multiplicative scaling rules. Instead, these occurred in a subset of synapses, irrespective of initial synaptic size. Synaptic growth seemed to depend on intrinsic network activity, but not on the degree to which bursting was suppressed. Intriguingly, sustained elevations of cholinergic tone were associated with a gradual recovery of synchronous bursting but not with a reversal of synaptic growth. These findings show that cholinergic tone can strongly affect synaptic remodeling and synchronous bursting activity, but do not support a strict coupling between the two. Finally, the reemergence of synchronous bursting in the presence of elevated cholinergic tone indicates that the capacity of cholinergic neuromodulation to indefinitely suppress synchronous bursting might be inherently limited.

Control of sleep and wakefulness

This review summarizes the brain mechanisms controlling sleep and wakefulness. Wakefulness promoting systems cause low-voltage, fast activity in the electroencephalogram (EEG). Multiple interacting neurotransmitter systems in the brain stem, hypothalamus, and basal forebrain converge onto common effector systems in the thalamus and cortex. Sleep results from the inhibition of wake-promoting systems by homeostatic sleep factors such as adenosine and nitric oxide and GABAergic neurons in the preoptic area of the hypothalamus, resulting in large-amplitude, slow EEG oscillations. Local, activity-dependent factors modulate the amplitude and frequency of cortical slow oscillations. Non-rapid-eye-movement (NREM) sleep results in conservation of brain energy and facilitates memory consolidation through the modulation of synaptic weights. Rapid-eye-movement (REM) sleep results from the interaction of brain stem cholinergic, aminergic, and GABAergic neurons which control the activity of glutamatergic reticular formation neurons leading to REM sleep phenomena such as muscle atonia, REMs, dreaming, and cortical activation. Strong activation of limbic regions during REM sleep suggests a role in regulation of emotion. Genetic studies suggest that brain mechanisms controlling waking and NREM sleep are strongly conserved throughout evolution, underscoring their enormous importance for brain function. Sleep disruption interferes with the normal restorative functions of NREM and REM sleep, resulting in disruptions of breathing and cardiovascular function, changes in emotional reactivity, and cognitive impairments in attention, memory, and decision making.

High-frequency neural activity and human cognition: past, present and possible future of intracranial EEG research

Human intracranial EEG (iEEG) recordings are primarily performed in epileptic patients for presurgical mapping. When patients perform cognitive tasks, iEEG signals reveal high-frequency neural activities (HFAs, between around 40 Hz and 150 Hz) with exquisite anatomical, functional and temporal specificity. Such HFAs were originally interpreted in the context of perceptual or motor binding, in line with animal studies on gamma-band ('40 Hz') neural synchronization. Today, our understanding of HFA has evolved into a more general index of cortical processing: task-induced HFA reveals, with excellent spatial and time resolution, the participation of local neural ensembles in the task-at-hand, and perhaps the neural communication mechanisms allowing them to do so. This review promotes the claim that studying HFA with iEEG provides insights into the neural bases of cognition that cannot be derived as easily from other approaches, such as fMRI. We provide a series of examples supporting that claim, drawn from studies on memory, language and default-mode networks, and successful attempts of real-time functional mapping. These examples are followed by several guidelines for HFA research, intended for new groups interested by this approach. Overall, iEEG research on HFA should play an increasing role in cognitive neuroscience in humans, because it can be explicitly linked to basic research in animals. We conclude by discussing the future evolution of this field, which might expand that role even further, for instance through the use of multi-scale electrodes and the fusion of iEEG with MEG and fMRI.

Phase-based measures of cross-frequency coupling in brain electrical dynamics under general anesthesia

The state of general anesthesia (GA) is associated with an increase in spectral power in scalp electroencephalogram (EEG) at frequencies below 40 Hz, including spectral peaks in the slow oscillation (SO, 0.1-1 Hz) and α (8-14 Hz) bands. Because conventional power spectral analyses are insensitive to possible cross-frequency coupling, the relationships among the oscillations at different frequencies remain largely unexplored. Quantifying such coupling is essential for improving clinical monitoring of anesthesia and understanding the neuroscience of this brain state. We tested the usefulness of two measures of cross-frequency coupling: the bispectrum-derived SynchFastSlow, which is sensitive to phase-phase coupling in different frequency bands, and modulogram analysis of coupling between SO phase and α rhythm amplitude. SynchFastSlow, a metric that is used in clinical depth-of-anesthesia monitors, showed a robust correlation with the loss of consciousness at the induction of propofol GA, but this could be largely explained by power spectral changes without considering cross-frequency coupling. Modulogram analysis revealed two distinct modes of cross-frequency coupling under GA. The waking and two distinct states under GA could be discriminated by projecting in a two-dimensional phase space defined by the SynchFastSlow and the preferred SO phase of α activity. Our results show that a stereotyped pattern of phase-amplitude coupling accompanies multiple stages of anesthetic-induced unconsciousness. These findings suggest that modulogram analysis can improve EEG based monitoring of brain state under GA.

Human gamma oscillations during slow wave sleep

Neocortical local field potentials have shown that gamma oscillations occur spontaneously during slow-wave sleep (SWS). At the macroscopic EEG level in the human brain, no evidences were reported so far. In this study, by using simultaneous scalp and intracranial EEG recordings in 20 epileptic subjects, we examined gamma oscillations in cerebral cortex during SWS. We report that gamma oscillations in low (30-50 Hz) and high (60-120 Hz) frequency bands recurrently emerged in all investigated regions and their amplitudes coincided with specific phases of the cortical slow wave. In most of the cases, multiple oscillatory bursts in different frequency bands from 30 to 120 Hz were correlated with positive peaks of scalp slow waves ("IN-phase" pattern), confirming previous animal findings. In addition, we report another gamma pattern that appears preferentially during the negative phase of the slow wave ("ANTI-phase" pattern). This new pattern presented dominant peaks in the high gamma range and was preferentially expressed in the temporal cortex. Finally, we found that the spatial coherence between cortical sites exhibiting gamma activities was local and fell off quickly when computed between distant sites. Overall, these results provide the first human evidences that gamma oscillations can be observed in macroscopic EEG recordings during sleep. They support the concept that these high-frequency activities might be associated with phasic increases of neural activity during slow oscillations. Such patterned activity in the sleeping brain could play a role in off-line processing of cortical networks.

Phase-amplitude coupling in human electrocorticography is spatially distributed and phase diverse

Spatially distributed phase-amplitude coupling (PAC) is a possible mechanism for selectively routing information through neuronal networks. If so, two key properties determine its selectivity and flexibility, phase diversity over space, and frequency diversity. To investigate these issues, we analyzed 42 human electrocorticographic recordings from 27 patients performing a working memory task. We demonstrate that (1) spatially distributed PAC occurred at distances >10 cm, (2) involved diverse preferred coupling phases, and (3) involved diverse frequencies. Using a novel technique [N-way decomposition based on the PARAFAC (for Parallel Factor analysis) model], we demonstrate that (4) these diverse phases originated mainly from the phase-providing oscillations. With these properties, PAC can be the backbone of a mechanism that is able to separate spatially distributed networks operating in parallel.

Large-scale cortical dynamics of sleep slow waves

Slow waves constitute the main signature of sleep in the electroencephalogram (EEG). They reflect alternating periods of neuronal hyperpolarization and depolarization in cortical networks. While recent findings have demonstrated their functional role in shaping and strengthening neuronal networks, a large-scale characterization of these two processes remains elusive in the human brain. In this study, by using simultaneous scalp EEG and intracranial recordings in 10 epileptic subjects, we examined the dynamics of hyperpolarization and depolarization waves over a large extent of the human cortex. We report that both hyperpolarization and depolarization processes can occur with two different characteristic time durations which are consistent across all subjects. For both hyperpolarization and depolarization waves, their average speed over the cortex was estimated to be approximately 1 m/s. Finally, we characterized their propagation pathways by studying the preferential trajectories between most involved intracranial contacts. For both waves, although single events could begin in almost all investigated sites across the entire cortex, we found that the majority of the preferential starting locations were located in frontal regions of the brain while they had a tendency to end in posterior and temporal regions.

First-pass selectivity for semantic categories in human anteroventral temporal lobe

How the brain encodes the semantic concepts represented by words is a fundamental question in cognitive neuroscience. Hemodynamic neuroimaging studies have robustly shown that different areas of posteroventral temporal lobe are selectively activated by images of animals versus manmade objects. Selective responses in these areas to words representing animals versus objects are sometimes also seen, but they are task-dependent, suggesting that posteroventral temporal cortex may encode visual categories, while more anterior areas encode semantic categories. Here, using the spatiotemporal resolution provided by intracranial macroelectrode and microelectrode arrays, we report category-selective responses to words representing animals and objects in human anteroventral temporal areas including inferotemporal, perirhinal, and entorhinal cortices. This selectivity generalizes across tasks and sensory modalities, suggesting that it represents abstract lexicosemantic categories. Significant category-specific responses are found in measures sensitive to synaptic activity (local field potentials, high gamma power, current sources and sinks) and unit-firing (multiunit and single-unit activity). Category-selective responses can occur at short latency (as early as 130 ms) in middle cortical layers and thus are extracted in the first pass of activity through the anteroventral temporal lobe. This activation may provide input to posterior areas for iconic representations when required by the task, as well as to the hippocampal formation for categorical encoding and retrieval of memories, and to the amygdala for emotional associations. More generally, these results support models in which the anteroventral temporal lobe plays a primary role in the semantic representation of words.

Sleep spindles in humans: insights from intracranial EEG and unit recordings

Sleep spindles are an electroencephalographic (EEG) hallmark of non-rapid eye movement (NREM) sleep and are believed to mediate many sleep-related functions, from memory consolidation to cortical development. Spindles differ in location, frequency, and association with slow waves, but whether this heterogeneity may reflect different physiological processes and potentially serve different functional roles remains unclear. Here we used a unique opportunity to record intracranial depth EEG and single-unit activity in multiple brain regions of neurosurgical patients to better characterize spindle activity in human sleep. We find that spindles occur across multiple neocortical regions, and less frequently also in the parahippocampal gyrus and hippocampus. Most spindles are spatially restricted to specific brain regions. In addition, spindle frequency is topographically organized with a sharp transition around the supplementary motor area between fast (13-15 Hz) centroparietal spindles often occurring with slow-wave up-states, and slow (9-12 Hz) frontal spindles occurring 200 ms later on average. Spindle variability across regions may reflect the underlying thalamocortical projections. We also find that during individual spindles, frequency decreases within and between regions. In addition, deeper NREM sleep is associated with a reduction in spindle occurrence and spindle frequency. Frequency changes between regions, during individual spindles, and across sleep may reflect the same phenomenon, the underlying level of thalamocortical hyperpolarization. Finally, during spindles neuronal firing rates are not consistently modulated, although some neurons exhibit phase-locked discharges. Overall, anatomical considerations can account well for regional spindle characteristics, while variable hyperpolarization levels can explain differences in spindle frequency.

Spatiotemporal dynamics of neocortical excitation and inhibition during human sleep

Intracranial recording is an important diagnostic method routinely used in a number of neurological monitoring scenarios. In recent years, advancements in such recordings have been extended to include unit activity of an ensemble of neurons. However, a detailed functional characterization of excitatory and inhibitory cells has not been attempted in human neocortex, particularly during the sleep state. Here, we report that such feature discrimination is possible from high-density recordings in the neocortex by using 2D multielectrode arrays. Successful separation of regular-spiking neurons (or bursting cells) from fast-spiking cells resulted in well-defined clusters that each showed unique intrinsic firing properties. The high density of the array, which allowed recording from a large number of cells (up to 90), helped us to identify apparent monosynaptic connections, confirming the excitatory and inhibitory nature of regular-spiking and fast-spiking cells, thus categorized as putative pyramidal cells and interneurons, respectively. Finally, we investigated the dynamics of correlations within each class. A marked exponential decay with distance was observed in the case of excitatory but not for inhibitory cells. Although the amplitude of that decline depended on the timescale at which the correlations were computed, the spatial constant did not. Furthermore, this spatial constant is compatible with the typical size of human columnar organization. These findings provide a detailed characterization of neuronal activity, functional connectivity at the microcircuit level, and the interplay of excitation and inhibition in the human neocortex.

Individualized localization and cortical surface-based registration of intracranial electrodes

In addition to its widespread clinical use, the intracranial electroencephalogram (iEEG) is increasingly being employed as a tool to map the neural correlates of normal cognitive function as well as for developing neuroprosthetics. Despite recent advances, and unlike other established brain-mapping modalities (e.g. functional MRI, magneto- and electroencephalography), registering the iEEG with respect to neuroanatomy in individuals-and coregistering functional results across subjects-remains a significant challenge. Here we describe a method which coregisters high-resolution preoperative MRI with postoperative computerized tomography (CT) for the purpose of individualized functional mapping of both normal and pathological (e.g., interictal discharges and seizures) brain activity. Our method accurately (within 3mm, on average) localizes electrodes with respect to an individual's neuroanatomy. Furthermore, we outline a principled procedure for either volumetric or surface-based group analyses. We demonstrate our method in five patients with medically-intractable epilepsy undergoing invasive monitoring of the seizure focus prior to its surgical removal. The straight-forward application of this procedure to all types of intracranial electrodes, robustness to deformations in both skull and brain, and the ability to compare electrode locations across groups of patients makes this procedure an important tool for basic scientists as well as clinicians.

The thalamic low-threshold Ca²⁺ potential: a key determinant of the local and global dynamics of the slow (<1 Hz) sleep oscillation in thalamocortical networks

During non-rapid eye movement sleep and certain types of anaesthesia, neurons in the neocortex and thalamus exhibit a distinctive slow (<1 Hz) oscillation that consists of alternating UP and DOWN membrane potential states and which correlates with a pronounced slow (<1 Hz) rhythm in the electroencephalogram. While several studies have claimed that the slow oscillation is generated exclusively in neocortical networks and then transmitted to other brain areas, substantial evidence exists to suggest that the full expression of the slow oscillation in an intact thalamocortical (TC) network requires the balanced interaction of oscillator systems in both the neocortex and thalamus. Within such a scenario, we have previously argued that the powerful low-threshold Ca(2+) potential (LTCP)-mediated burst of action potentials that initiates the UP states in individual TC neurons may be a vital signal for instigating UP states in related cortical areas. To investigate these issues we constructed a computational model of the TC network which encompasses the important known aspects of the slow oscillation that have been garnered from earlier in vivo and in vitro experiments. Using this model we confirm that the overall expression of the slow oscillation is intricately reliant on intact connections between the thalamus and the cortex. In particular, we demonstrate that UP state-related LTCP-mediated bursts in TC neurons are proficient in triggering synchronous UP states in cortical networks, thereby bringing about a synchronous slow oscillation in the whole network. The importance of LTCP-mediated action potential bursts in the slow oscillation is also underlined by the observation that their associated dendritic Ca(2+) signals are the only ones that inform corticothalamic synapses of the TC neuron output, since they, but not those elicited by tonic action potential firing, reach the distal dendritic sites where these synapses are located.

The multiple time scales of sleep dynamics as a challenge for modelling the sleeping brain

A particular property of the sleeping brain is that it exhibits dynamics on very different time scales ranging from the typical sleep oscillations such as sleep spindles and slow waves that can be observed in electroencephalogram (EEG) segments of several seconds duration over the transitions between the different sleep stages on a time scale of minutes to the dynamical processes involved in sleep regulation with typical time constants in the range of hours. There is an increasing body of work on mathematical and computational models addressing these different dynamics, however, usually considering only processes on a single time scale. In this paper, we review and present a new analysis of the dynamics of human sleep EEG at the different time scales and relate the findings to recent modelling efforts pointing out both the achievements and remaining challenges.

Inhibition recruitment in prefrontal cortex during sleep spindles and gating of hippocampal inputs

During light slow-wave sleep, the thalamo-cortical network oscillates in waxing-and-waning patterns at about 7 to 14 Hz and lasting for 500 ms to 3 s, called spindles, with the thalamus rhythmically sending strong excitatory volleys to the cortex. Concurrently, the hippocampal activity is characterized by transient and strong excitatory events, Sharp-Waves-Ripples (SPWRs), directly affecting neocortical activity--in particular the medial prefrontal cortex (mPFC)--which receives monosynaptic fibers from the ventral hippocampus and subiculum. Both spindles and SPWRs have been shown to be strongly involved in memory consolidation. However, the dynamics of the cortical network during natural sleep spindles and how prefrontal circuits simultaneously process hippocampal and thalamo-cortical activity remain largely undetermined. Using multisite neuronal recordings in rat mPFC, we show that during sleep spindles, oscillatory responses of cortical cells are different for different cell types and cortical layers. Superficial neurons are more phase-locked and tonically recruited during spindle episodes. Moreover, in a given layer, interneurons were always more modulated than pyramidal cells, both in firing rate and phase, suggesting that the dynamics are dominated by inhibition. In the deep layers, where most of the hippocampal fibers make contacts, pyramidal cells respond phasically to SPWRs, but not during spindles. Similar observations were obtained when analyzing γ-oscillation modulation in the mPFC. These results demonstrate that during sleep spindles, the cortex is functionnaly "deafferented" from its hippocampal inputs, based on processes of cortical origin, and presumably mediated by the strong recruitment of inhibitory interneurons. The interplay between hippocampal and thalamic inputs may underlie a global mechanism involved in the consolidation of recently formed memory traces.

Activity of cortical and thalamic neurons during the slow (<1 Hz) rhythm in the mouse in vivo

During NREM sleep and under certain types of anaesthesia, the mammalian brain exhibits a distinctive slow (<1 Hz) rhythm. At the cellular level, this rhythm correlates with so-called UP and DOWN membrane potential states. In the neocortex, these UP and DOWN states correspond to periods of intense network activity and widespread neuronal silence, respectively, whereas in thalamocortical (TC) neurons, UP/DOWN states take on a more stereotypical oscillatory form, with UP states commencing with a low-threshold Ca²⁺ potential (LTCP). Whilst these properties are now well recognised for neurons in cats and rats, whether or not they are also shared by neurons in the mouse is not fully known. To address this issue, we obtained intracellular recordings from neocortical and TC neurons during the slow (<1 Hz) rhythm in anaesthetised mice. We show that UP/DOWN states in this species are broadly similar to those observed in cats and rats, with UP states in neocortical neurons being characterised by a combination of action potential output and intense synaptic activity, whereas UP states in TC neurons always commence with an LTCP. In some neocortical and TC neurons, we observed ‘spikelets’ during UP states, supporting the possible presence of electrical coupling. Lastly, we show that, upon tonic depolarisation, UP/DOWN states in TC neurons are replaced by rhythmic high-threshold bursting at ~5 Hz, as predicted by in vitro studies. Thus, UP/DOWN state generation appears to be an elemental and conserved process in mammals that underlies the slow (<1 Hz) rhythm in several species, including humans.

Complex propagation patterns characterize human cortical activity during slow-wave sleep

Cortical electrical activity during nonrapid eye movement (non-REM) sleep is dominated by slow-wave activity (SWA). At larger spatial scales (∼2-30 cm), investigated by scalp EEG recordings, SWA has been shown to propagate globally over wide cortical regions as traveling waves, which has been proposed to serve as a temporal framework for neural plasticity. However, whether SWA dynamics at finer spatial scales also reflects the orderly propagation has not previously been investigated in humans. To reveal the local, finer spatial scale (∼1-6 cm) patterns of SWA propagation during non-REM sleep, electrocorticographic (ECoG) recordings were conducted from subdurally implanted electrode grids and a nonlinear correlation technique [mutual information (MI)] was implemented. MI analysis revealed spatial maps of correlations between cortical areas demonstrating SWA propagation directions, speed, and association strength. Highest correlations, indicating significant coupling, were detected during the initial positive-going deflection of slow waves. SWA propagated predominantly between adjacent cortical areas, albeit spatial noncontinuities were also frequently observed. MI analysis further uncovered significant convergence and divergence patterns. Areas receiving the most convergent activity were similar to those with high divergence rate, while reciprocal and circular propagation of SWA was also frequent. We hypothesize that SWA is characterized by distinct attributes depending on the spatial scale observed. At larger spatial scales, the orderly SWA propagation dominates; at the finer scale of the ECoG recordings, non-REM sleep is characterized by complex SWA propagation patterns.

Functional MRI of sleep spindles and K-complexes

OBJECTIVE

Sleep spindles and K-complexes are EEG hallmarks of non-REM sleep. However, the brain regions generating these discharges and the functional connections of their generators to other regions are not fully known. We investigated the neuroanatomical correlates of spindles and K-complexes using simultaneous EEG and fMRI.

METHODS

EEGs recorded during EEG-fMRI studies of 7 individuals were used for fMRI analysis. Higher-level group analyses were performed, and images were thresholded at Z ≥ 2.3.

RESULTS

fMRI of 106 spindles and 60 K-complexes was analyzed. Spindles corresponded to increased signal in thalami and posterior cingulate, and right precuneus, putamen, paracentral cortex, and temporal lobe. K-complexes corresponded to increased signal in thalami, superior temporal lobes, paracentral gyri, and medial regions of the occipital, parietal and frontal lobes. Neither corresponded to regions of decreased signal.

CONCLUSIONS

fMRI of both spindles and K-complexes depicts signal subjacent to the vertex, which likely indicates each discharges' source. The thalamic signal is consistent with thalamic involvement in sleep homeostasis. The limbic region's signal is consistent with roles in memory consolidation. Unlike the spindle, the K-complex corresponds to extensive signal in primary sensory cortices.

SIGNIFICANCE

Identification of these active regions contributes to the understanding of sleep networks and the physiology of awareness and memory during sleep.

Regional slow waves and spindles in human sleep

The most prominent EEG events in sleep are slow waves, reflecting a slow (<1 Hz) oscillation between up and down states in cortical neurons. It is unknown whether slow oscillations are synchronous across the majority or the minority of brain regions--are they a global or local phenomenon? To examine this, we recorded simultaneously scalp EEG, intracerebral EEG, and unit firing in multiple brain regions of neurosurgical patients. We find that most sleep slow waves and the underlying active and inactive neuronal states occur locally. Thus, especially in late sleep, some regions can be active while others are silent. We also find that slow waves can propagate, usually from medial prefrontal cortex to the medial temporal lobe and hippocampus. Sleep spindles, the other hallmark of NREM sleep EEG, are likewise predominantly local. Thus, intracerebral communication during sleep is constrained because slow and spindle oscillations often occur out-of-phase in different brain regions.

Independent contributions of cortical gray matter, aging, sex and alcoholism to K-complex amplitude evoked during sleep

STUDY OBJECTIVES

The amplitude of the N550 component derived from the averaged evoked K-complex decreases with normal aging and with alcoholism. The study was designed to determine whether these declines are related to the extent of cortical or subcortical shrinkage.

SETTING

Research sleep laboratory and MR imaging facility

PARTICIPANTS

26 abstinent long-term alcoholic men, 14 abstinent long-term alcoholic women, 18 control men, and 22 control women.

MEASUREMENTS AND RESULTS

MRI data collected at 3T were analyzed from alcoholic and control men and women previously reported to have significantly different evoked delta activity during sleep. Segmented and parcellated MRI data collected at 3T were compared between these groups and evaluated for correlation with evoked K-complex amplitude measured at FP1, Fz, FCz, Cz, CPz, and Pz. Cortical gray matter and regional subcortical tissue volumes entered as predictors into stepwise multiple regression identified cortical gray matter as a unique significant predictor of evoked K-complex at all sites. Age added independent variance at 5 of the 6 sites, while alcoholism and sex added independent variance at frontal sites only.

CONCLUSIONS

These data support recent intracranial studies showing cortical generation of K-complexes by indicating that cortical, but not subcortical volume contributes to K-complex amplitude. Establishing the extent of the relation between cortical volume and K-complex amplitude provides a mechanistic understanding of sleep compromise clinically relevant to normal aging, alcoholism, and likely other conditions affecting cortical volume and integrity.

Cellular mechanisms of high frequency oscillations in epilepsy: on the diverse sources of pathological activities

A major goal in epilepsy research is to understand the cellular basis of pathological forms of network oscillations, particularly those classified as high-frequency activity. What are the underlying mechanisms, and how do they arise? The topic of this review is the pattern of high-frequency oscillations that have been recorded in epileptic tissue, and how they might differ from physiological activity. We discuss recent experimental and clinical data with a major focus on the diverse sources of extracellular signals and the contribution of different neuronal populations, including GABAergic interneurons and glutamatergic principal cells.

Visually triggered K-complexes: a study in New Zealand rabbits

K-complexes are the EEG elements recorded during the state of developing sleep and during slow wave sleep. They are the only EEG components which can be elicited by sensory stimulation during sleep. The peculiarity of New Zealand rabbits to sleep with their eyes open allows the use of visual stimuli to elicit K-complexes. Experiments were performed with three rabbits. For visual stimulation, an elongated screen illuminated by LED flashes was attached to an implant on the animal's skull. The screen covered 20-120° of the visual field of one eye, and moved with the head during animal motion. One-millisecond flashes (15-s interval) were used during daytime in an illuminated room. Flashes elicited evoked responses, which, during the first stages of sleep, were often accompanied by K-complexes. The induced K-complexes were recorded from electrodes located both above visual and somatosensory areas. Evoked responses to visual stimuli were also recorded from both pairs of electrodes, although they were generated exclusively in the visual cortex. Correlation analysis showed that visual evoked responses and K-complexes induced by this stimulation were generated in visual cortex, and passively spread to the electrodes above the somatosensory area. Investigation of the latencies of induced K-complexes revealed two time windows when these complexes could be seen. Within each window there was no correlation between latency and amplitude of K-complexes. There was also no correlation between amplitudes of the visual evoked responses and K-complexes elicited by these responses. We propose that visual stimulation in light sleep temporarily opens a gate for some independent external signals, which evoke activation of the visual cortex, reflected in K-complexes.

Progressive changes in cortical state before and after spontaneous arousals from sleep in elderly and middle-aged women

Arousals are often considered to be events which have an abrupt onset and offset, indicating abrupt changes in the state of the cortex. We hypothesized that cortical state, as reflected in electroencephalograph (EEG) signals, exhibits progressive systematic changes before and after a spontaneous, isolated arousal and that the time courses of the spectral components of the EEG before and after an arousal would differ between healthy middle-aged and elderly subjects. We analyzed the power spectrum and Sample Entropy of the C3A2 EEG before and after isolated arousals from 20 middle-aged (47.2±2.0 years) and 20 elderly (78.4±3.8 years) women using polysomnograms from the Sleep Heart Health Study database. In middle-aged women, all EEG spectral band powers <16 Hz exhibited a significant increase relative to baseline at some time in the 21 s before an arousal, but only low- (0.2-2.0 Hz) and high-frequency (2.0-4.0 Hz) delta increased in elderly and only during the last 7 s pre-arousal. Post-arousal, all frequency bands below 12 Hz transiently fell below pre-arousal baseline in both age groups. Consistent with these findings, Sample Entropy decreased steadily before an arousal, increased markedly during the arousal, and remained above pre-arousal baseline levels for ∼30 s after the arousal. In middle-aged, but not in elderly, women the presence of early pre-arousal low delta power was associated with shorter arousals. We propose that this attenuation of the effect of the arousing stimulus may be related to the slow (<1 Hz) cortical state oscillation, and that prolonged alterations of cortical state due to arousals may contribute to the poor correlation between indices of arousals and indices of sleepiness or impaired cognitive function.

Temporal dynamics of cortical sources underlying spontaneous and peripherally evoked slow waves

Slow waves are the most prominent electroencephalographic feature of non-rapid eye movement (NREM) sleep. During NREM sleep, cortical neurons oscillate approximately once every second between a depolarized upstate, when cortical neurons are actively firing, and a hyperpolarized downstate, when cortical neurons are virtually silent (Destexhe et al., 1999; Steriade et al., 1993a, 2001). Intracellular recordings indicate that the origins of the slow oscillation are cortical and that corticocortical connections are necessary for their synchronization (Amzica and Steriade, 1995; Steriade et al., 1993b; Timofeev and Steriade, 1996; Timofeev et al., 2000). The currents produced by the near-synchronous slow oscillation of large populations of neurons appear on the scalp as electroencephalogram (EEG) slow waves (Amzica and Steriade, 1997). Despite this cellular understanding, questions remain about the role of specific cortical structures in individual slow waves. Early EEG studies of slow waves in humans were limited by the small number of derivations employed and by the difficulty of relating scalp potentials to underlying brain activity (Brazier, 1949; Roth et al., 1956). Functional neuroimaging methods offer exceptional spatial resolution, but lack the temporal resolution to track individual slow waves (Dang-Vu et al., 2008; Maquet, 2000). Intracranial recordings in patient populations are limited by the availability of medically necessary electrode placements and can be confounded by pathology and medications (Cash et al., 2009; Nir et al., 2011; Wenneberg 2010). Source modeling of high-density EEG recordings offers a unique opportunity for neuroimaging sleep slow waves. So far, the results have challenged several of the influential topographic observations about slow waves that had persisted since the original EEG recordings of sleep. These recent analyses revealed that individual slow waves are idiosyncratic cortical events and that the negative peak of the EEG slow wave often involves cortical structures not necessarily apparent from the scalp, like the inferior frontal gyrus, anterior cingulate, posterior cingulate, and precuneus (Murphy et al., 2009). In addition, not only do slow waves travel (Massimini et al., 2004), but they often do so preferentially through the areas comprising the major connectional backbone of the human cortex (Hagmann et al., 2008). In this chapter, we will review the cellular, intracranial recording, and neuroimaging results concerning EEG slow waves. We will also confront a long held belief about peripherally evoked slow waves, also known as K-complexes, namely that they are modality independent and do not involve cortical sensory pathways. The analysis included here is the first to directly compare K-complexes evoked with three different stimulation modalities within the same subject on the same night using high-density EEG.

Integrated brain circuits: neuron-astrocyte interaction in sleep-related rhythmogenesis

Although astrocytes are increasingly recognized as important modulators of neuronal excitability and information transfer at the synapse, whether these cells regulate neuronal network activity has only recently started to be investigated. In this article, we highlight the role of astrocytes in the modulation of circuit function with particular focus on sleep-related rhythmogenesis. We discuss recent data showing that these glial cells regulate slow oscillations, a specific thalamocortical activity that characterizes non-REM sleep, and sleep-associated behaviors. Based on these findings, we predict that our understanding of the genesis and tuning of thalamocortical rhythms will necessarily go through an integrated view of brain circuits in which non-neuronal cells can play important neuromodulatory roles.

Clinical correlations of midline spikes in children

Here we describe the clinical characteristics of children with isolated midline spikes, comparing patients with and without epilepsy, and examining the evolution of midline spikes on repeat EEGs. EEGs and clinical information of 69 patients with isolated midline spikes identified from our EEG database were reviewed. Forty-three patients had a history of seizures. Most patients had complex partial seizures, and had an approximately five times higher chance of having new discharges at other sites on repeat EEGs than the nonepilepsy group (odds ratio=4.95). Most children without epilepsy had developmental delay, attention deficit hyperactivity disorder, and pervasive developmental disorder. Their repeat EEGs showed disappearance or persistence of the midline discharges, with a two times higher probability of normal repeat EEG (58%) than the epilepsy group (24%) (odds ratio=2.40). Isolated midline spikes may represent focal epileptiform activity, but are also found in normal children and in children with developmental and behavioral problems.

A Comparison of Sleeplike Slow Oscillations in the Hippocampus Under Ketamine and Urethane Anesthesia

During sleep and anesthesia, a slow (≤1 Hz) synchronized rhythmic fluctuation of the network activity in the neocortex (nCTX) is prominent. This rhythm, called the slow oscillation (SO), corresponds to sequences of neuronal activity and inactivity (UP and DOWN states) in local and extended networks. Recently, this network pattern has also been described in the hippocampus (HPC) and, interestingly, it shows a dynamic correlation with ongoing SO in the nCTX. However, because of its transient nature during both sleep and urethane anesthesia, studying the SO in the HPC is difficult. Ketamine anesthesia is known to induce a uniform and continuous SO state in the nCTX, but its effects on HPC activity and HPC–nCTX interplay are unknown. Using multisite local field potential recordings, we investigated the effects of ketamine anesthesia on HPC activity and its relation to concurrent nCTX activity. We directly compared the spectral content and spatial distribution of laminar potentials and current source density (CSD) under ketamine to urethane anesthesia. Ketamine evoked stable bouts of SO in the HPC that had a peak frequency of 1.77 ± 0.08 Hz, slightly higher than that of urethane: 1.17 ± 0.07 Hz. Laminar voltage and CSD profiles of SO were highly correlated across ketamine and urethane anesthesia, although a higher degree of HPC–nCTX coherence at SO frequencies appeared under ketamine as opposed to urethane. In addition, activity in the gamma bandwidth (30–40 Hz) made up 4.7% of the power spectrum under ketamine, but accounted for only 2.0% of the power spectrum in urethane. Although some differences exist, the SO under ketamine anesthesia appears highly similar to that under urethane.

Laminar analysis of slow wave activity in humans

Brain electrical activity is largely composed of oscillations at characteristic frequencies. These rhythms are hierarchically organized and are thought to perform important pathological and physiological functions. The slow wave is a fundamental cortical rhythm that emerges in deep non-rapid eye movement sleep. In animals, the slow wave modulates delta, theta, spindle, alpha, beta, gamma and ripple oscillations, thus orchestrating brain electrical rhythms in sleep. While slow wave activity can enhance epileptic manifestations, it is also thought to underlie essential restorative processes and facilitate the consolidation of declarative memories. Animal studies show that slow wave activity is composed of rhythmically recurring phases of widespread, increased cortical cellular and synaptic activity, referred to as active- or up-state, followed by cellular and synaptic inactivation, referred to as silent- or down-state. However, its neural mechanisms in humans are poorly understood, since the traditional intracellular techniques used in animals are inappropriate for investigating the cellular and synaptic/transmembrane events in humans. To elucidate the intracortical neuronal mechanisms of slow wave activity in humans, novel, laminar multichannel microelectrodes were chronically implanted into the cortex of patients with drug-resistant focal epilepsy undergoing cortical mapping for seizure focus localization. Intracortical laminar local field potential gradient, multiple-unit and single-unit activities were recorded during slow wave sleep, related to simultaneous electrocorticography, and analysed with current source density and spectral methods. We found that slow wave activity in humans reflects a rhythmic oscillation between widespread cortical activation and silence. Cortical activation was demonstrated as increased wideband (0.3-200 Hz) spectral power including virtually all bands of cortical oscillations, increased multiple- and single-unit activity and powerful inward transmembrane currents, mainly localized to the supragranular layers. Neuronal firing in the up-state was sparse and the average discharge rate of single cells was less than expected from animal studies. Action potentials at up-state onset were synchronized within +/-10 ms across all cortical layers, suggesting that any layer could initiate firing at up-state onset. These findings provide strong direct experimental evidence that slow wave activity in humans is characterized by hyperpolarizing currents associated with suppressed cell firing, alternating with high levels of oscillatory synaptic/transmembrane activity associated with increased cell firing. Our results emphasize the major involvement of supragranular layers in the genesis of slow wave activity.

Heterogeneous neuronal firing patterns during interictal epileptiform discharges in the human cortex

Epileptic cortex is characterized by paroxysmal electrical discharges. Analysis of these interictal discharges typically manifests as spike-wave complexes on electroencephalography, and plays a critical role in diagnosing and treating epilepsy. Despite their fundamental importance, little is known about the neurophysiological mechanisms generating these events in human focal epilepsy. Using three different systems of microelectrodes, we recorded local field potentials and single-unit action potentials during interictal discharges in patients with medically intractable focal epilepsy undergoing diagnostic workup for localization of seizure foci. We studied 336 single units in 20 patients. Ten different cortical areas and the hippocampus, including regions both inside and outside the seizure focus, were sampled. In three of these patients, high density microelectrode arrays simultaneously recorded between 43 and 166 single units from a small (4 mm x 4 mm) patch of cortex. We examined how the firing rates of individual neurons changed during interictal discharges by determining whether the firing rate during the event was the same, above or below a median baseline firing rate estimated from interictal discharge-free periods (Kruskal-Wallis one-way analysis, P<0.05). Only 48% of the recorded units showed such a modulation in firing rate within 500 ms of the discharge. Units modulated during the discharge exhibited significantly higher baseline firing and bursting rates than unmodulated units. As expected, many units (27% of the modulated population) showed an increase in firing rate during the fast segment of the discharge (+ or - 35 ms from the peak of the discharge), while 50% showed a decrease during the slow wave. Notably, in direct contrast to predictions based on models of a pure paroxysmal depolarizing shift, 7.7% of modulated units recorded in or near the seizure focus showed a decrease in activity well ahead (0-300 ms) of the discharge onset, while 12.2% of units increased in activity in this period. No such pre-discharge changes were seen in regions well outside the seizure focus. In many recordings there was also a decrease in broadband field potential activity during this same pre-discharge period. The different patterns of interictal discharge-modulated firing were classified into more than 15 different categories. This heterogeneity in single unit activity was present within small cortical regions as well as inside and outside the seizure onset zone, suggesting that interictal epileptiform activity in patients with epilepsy is not a simple paroxysm of hypersynchronous excitatory activity, but rather represents an interplay of multiple distinct neuronal types within complex neuronal networks.

[Contribution of sleep to learning and memory]

A growing body of evidence indicates that sleep promotes memory consolidation. Although the first experimental evidence for this positive influence of sleep on memory was collected more than a century ago, the potential underlying neural mechanisms begins only to be conceptualized and experimentally characterized. A first hypothesis contrasted the influence of non-rapid eye movement (NREM) sleep and rapid eye movement (REM) sleep on declarative and procedural memories, respectively. As the understanding of the effects of sleep on memory consolidation during sleep progressed, the hypotheses were increasingly framed in terms of neural processes occurring with NREM and REM sleep, especially associated with phasic events such as slow waves, spindles or phasic REM sleep. This paper reviews two of these hypotheses: the synaptic downscaling and the systemic consolidation during non NREM sleep.

Large-scale microelectrode recordings of high-frequency gamma oscillations in human cortex during sleep

Gamma oscillations (40-120 Hz), usually associated with waking functions, can be recorded in the deepest stages of sleep in animals. The full details of their large-scale coordination across multiple cortical networks are still unknown. Furthermore, it is not known whether oscillations with similar characteristics are also present in the human brain. In this study, we examined the existence of gamma oscillations during polysomnographically defined sleep-wake states using large-scale microelectrode recordings (up to 56 channels), with single-cell and spike-time precision, in epilepsy patients. We report that low (40-80 Hz) and high (80-120 Hz) gamma oscillations recurrently emerged over time windows of several hundreds of milliseconds in all investigated cortical areas during slow-wave sleep. These patterns were correlated with positive peaks of EEG slow oscillations and marked increases in local cellular discharges, suggesting that they were associated with cortical UP states. These gamma oscillations frequently appeared at approximately the same time in many different cortical areas, including homotopic regions, forming large spatial patterns. Coincident firings with millisecond precision were strongly enhanced during gamma oscillations but only between cells within the same cortical area. Furthermore, in a significant number of cases, cortical gamma oscillations tended to occur within 100 ms after hippocampal ripple/sharp wave complexes. These data confirm and extend earlier animal studies reporting that gamma oscillations are transiently expressed during UP states during sleep. We speculate that these high-frequency patterns briefly restore "microwake" activity and are important for consolidation of memory traces acquired during previous awake periods.

The temporal structures and functional significance of scale-free brain activity

Scale-free dynamics, with a power spectrum following P proportional to f(-beta), are an intrinsic feature of many complex processes in nature. In neural systems, scale-free activity is often neglected in electrophysiological research. Here, we investigate scale-free dynamics in human brain and show that it contains extensive nested frequencies, with the phase of lower frequencies modulating the amplitude of higher frequencies in an upward progression across the frequency spectrum. The functional significance of scale-free brain activity is indicated by task performance modulation and regional variation, with beta being larger in default network and visual cortex and smaller in hippocampus and cerebellum. The precise patterns of nested frequencies in the brain differ from other scale-free dynamics in nature, such as earth seismic waves and stock market fluctuations, suggesting system-specific generative mechanisms. Our findings reveal robust temporal structures and behavioral significance of scale-free brain activity and should motivate future study on its physiological mechanisms and cognitive implications.