Spiking-bursting activity in the thalamic reticular nucleus initiates sequences of spindle oscillations in thalamic networks

Electroencephalographic Microstates During Sleep and Wake in Schizophrenia

Background

Aberrant functional connectivity is a hallmark of schizophrenia. The precise nature and mechanism of dysconnectivity in schizophrenia remains unclear, but evidence suggests that dysconnectivity is different in wake versus sleep. Microstate analysis uses electroencephalography (EEG) to investigate large-scale patterns of coordinated brain activity by clustering EEG data into a small set of recurring spatial patterns, or microstates. We hypothesized that this technique would allow us to probe connectivity between brain networks at a fine temporal resolution and uncover previously unknown sleep-specific dysconnectivity.

Methods

We studied microstates during sleep in patients with schizophrenia by analyzing high-density EEG sleep data from 114 patients with schizophrenia and 79 control participants. We used a polarity-insensitive k-means analysis to extract a set of 6 microstate topographies.

Results

These 6 states included 4 widely reported canonical microstates. In patients and control participants, falling asleep was characterized by a shift from microstates A, B, and C to microstates D, E, and F. Microstate F was decreased in patients during wake, and microstate E was decreased in patients during sleep. The complexity of microstate transitions was greater in patients than control participants during wake, but this reversed during sleep.

Conclusions

Our findings reveal behavioral state-dependent patterns of cortical dysconnectivity in schizophrenia. Furthermore, these findings are largely unrelated to previous sleep-related EEG markers of schizophrenia such as decreased sleep spindles. Therefore, these findings are driven by previously undescribed sleep-related pathology in schizophrenia.

Emergent effects of synaptic connectivity on the dynamics of global and local slow waves in a large-scale thalamocortical network model of the human brain

Slow-wave sleep (SWS), characterized by slow oscillations (SOs, <1Hz) of alternating active and silent states in the thalamocortical network, is a primary brain state during Non-Rapid Eye Movement (NREM) sleep. In the last two decades, the traditional view of SWS as a global and uniform whole-brain state has been challenged by a growing body of evidence indicating that SO can be local and can coexist with wake-like activity. However, the mechanisms by which global and local SOs arise from micro-scale neuronal dynamics and network connectivity remain poorly understood. We developed a multi-scale, biophysically realistic human whole-brain thalamocortical network model capable of transitioning between the awake state and SWS, and we investigated the role of connectivity in the spatio-temporal dynamics of sleep SO. We found that the overall strength and a relative balance between long and short-range synaptic connections determined the network state. Importantly, for a range of synaptic strengths, the model demonstrated complex mixed SO states, where periods of synchronized global slow-wave activity were intermittent with the periods of asynchronous local slow-waves. An increase in the overall synaptic strength led to synchronized global SO, while a decrease in synaptic connectivity produced only local slow-waves that would not propagate beyond local areas. These results were compared to human data to validate probable models of biophysically realistic SO. The model producing mixed states provided the best match to the spatial coherence profile and the functional connectivity estimated from human subjects. These findings shed light on how the spatio-temporal properties of SO emerge from local and global cortical connectivity and provide a framework for further exploring the mechanisms and functions of SWS in health and disease.

The Feature of Sleep Spindle Deficits in Patients With Schizophrenia With and Without Auditory Verbal Hallucinations

BACKGROUND

Previous sleep electroencephalography studies have detected abnormalities in sleep architecture and sleep spindle deficits in schizophrenia (SCZ), but the consistency of these results was not robust, which might be due to the small sample size and the influence of clinical factors such as the various medication therapies and symptom heterogeneity. This study aimed to regard auditory verbal hallucinations (AVHs) as a pointcut to downscale the heterogeneity of SCZ and explore whether some sleep architecture and spindle parameters were more severely impaired in SCZ patients with AVHs compared with those without AVHs.

METHODS

A total of 90 SCZ patients with AVHs, 92 SCZ patients without AVHs, and 91 healthy control subjects were recruited, and parameters of sleep architecture and spindle activities were compared between groups. The correlation between significant sleep parameters and clinical indicators was analyzed.

RESULTS

Deficits of sleep spindle activities at prefrontal electrodes and intrahemispheric spindle coherence were observed in both AVH and non-AVH groups, several of which were more serious in the AVH group. In addition, deficits of spindle activities at central and occipital electrodes and interhemispheric spindle coherence mainly manifested accompanying AVH symptoms, most of which were retained in the medication-naive first-episode patients, and were associated with Auditory Hallucination Rating Scale scores.

CONCLUSIONS

Our results suggest that the underlying mechanism of spindle deficits might be different between SCZ patients with and without AVHs. In the future, the sleep feature of SCZ patients with different symptoms and the influence of clinical factors, such as medication therapy, should be further illustrated.

Thalamic control of sensory processing and spindles in a biophysical somatosensory thalamoreticular circuit model of wakefulness and sleep

Thalamoreticular circuitry plays a key role in arousal, attention, cognition, and sleep spindles, and is linked to several brain disorders. A detailed computational model of mouse somatosensory thalamus and thalamic reticular nucleus has been developed to capture the properties of over 14,000 neurons connected by 6 million synapses. The model recreates the biological connectivity of these neurons, and simulations of the model reproduce multiple experimental findings in different brain states. The model shows that inhibitory rebound produces frequency-selective enhancement of thalamic responses during wakefulness. We find that thalamic interactions are responsible for the characteristic waxing and waning of spindle oscillations. In addition, we find that changes in thalamic excitability control spindle frequency and their incidence. The model is made openly available to provide a new tool for studying the function and dysfunction of the thalamoreticular circuitry in various brain states.

Clocking Epilepsies: A Chronomodulated Strategy-Based Therapy for Rhythmic Seizures

Epilepsy is a neurological disorder characterized by hypersynchronous recurrent neuronal activities and seizures, as well as loss of muscular control and sometimes awareness. Clinically, seizures have been reported to display daily variations. Conversely, circadian misalignment and circadian clock gene variants contribute to epileptic pathogenesis. Elucidation of the genetic bases of epilepsy is of great importance because the genetic variability of the patients affects the efficacies of antiepileptic drugs (AEDs). For this narrative review, we compiled 661 epilepsy-related genes from the PHGKB and OMIM databases and classified them into 3 groups: driver genes, passenger genes, and undetermined genes. We discuss the potential roles of some epilepsy driver genes based on GO and KEGG analyses, the circadian rhythmicity of human and animal epilepsies, and the mutual effects between epilepsy and sleep. We review the advantages and challenges of rodents and zebrafish as animal models for epileptic studies. Finally, we posit chronomodulated strategy-based chronotherapy for rhythmic epilepsies, integrating several lines of investigation for unraveling circadian mechanisms underpinning epileptogenesis, chronopharmacokinetic and chronopharmacodynamic examinations of AEDs, as well as mathematical/computational modeling to help develop time-of-day-specific AED dosing schedules for rhythmic epilepsy patients.

Metabotropic glutamate receptor function and regulation of sleep-wake cycles

Metabotropic glutamate (mGlu) receptors are the most abundant family of G-protein coupled receptors and are widely expressed throughout the central nervous system (CNS). Alterations in glutamate homeostasis, including dysregulations in mGlu receptor function, have been indicated as key contributors to multiple CNS disorders. Fluctuations in mGlu receptor expression and function also occur across diurnal sleep-wake cycles. Sleep disturbances including insomnia are frequently comorbid with neuropsychiatric, neurodevelopmental, and neurodegenerative conditions. These often precede behavioral symptoms and/or correlate with symptom severity and relapse. Chronic sleep disturbances may also be a consequence of primary symptom progression and can exacerbate neurodegeneration in disorders including Alzheimer's disease (AD). Thus, there is a bidirectional relationship between sleep disturbances and CNS disorders; disrupted sleep may serve as both a cause and a consequence of the disorder. Importantly, comorbid sleep disturbances are rarely a direct target of primary pharmacological treatments for neuropsychiatric disorders even though improving sleep can positively impact other symptom clusters. This chapter details known roles of mGlu receptor subtypes in both sleep-wake regulation and CNS disorders focusing on schizophrenia, major depressive disorder, post-traumatic stress disorder, AD, and substance use disorder (cocaine and opioid). In this chapter, preclinical electrophysiological, genetic, and pharmacological studies are described, and, when possible, human genetic, imaging, and post-mortem studies are also discussed. In addition to reviewing the important relationships between sleep, mGlu receptors, and CNS disorders, this chapter highlights the development of selective mGlu receptor ligands that hold promise for improving both primary symptoms and sleep disturbances.

Sleep spindle alterations relate to working memory deficits in individuals at clinical high-risk for psychosis

STUDY OBJECTIVES

Sleep spindles are waxing and waning EEG waves exemplifying the main fast oscillatory activity occurring during NREM sleep. Several recent studies have established that sleep spindle abnormalities are present in schizophrenia spectrum disorders, including in early-course and first-episode patients, and those spindle deficits are associated with some of the cognitive impairments commonly observed in these patients. Cognitive deficits are often observed before the onset of psychosis and seem to predict poor functional outcomes in individuals at clinical high-risk for psychosis (CHR). Yet, the presence of spindle abnormalities and their relationship with cognitive dysfunction has not been investigated in CHR.

METHODS

In this study, overnight high-density (hd)-EEG recordings were collected in 24 CHR and 24 healthy control (HC) subjects. Spindle density, duration, amplitude, and frequency were computed and compared between CHR and HC. Furthermore, WM was assessed for both HC and CHR, and its relationship with spindle parameters was examined.

RESULTS

CHR had reduced spindle duration in centro-parietal and prefrontal regions, with the largest decrease in the right prefrontal area. Moderation analysis showed that the relation between spindle duration and spindle frequency was altered in CHR relative to HC. Furthermore, CHR had reduced WM performance compared to HC, which was predicted by spindle frequency, whereas in HC spindle frequency, duration, and density all predicted working memory performance.

CONCLUSION

Altogether, these findings indicate that sleep spindles are altered in CHR individuals, and spindle alterations are associated with their cognitive deficits, thus representing a sleep-specific putative neurophysiological biomarker of cognitive dysfunction in psychosis risk.

The space-time profiles of sleep spindles and their coordination with slow oscillations on the electrode manifold

Sleep spindles are important for sleep quality and cognitive functions, with their coordination with slow oscillations (SOs) potentially organizing cross-region reactivation of memory traces. Here, we describe the organization of spindles on the electrode manifold and their relation to SOs. We analyzed the sleep night EEG of 34 subjects and detected spindles and SOs separately at each electrode. We compared spindle properties (frequency, duration, and amplitude) in slow wave sleep (SWS) and Stage 2 sleep (S2); and in spindles that coordinate with SOs or are uncoupled. We identified different topographical spindle types using clustering analysis that grouped together spindles co-detected across electrodes within a short delay (±300 ms). We then analyzed the properties of spindles of each type, and coordination to SOs. We found that SWS spindles are shorter than S2 spindles, and spindles at frontal electrodes have higher frequencies in S2 compared to SWS. Furthermore, S2 spindles closely following an SO (about 10% of all spindles) show faster frequency, shorter duration, and larger amplitude than uncoupled ones. Clustering identified Global, Local, Posterior, Frontal-Right and Left spindle types. At centro-parietal locations, Posterior spindles show faster frequencies compared to other types. Furthermore, the infrequent SO-spindle complexes are preferentially recruiting Global SO waves coupled with fast Posterior spindles. Our results suggest a non-uniform participation of spindles to complexes, especially evident in S2. This suggests the possibility that different mechanisms could initiate an SO-spindle complex compared to SOs and spindles separately. This has implications for understanding the role of SOs-spindle complexes in memory reactivation.

fMRI spectral signatures of sleep

The conventional wisdom that sleep is a global state, affecting the whole brain uniformly and simultaneously, was overturned by the discovery of local sleep, where individual neuronal populations were found to be asleep and the rest of the brain awake. However, due to the difficulty of monitoring local neuronal states in humans, our understanding of local sleep remains limited. Using simultaneous functional MRI (fMRI) and electroencephalography, we find that the oscillations of brain hemodynamic activity provide signatures of sleep at a local neuronal population level. We show that the fMRI signatures of sleep can be employed to monitor local neuronal states and investigate which brain regions are the first to fall asleep or wake up at wake–sleep transitions.

Sleep can be distinguished from wake by changes in brain electrical activity, typically assessed using electroencephalography (EEG). The hallmark of nonrapid-eye-movement (NREM) sleep is the shift from high-frequency, low-amplitude wake EEG to low-frequency, high-amplitude sleep EEG dominated by spindles and slow waves. Here we identified signatures of sleep in brain hemodynamic activity, using simultaneous functional MRI (fMRI) and EEG. We found that, at the transition from wake to sleep, fMRI blood oxygen level–dependent (BOLD) activity evolved from a mixed-frequency pattern to one dominated by two distinct oscillations: a low-frequency (<0.1 Hz) oscillation prominent in light sleep and correlated with the occurrence of spindles, and a high-frequency oscillation (>0.1 Hz) prominent in deep sleep and correlated with the occurrence of slow waves. The two oscillations were both detectable across the brain but exhibited distinct spatiotemporal patterns. During the falling-asleep process, the low-frequency oscillation first appeared in the thalamus, then the posterior cortex, and lastly the frontal cortex, while the high-frequency oscillation first appeared in the midbrain, then the frontal cortex, and lastly the posterior cortex. During the waking-up process, both oscillations disappeared first from the thalamus, then the frontal cortex, and lastly the posterior cortex. The BOLD oscillations provide local signatures of spindle and slow wave activity. They may be employed to monitor the regional occurrence of sleep or wakefulness, track which regions are the first to fall asleep or wake up at the wake–sleep transitions, and investigate local homeostatic sleep processes.

Investigating sleep spindle density and schizophrenia: A meta-analysis

Sleep abnormalities are an early feature of schizophrenia (SZ) characterized by reductions in sleep spindles that are associated with deficits in brain connectivity and cognitive function. This study investigated sleep spindle density (SSD) differences between SZ, first episode psychosis (FEP), and family high-risk (FHR) populations and matched healthy controls (HC) by investigating recent studies via a meta-analysis. We collected experimental, demographic, and methodological metrics from eligible studies across multiple online databases. 14 total studies survived the inclusion and exclusion criteria for a total of 337 patients and relatives and 339 HC. R-Studio was used to run the meta-analysis via the meta and metaphor packages. A heterogeneity score of I² = 80% was calculated and thus a random effects model was chosen. We report a large effect size for SSD in patients compared to controls. Furthermore, illness duration was significantly associated with SSD. Our next step to understanding sleep spindles would be to investigate SSD's use as a predictor for SZ or attempt to normalize SSD deficits as a therapeutic option.

Thalamocortical Spectral Transmission Relies on Balanced Input Strengths

The thalamus is a key element of sensory transmission in the brain, as it gates and selects sensory streams through a modulation of its internal activity. A preponderant role in these functions is played by its internal activity in the alpha range ([8–14] Hz), but the mechanism underlying this process is not completely understood. In particular, how do thalamocortical connections convey stimulus driven information selectively over the back-ground of thalamic internally generated activity? Here we investigate this issue with a spiking network model of feedforward connectivity between thalamus and primary sensory cortex reproducing the local field potential of both areas. We found that in a feedforward network, thalamic oscillations in the alpha range do not entrain cortical activity for two reasons: (i) alpha range oscillations are weaker in neurons projecting to the cortex, (ii) the gamma resonance dynamics of cortical networks hampers oscillations over the 10–20 Hz range thus weakening alpha range oscillations. This latter mechanism depends on the balance of the strength of thalamocortical connections toward excitatory and inhibitory neurons in the cortex. Our results highlight the relevance of corticothalamic feedback to sustain alpha range oscillations and pave the way toward an integrated understanding of the sensory streams traveling between the periphery and the cortex.

The Contribution of Thalamic Nuclei in Salience Processing

The brain continuously receives diverse information about the external environment and changes in the homeostatic state. The attribution of salience determines which stimuli capture attention and, therefore, plays an essential role in regulating emotions and guiding behaviors. Although the thalamus is included in the salience network, the neural mechanism of how the thalamus contributes to salience processing remains elusive. In this mini-review, we will focus on recent advances in understanding the specific roles of distinct thalamic nuclei in salience processing. We will summarize the functional connections between thalamus nuclei and other key nodes in the salience network. We will highlight the convergence of neural circuits involved in reward and pain processing, arousal, and attention control in thalamic structures. We will discuss how thalamic activities represent salience information in associative learning and how thalamic neurons modulate adaptive behaviors. Lastly, we will review recent studies which investigate the contribution of thalamic dysfunction to aberrant salience processing in neuropsychiatric disorders, such as drug addiction, posttraumatic stress disorder (PTSD), and schizophrenia. Based on emerging evidence from both human and rodent research, we propose that the thalamus, different from previous studies that as an information relay, has a broader role in coordinating the cognitive process and regulating emotions.

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

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

Emergence of bursting in a network of memory dependent excitable and spiking leech-heart neurons

Excitable cells often produce different oscillatory activities that help us to understand the transmitting and processing of signals in the neural system. The diverse excitabilities of an individual neuron can be reproduced by a fractional-order biophysical model that preserves several previous memory effects. However, it is not completely clear to what extent the fractional-order dynamics changes the firing properties of excitable cells. In this article, we investigate the alternation of spiking and bursting phenomena of an uncoupled and coupled fractional leech-heart (L-H) neurons. We show that a complete graph of heterogeneous de-synchronized neurons in the backdrop of diverse memory settings (a mixture of integer and fractional exponents) can eventually lead to bursting with the formation of cluster synchronization over a certain threshold of coupling strength, however, the uncoupled L-H neurons cannot reveal bursting dynamics. Using the stability analysis in fractional domain, we demarcate the parameter space where the quiescent or steady-state emerges in uncoupled L-H neuron. Finally, a reduced-order model is introduced to capture the activities of the large network of fractional-order model neurons.

Augmented Reticular Thalamic Bursting and Seizures in Scn1a-Dravet Syndrome

Loss of function in the Scn1a gene leads to a severe epileptic encephalopathy called Dravet syndrome (DS). Reduced excitability in cortical inhibitory neurons is thought to be the major cause of DS seizures. Here, in contrast, we show enhanced excitability in thalamic inhibitory neurons that promotes the non-convulsive seizures that are a prominent yet poorly understood feature of DS. In a mouse model of DS with a loss of function in Scn1a, reticular thalamic cells exhibited abnormally long bursts of firing caused by the downregulation of calcium-activated potassium SK channels. Our study supports a mechanism in which loss of SK activity causes the reticular thalamic neurons to become hyperexcitable and promote non-convulsive seizures in DS. We propose that reduced excitability of inhibitory neurons is not global in DS and that non-GABAergic mechanisms such as SK channels may be important targets for treatment.

In a mouse model of Dravet syndrome (DS) resulting from voltage-gated sodium channel deficiency, Ritter-Makinson et al. find that inhibitory neurons of the reticular thalamic nucleus are paradoxically hyperexcitable due to compensatory reductions in a potassium SK current. Boosting this SK current treats nonconvulsive seizures in DS mice.

GABAB receptors: modulation of thalamocortical dynamics and synaptic plasticity

GABA_B-receptors (GABA_B-Rs) are metabotropic, G protein-coupled receptors for the neurotransmitter GABA. Their activation induces slow inhibitory control of the neuronal excitability mediated by pre- and postsynaptic inhibition. Presynaptically GABA_B-Rs reduce GABA and glutamate release inhibiting presynaptic Ca²⁺ channels in both inhibitory and excitatory synapses while postsynaptic GABA_B-Rs induce robust slow hyperpolarization by the activation of K⁺ channels. GABA_B-Rs are activated by non-synaptic or volume transmission, which requires high levels of GABA release, either by the simultaneous discharge of GABAergic interneurons or very intense discharges in the thalamus or by means of the activation of a neurogliaform interneurons in the cortex. The main receptor subunits GABA_B1a, GABA_B1b and GABA_B2 are strongly expressed in neurons and glial cells throughout the central nervous system and GABA_B-R activation is related to many neuronal processes such as the modulation of rhythmic activity in several brain regions. In the thalamus, GABA_B-Rs modulate the generation of the main thalamic rhythm, spindle waves. In the cerebral cortex, GABA_B-Rs also modulate the most prominent emergent oscillatory activity-slow oscillations-as well as faster oscillations like gamma frequency. Further, recent studies evaluating the complexity expressed by the cortical network, a parameter associated with consciousness levels, have found that GABA_B-Rs enhance this complexity, while their blockade decreases it. This review summarizes the current results on how the activation of GABA_B-Rs affects the interchange of information between brain areas by controlling rhythmicity as well as synaptic plasticity.

Simulating human sleep spindle MEG and EEG from ion channel and circuit level dynamics

BACKGROUND

Although they form a unitary phenomenon, the relationship between extracranial M/EEG and transmembrane ion flows is understood only as a general principle rather than as a well-articulated and quantified causal chain.

METHOD

We present an integrated multiscale model, consisting of a neural simulation of thalamus and cortex during stage N2 sleep and a biophysical model projecting cortical current densities to M/EEG fields. Sleep spindles were generated through the interactions of local and distant network connections and intrinsic currents within thalamocortical circuits. 32,652 cortical neurons were mapped onto the cortical surface reconstructed from subjects' MRI, interconnected based on geodesic distances, and scaled-up to current dipole densities based on laminar recordings in humans. MRIs were used to generate a quasi-static electromagnetic model enabling simulated cortical activity to be projected to the M/EEG sensors.

RESULTS

The simulated M/EEG spindles were similar in amplitude and topography to empirical examples in the same subjects. Simulated spindles with more core-dominant activity were more MEG weighted.

COMPARISON WITH EXISTING METHODS

Previous models lacked either spindle-generating thalamic neural dynamics or whole head biophysical modeling; the framework presented here is the first to simultaneously capture these disparate scales.

CONCLUSIONS

This multiscale model provides a platform for the principled quantitative integration of existing information relevant to the generation of sleep spindles, and allows the implications of future findings to be explored. It provides a proof of principle for a methodological framework allowing large-scale integrative brain oscillations to be understood in terms of their underlying channels and synapses.

Circadian rhythm and epilepsy

Advances in diagnostic technology, including chronic intracranial EEG recordings, have confirmed the clinical observation of different temporal patterns of epileptic activity and seizure occurrence over a 24-h period. The rhythmic patterns in epileptic activity and seizure occurrence are probably related to vigilance states and circadian variation in excitatory and inhibitory balance. Core circadian genes BMAL1 and CLOCK, which code for transcription factors, have been shown to influence excitability and seizure threshold. Despite uncertainties about the relative contribution of vigilance states versus circadian rhythmicity, including circadian factors such as seizure timing improves sensitivity of seizure prediction algorithms in individual patients. Improved prediction of seizure occurrence opens the possibility for personalised antiepileptic drug-dosing regimens timed to particular phases of the circadian cycle to improve seizure control and to reduce side-effects and risks associated with seizures. Further studies are needed to clarify the pathways through which rhythmic patterns of epileptic activity are generated, because this might also inform future treatment options.

Thalamocortical and intracortical laminar connectivity determines sleep spindle properties

Sleep spindles are brief oscillatory events during non-rapid eye movement (NREM) sleep. Spindle density and synchronization properties are different in MEG versus EEG recordings in humans and also vary with learning performance, suggesting spindle involvement in memory consolidation. Here, using computational models, we identified network mechanisms that may explain differences in spindle properties across cortical structures. First, we report that differences in spindle occurrence between MEG and EEG data may arise from the contrasting properties of the core and matrix thalamocortical systems. The matrix system, projecting superficially, has wider thalamocortical fanout compared to the core system, which projects to middle layers, and requires the recruitment of a larger population of neurons to initiate a spindle. This property was sufficient to explain lower spindle density and higher spatial synchrony of spindles in the superficial cortical layers, as observed in the EEG signal. In contrast, spindles in the core system occurred more frequently but less synchronously, as observed in the MEG recordings. Furthermore, consistent with human recordings, in the model, spindles occurred independently in the core system but the matrix system spindles commonly co-occurred with core spindles. We also found that the intracortical excitatory connections from layer III/IV to layer V promote spindle propagation from the core to the matrix system, leading to widespread spindle activity. Our study predicts that plasticity of intra- and inter-cortical connectivity can potentially be a mechanism for increased spindle density as has been observed during learning.

Distinct Thalamic Reticular Cell Types Differentially Modulate Normal and Pathological Cortical Rhythms

Integrative brain functions depend on widely distributed, rhythmically coordinated computations. Through its long-ranging connections with cortex and most senses, the thalamus orchestrates the flow of cognitive and sensory information. Essential in this process, the nucleus reticularis thalami (nRT) gates different information streams through its extensive inhibition onto other thalamic nuclei, however, we lack an understanding of how different inhibitory neuron subpopulations in nRT function as gatekeepers. We dissociated the connectivity, physiology, and circuit functions of neurons within rodent nRT, based on parvalbumin (PV) and somatostatin (SOM) expression, and validated the existence of such populations in human nRT. We found that PV, but not SOM, cells are rhythmogenic, and that PV and SOM neurons are connected to and modulate distinct thalamocortical circuits. Notably, PV, but not SOM, neurons modulate somatosensory behavior and disrupt seizures. These results provide a conceptual framework for how nRT may gate incoming information to modulate brain-wide rhythms.

Reduced sleep spindle activity point to a TRN-MD thalamus-PFC circuit dysfunction in schizophrenia

Sleep disturbances have been reliably reported in patients with schizophrenia, thus suggesting that abnormal sleep may represent a core feature of this disorder. Traditional electroencephalographic studies investigating sleep architecture have found reduced deep non-rapid eye movement (NREM) sleep, or slow wave sleep (SWS), and increased REM density. However, these findings have been inconsistently observed, and have not survived meta-analysis. By contrast, several recent EEG studies exploring brain activity during sleep have established marked deficits in sleep spindles in schizophrenia, including first-episode and early-onset patients, compared to both healthy and psychiatric comparison subjects. Spindles are waxing and waning, 12-16Hz NREM sleep oscillations that are generated within the thalamus by the thalamic reticular nucleus (TRN), and are then synchronized and sustained in the cortex. While the functional role of sleep spindles still needs to be fully established, increasing evidence has shown that sleep spindles are implicated in learning and memory, including sleep dependent memory consolidation, and spindle parameters have been associated to general cognitive ability and IQ. In this article we will review the EEG studies demonstrating sleep spindle deficits in patients with schizophrenia, and show that spindle deficits can predict their reduced cognitive performance. We will then present data indicating that spindle impairments point to a TRN-MD thalamus-prefrontal cortex circuit deficit, and discuss about the possible molecular mechanisms underlying thalamo-cortical sleep spindle abnormalities in schizophrenia.

Cellular and neurochemical basis of sleep stages in the thalamocortical network

The link between the combined action of neuromodulators in the brain and global brain states remains a mystery. In this study, using biophysically realistic models of the thalamocortical network, we identified the critical intrinsic and synaptic mechanisms, associated with the putative action of acetylcholine (ACh), GABA and monoamines, which lead to transitions between primary brain vigilance states (waking, non-rapid eye movement sleep [NREM] and REM sleep) within an ultradian cycle. Using ECoG recordings from humans and LFP recordings from cats and mice, we found that during NREM sleep the power of spindle and delta oscillations is negatively correlated in humans and positively correlated in animal recordings. We explained this discrepancy by the differences in the relative level of ACh. Overall, our study revealed the critical intrinsic and synaptic mechanisms through which different neuromodulators acting in combination result in characteristic brain EEG rhythms and transitions between sleep stages.

Sleep spindles: a physiological marker of age-related changes in gray matter in brain regions supporting motor skill memory consolidation

Sleep is necessary for the optimal consolidation of procedural learning, and in particular, for motor sequential skills. Motor sequence learning remains intact with age, but sleep-dependent consolidation is impaired, suggesting that memory deficits for procedural skills are specifically impacted by age-related changes in sleep. Age-related changes in spindles may be responsible for impaired motor sequence learning consolidation, but the morphological basis for this deficit is unknown. Here, we found that gray matter in the hippocampus and cerebellum was positively correlated with both sleep spindles and offline improvements in performance in young participants but not in older participants. These results suggest that age-related changes in gray matter in the hippocampus relate to spindles and may underlie age-related deficits in sleep-related motor sequence memory consolidation. In this way, spindles can serve as a biological marker for structural brain changes and the related memory deficits in older adults.

Coupling of Thalamocortical Sleep Oscillations Are Important for Memory Consolidation in Humans

Sleep, specifically non-rapid eye movement (NREM) sleep, is thought to play a critical role in the consolidation of recent memories. Two main oscillatory activities observed during NREM, cortical slow oscillations (SO, 0.5–1.0Hz) and thalamic spindles (12–15Hz), have been shown to independently correlate with memory improvement. Yet, it is not known how these thalamocortical events interact, or the significance of this interaction, during the consolidation process. Here, we found that systemic administration of the GABAergic drug (zolpidem) increased both the phase-amplitude coupling between SO and spindles, and verbal memory improvement in humans. These results suggest that thalamic spindles that occur during transitions to the cortical SO Up state are optimal for memory consolidation. Our study predicts that the timely interactions between cortical and thalamic events during consolidation, contribute to memory improvement and is mediated by the level of inhibitory neurotransmission.

Thalamic reticular nucleus induces fast and local modulation of arousal state

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

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

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

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

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

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

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

Sleep spindles are related to schizotypal personality traits and thalamic glutamine/glutamate in healthy subjects

BACKGROUND

Schizophrenia is a severe mental disorder affecting approximately 1% of the worldwide population. Yet, schizophrenia-like experiences (schizotypy) are very common in the healthy population, indicating a continuum between normal mental functioning and the psychosis found in schizophrenic patients. A continuum between schizotypy and schizophrenia would be supported if they share the same neurobiological origin. Two such neurobiological markers of schizophrenia are: (1) a reduction of sleep spindles (12-15 Hz oscillations during nonrapid eye movement sleep), likely reflecting deficits in thalamo-cortical circuits and (2) increased glutamine and glutamate (Glx) levels in the thalamus. Thus, this study aimed to investigate whether sleep spindles and Glx levels are related to schizotypal personality traits in healthy subjects.

METHODS

Twenty young male subjects underwent 2 all-night sleep electroencephalography recordings (128 electrodes). Sleep spindles were detected automatically. After those 2 nights, thalamic Glx levels were measured by magnetic resonance spectroscopy. Subjects completed a magical ideation scale to assess schizotypy.

RESULTS

Sleep spindle density was negatively correlated with magical ideation (r = -.64, P < .01) and thalamic Glx levels (r = -.70, P < .005). No correlation was found between Glx levels in the thalamus and magical ideation (r = .12, P > .1).

CONCLUSIONS

The common relationship of sleep spindle density with schizotypy and thalamic Glx levels indicates a neurobiological overlap between nonclinical schizotypy and schizophrenia. Thus, sleep spindle density and magical ideation may reflect the anatomy and efficiency of the thalamo-cortical system that shows pronounced impairment in patients with schizophrenia.

State-dependent architecture of thalamic reticular subnetworks

Behavioral state is known to influence interactions between thalamus and cortex, which are important for sensation, action, and cognition. The thalamic reticular nucleus (TRN) is hypothesized to regulate thalamo-cortical interactions, but the underlying functional architecture of this process and its state dependence are unknown. By combining the first TRN ensemble recording with psychophysics and connectivity-based optogenetic tagging, we found reticular circuits to be composed of distinct subnetworks. While activity of limbic-projecting TRN neurons positively correlates with arousal, sensory-projecting neurons participate in spindles and show elevated synchrony by slow waves during sleep. Sensory-projecting neurons are suppressed by attentional states, demonstrating that their gating of thalamo-cortical interactions is matched to behavioral state. Bidirectional manipulation of attentional performance was achieved through subnetwork-specific optogenetic stimulation. Together, our findings provide evidence for differential inhibition of thalamic nuclei across brain states, where the TRN separately controls external sensory and internal limbic processing facilitating normal cognitive function. PAPERFLICK:

Synchronization of isolated downstates (K-complexes) may be caused by cortically-induced disruption of thalamic spindling

Sleep spindles and K-complexes (KCs) define stage 2 NREM sleep (N2) in humans. We recently showed that KCs are isolated downstates characterized by widespread cortical silence. We demonstrate here that KCs can be quasi-synchronous across scalp EEG and across much of the cortex using electrocorticography (ECOG) and localized transcortical recordings (bipolar SEEG). We examine the mechanism of synchronous KC production by creating the first conductance based thalamocortical network model of N2 sleep to generate both spontaneous spindles and KCs. Spontaneous KCs are only observed when the model includes diffuse projections from restricted prefrontal areas to the thalamic reticular nucleus (RE), consistent with recent anatomical findings in rhesus monkeys. Modeled KCs begin with a spontaneous focal depolarization of the prefrontal neurons, followed by depolarization of the RE. Surprisingly, the RE depolarization leads to decreased firing due to disrupted spindling, which in turn is due to depolarization-induced inactivation of the low-threshold Ca²⁺ current (I_T). Further, although the RE inhibits thalamocortical (TC) neurons, decreased RE firing causes decreased TC cell firing, again because of disrupted spindling. The resulting abrupt removal of excitatory input to cortical pyramidal neurons then leads to the downstate. Empirically, KCs may also be evoked by sensory stimuli while maintaining sleep. We reproduce this phenomenon in the model by depolarization of either the RE or the widely-projecting prefrontal neurons. Again, disruption of thalamic spindling plays a key role. Higher levels of RE stimulation also cause downstates, but by directly inhibiting the TC neurons. SEEG recordings from the thalamus and cortex in a single patient demonstrated the model prediction that thalamic spindling significantly decreases before KC onset. In conclusion, we show empirically that KCs can be widespread quasi-synchronous cortical downstates, and demonstrate with the first model of stage 2 NREM sleep a possible mechanism whereby this widespread synchrony may arise.

EEG in the most common stage of human sleep is dominated by K-complexes (KCs) and sleep spindles (bursts of 10–14 Hz oscillations) occupying the thalamus and cortex. Recently, we discovered that KCs are brief moments when the cortex becomes almost completely silent. Here, using recordings directly from the cortex of epileptic patients, we show that KCs can be quasi-synchronous across widespread cortical areas, and ask what mechanism could produce such a phenomenon. We created the first network model of realistic cortical and thalamic neurons, which spontaneously generate KCs as well as sleep spindles. We showed that the membrane channels in the reticular nucleus of the thalamus can be inactivated by excitatory inputs from the cortex, and this disrupts the spindle-generating network, which can trigger widespread cortical silence. The model prediction that thalamic spindle disruption occurs prior to KC was then observed in simultaneous recordings from the human thalamus and cortex. Understanding the cellular and network mechanisms whereby KCs arise is crucial to understanding its roles in maintaining sleep and consolidating memories.

Efavirenz modulation of sleep spindles and sleep spectral profile

Non-nucleoside reverse transcriptase inhibitors are important antiretroviral agents for the treatment of human immunodeficiency virus. Some non-nucleoside reverse transcriptase inhibitors, in particular efavirenz, have prominent effects on sleep, cognition and psychiatric variables that limit their tolerability. To avoid confounds due to drug-drug and drug-disease interactions, we assessed the effects of efavirenz in healthy volunteers on sleep, cognition and psychological endpoints during the first week of treatment. Forty healthy male subjects were randomized to receive placebo or efavirenz 600 mg nightly for 7 days after completion of a 3-day placebo run-in period. Treatment with efavirenz was associated with reduced time to sleep onset in the Maintenance of Wakefulness Test, an increase in non-rapid eye movement sleep, a large exposure-related decrease in sigma band spectral density and sleep spindle density during non-rapid eye movement sleep, and reduced performance on an attention switching task. Because efavirenz has been shown to have serotonin 2A receptor partial-agonist properties, we reasoned that antagonism of serotonin 2A receptor signalling in the thalamic reticular nucleus, which generates sleep spindles and promotes attention, may be responsible. Consistent with predictions, treatment of healthy volunteers with a single dose of a serotonin 2A receptor antagonist was found to significantly suppress sigma band spectral density in an exposure-related manner and modulated the overall spectral profile in a manner highly similar to that observed with efavirenz, consistent with the notion that efavirenz exhibits serotonin 2A receptor partial-agonist pharmacology in humans.

Deterministic and stochastic bifurcations in the Hindmarsh-Rose neuronal model

We analyze the bifurcations occurring in the 3D Hindmarsh-Rose neuronal model with and without random signal. When under a sufficient stimulus, the neuron activity takes place; we observe various types of bifurcations that lead to chaotic transitions. Beside the equilibrium solutions and their stability, we also investigate the deterministic bifurcation. It appears that the neuronal activity consists of chaotic transitions between two periodic phases called bursting and spiking solutions. The stochastic bifurcation, defined as a sudden change in character of a stochastic attractor when the bifurcation parameter of the system passes through a critical value, or under certain condition as the collision of a stochastic attractor with a stochastic saddle, occurs when a random Gaussian signal is added. Our study reveals two kinds of stochastic bifurcation: the phenomenological bifurcation (P-bifurcations) and the dynamical bifurcation (D-bifurcations). The asymptotical method is used to analyze phenomenological bifurcation. We find that the neuronal activity of spiking and bursting chaos remains for finite values of the noise intensity.

Sustaining sleep spindles through enhanced SK2-channel activity consolidates sleep and elevates arousal threshold

Sleep spindles are synchronized 11-15 Hz electroencephalographic (EEG) oscillations predominant during nonrapid-eye-movement sleep (NREMS). Rhythmic bursting in the reticular thalamic nucleus (nRt), arising from interplay between Ca(v)3.3-type Ca(2+) channels and Ca(2+)-dependent small-conductance-type 2 (SK2) K(+) channels, underlies spindle generation. Correlative evidence indicates that spindles contribute to memory consolidation and protection against environmental noise in human NREMS. Here, we describe a molecular mechanism through which spindle power is selectively extended and we probed the actions of intensified spindling in the naturally sleeping mouse. Using electrophysiological recordings in acute brain slices from SK2 channel-overexpressing (SK2-OE) mice, we found that nRt bursting was potentiated and thalamic circuit oscillations were prolonged. Moreover, nRt cells showed greater resilience to transit from burst to tonic discharge in response to gradual depolarization, mimicking transitions out of NREMS. Compared with wild-type littermates, chronic EEG recordings of SK2-OE mice contained less fragmented NREMS, while the NREMS EEG power spectrum was conserved. Furthermore, EEG spindle activity was prolonged at NREMS exit. Finally, when exposed to white noise, SK2-OE mice needed stronger stimuli to arouse. Increased nRt bursting thus strengthens spindles and improves sleep quality through mechanisms independent of EEG slow waves (<4 Hz), suggesting SK2 signaling as a new potential therapeutic target for sleep disorders and for neuropsychiatric diseases accompanied by weakened sleep spindles.

Astrocyte regulation of sleep circuits: experimental and modeling perspectives

Integrated within neural circuits, astrocytes have recently been shown to modulate brain rhythms thought to mediate sleep function. Experimental evidence suggests that local impact of astrocytes on single synapses translates into global modulation of neuronal networks and behavior. We discuss these findings in the context of current conceptual models of sleep generation and function, each of which have historically focused on neural mechanisms. We highlight the implications and the challenges introduced by these results from a conceptual and computational perspective. We further provide modeling directions on how these data might extend our knowledge of astrocytic properties and sleep function. Given our evolving understanding of how local cellular activities during sleep lead to functional outcomes for the brain, further mechanistic and theoretical understanding of astrocytic contribution to these dynamics will undoubtedly be of great basic and translational benefit.

Interactions between core and matrix thalamocortical projections in human sleep spindle synchronization

Sleep spindles are bursts of 11-15 Hz that occur during non-rapid eye movement sleep. Spindles are highly synchronous across the scalp in the electroencephalogram (EEG) but have low spatial coherence and exhibit low correlation with the EEG when simultaneously measured in the magnetoencephalogram (MEG). We developed a computational model to explore the hypothesis that the spatial coherence spindles in the EEG is a consequence of diffuse matrix projections of the thalamus to layer 1 compared with the focal projections of the core pathway to layer 4 recorded in the MEG. Increasing the fanout of thalamocortical connectivity in the matrix pathway while keeping the core pathway fixed led to increased synchrony of the spindle activity in the superficial cortical layers in the model. In agreement with cortical recordings, the latency for spindles to spread from the core to the matrix was independent of the thalamocortical fanout but highly dependent on the probability of connections between cortical areas.

Schizophrenia as a disturbance of cortical sensory maps

Schizophrenia is a disorder characterized by a variety of symptoms, which among others include hallucinations, delusions and passivity experiences. It has been found that individuals with schizophrenia misattribute their own thoughts and actions to an outside agency (source monitoring deficits), which could account for psychotic experiences such as that of hearing voices. In order to explain the source-monitoring deficits as well as psychosis, it has been proposed that mechanisms that enable anticipation and recognition of sensory consequences of one’s own actions are impaired in schizophrenia. Importantly, such mechanisms may require accurate cortical sensory representations such as in the primary somatosensory cortex (S1). The establishment and maintenance of cortical sensory representations has been found to utilize a sleep-related brain rhythm known as spindling. Namely, in the perinatal period in humans and animals, and possibly also thereafter, spontaneous activity in the sensory periphery drives spindle activity in the developing cortical sensory areas, which then contributes to the formation of sensory representations that match bodily features. For example, muscle twitch-spindle sequences during sleep facilitate the formation and maintenance of S1 in accordance with the layout of musculature. This process has been proposed to continue throughout the lifespan and may be particularly important during periods of bodily changes (adolescence, menopause). In schizophrenia, the amount of sleep spindle activity is markedly reduced, which would be expected to result in insufficient cortical sensory representations and have relevance for the relative inability of individuals with schizophrenia to accurately recognize self-initiated actions.

Similarities between cortical “up” states during slow wave sleep and wakefulness: the implications for schizophrenia

Negative and positive symptoms are defining features of schizophrenia. This illness is commonly associated with a number of cognitive and affective deficits as well as with some more specific sleep abnormalities. It has been previously proposed that psychosis and positive symptoms in schizophrenia could be understood as disorders of internal brain dynamics. This proposed disordered network interplay might be particularly displayed during sleep when modulation by the senses is at the minimum. It is argued here that sleep abnormalities in schizophrenia inform our understanding of the pathomechanisms involved in psychosis. More specifically, sleep spindle initiation in NREM sleep and the preparation of sensory pathways for upcoming motor actions during wakefulness may share a common mechanism, and this shared mechanism is suggested to be impaired in schizophrenia.

Abnormalities in thalamic neurophysiology in schizophrenia: could psychosis be a result of potassium channel dysfunction?

Psychosis in schizophrenia is associated with source-monitoring deficits whereby self-initiated behaviors become attributed to outside sources. One of the proposed functions of the thalamus is to adjust sensory responsiveness in accordance with the behavioral contextual cues. The thalamus is markedly affected in schizophrenia, and thalamic dysfunction may here result in reduced ability to adjust sensory responsiveness to ongoing behavior. One of the ways in which the thalamus accomplishes the adjustment of sensory processing is by a neurophysiological shift to post-inhibitory burst firing mode prior to and during certain exploratory actions. Reduced amount of thalamic burst firing may result from increased neuronal excitability secondary to a reported potassium channel dysfunction in schizophrenia. Pharmacological agents that reduce the excitability of thalamic cells and thereby promote burst firing by and large tend to have antipsychotic effects.

Corticothalamic feedback controls sleep spindle duration in vivo

Spindle oscillations are commonly observed during stage 2 of non-rapid eye movement sleep. During sleep spindles, the cerebral cortex and thalamus interact through feedback connections. Both initiation and termination of spindle oscillations are thought to originate in the thalamus based on thalamic recordings and computational models, although some in vivo results suggest otherwise. Here, we have used computer modeling and in vivo multisite recordings from the cortex and the thalamus in cats to examine the involvement of the cortex in spindle oscillations. We found that although the propagation of spindles depended on synaptic interaction within the thalamus, the initiation and termination of spindle sequences critically involved corticothalamic influences.

The thalamic reticular nucleus and schizophrenia

BACKGROUND

The thalamic reticular nucleus (TRN) is a shell-shaped gamma amino butyric acid (GABA)ergic nucleus, which is uniquely placed between the thalamus and the cortex, because it receives excitatory afferents from both cortical and thalamic neurons and sends inhibitory projections to all nuclei of the dorsal thalamus.

METHOD

A review of the evidence suggesting that the TRN is implicated in the neurobiology of schizophrenia.

RESULTS

TRN-thalamus circuits are implicated in bottom-up as well as top-down processing. TRN projections to nonspecific nuclei of the dorsal thalamus mediate top-down processes, including attentional modulation, which are initiated by cortical afferents to the TRN. TRN-thalamus circuits are also involved in bottom-up activities, including sensory gating and the transfer to the cortex of sleep spindles. Intriguingly, deficits in attention and sensory gating have been consistently found in schizophrenics, including first-break and chronic patients. Furthermore, high-density electroencephalographic studies have revealed a marked reduction in sleep spindles in schizophrenics.

CONCLUSION

On the basis of our current knowledge on the molecular and anatomo-functional properties of the TRN, we suggest that this thalamic GABAergic nucleus may be involved in the neurobiology of schizophrenia.

The function of the sleep spindle: a physiological index of intelligence and a mechanism for sleep-dependent memory consolidation

Until recently, the electrophysiological mechanisms involved in strengthening new memories into a more permanent form during sleep have been largely unknown. The sleep spindle is an event in the electroencephalogram (EEG) characterizing Stage 2 sleep. Sleep spindles may reflect, at the electrophysiological level, an ideal mechanism for inducing long-term synaptic changes in the neocortex. Recent evidence suggests the spindle is highly correlated with tests of intellectual ability (e.g.; IQ tests) and may serve as a physiological index of intelligence. Further, spindles increase in number and duration in sleep following new learning and are correlated with performance improvements. Spindle density and sigma (14-16Hz) spectral power have been found to be positively correlated with performance following a daytime nap, and animal studies suggest the spindle is involved in a hippocampal-neocortical dialogue necessary for memory consolidation. The findings reviewed here collectively provide a compelling body of evidence that the function of the sleep spindle is related to intellectual ability and memory consolidation.

Reduced sleep spindle activity in early-onset and elevated risk for depression

OBJECTIVE

Sleep disturbances are common in major depressive disorder (MDD), although polysomnographic (PSG) abnormalities are more prevalent in adults than in children and adolescents with MDD. Sleep spindle activity (SPA) is associated with neuroplasticity mechanisms during brain maturation and is more abundant in childhood and adolescence than in adulthood, and as such, may be a more sensitive measure of sleep alteration than PSG in early-onset depression. This study investigated SPA changes related to early-onset MDD, comparing individuals already ill with MDD and individuals at high-risk for MDD with healthy nondepressed controls.

METHOD

The study included 63 participants (8 to 15 years of age): 21 currently depressed individuals, 21 individuals at high risk for MDD based on positive family history of MDD, and 21 healthy control individuals with no personal or family history of psychiatric illness. All participants maintained a regular sleep/wake schedule for 5 days, followed by 2 nights in the laboratory. SPA was analyzed in Stage 2 of non-rapid eye movement sleep.

RESULTS

SPA differed significantly between groups, particularly in the late part of the night (F(2,62) = 7.3, p = .001). Although the difference was greatest between the MDD and healthy control groups, both the MDD (p = .0004) and at high-risk groups (p = .02) had significantly lower SPA compared with healthy controls. SPA deficit was more prominent in females than in males (F(5,62) = 5.19, p = .005).

CONCLUSIONS

Low SPA characterizes youths with MDD and those at high risk for MDD, particularly girls, suggesting that early-onset depression and risk for the MDD are associated with decreased neuroplasticity.

Enhanced synchronization of thalamic theta band local field potentials in patients with essential tremor

Local field potentials (LFPs) were recorded in 13 patients from pairs of microelectrodes driven through thalamus during functional localization prior to implantation of a thalamic deep brain stimulation electrode for treatment of tremor or pain. Six patients had a history of essential tremor (ET), 3 of multiple sclerosis, and the remaining 4 had symptoms of chronic pain. Specific to the ET group was the observation that oscillatory field potentials recorded from the two microelectrodes in the motor thalamus (ventralis intermedius--Vim, ventralis oralis posterior--Vop) were highly coherent at frequencies characteristic of pathological tremor (4-7 Hz). This stands in contrast to the significantly more desynchronized state observed in the somatosensory thalamus (ventralis caudalis--Vc) for that frequency band. In addition, higher frequency coherent oscillations typically associated with physiological tremor (8-12 Hz) were observed in the ET patients in motor thalamus and Vc and in motor thalamus of pain patients. An examination of the inter-frequency correlation of the LFPs in Vim and Vop showed that the low frequency theta waves correlated with high frequency oscillations in the beta and gamma ranges. These findings are consistent with and extend those of other studies suggesting that alterations in thalamic oscillatory activity are involved in the pathophysiology of ET and furthermore suggest that increased synchronization in the 4-7 Hz range is related to the occurrence of tremor in the ET patient group. Furthermore, they support the idea that therapies such as lesions and high frequency stimulation of the motor thalamus are effective in reducing tremor symptoms since they destroy the abnormal low frequency synchronization in motor thalamus.

A network model for activity-dependent sleep regulation

We develop and characterize a dynamical network model for activity-dependent sleep regulation. Specifically, in accordance with the activity-dependent theory for sleep, we view organism sleep as emerging from the local sleep states of functional units known as cortical columns; these local sleep states evolve through integration of local activity inputs, loose couplings with neighboring cortical columns, and global regulation (e.g. by the circadian clock). We model these cortical columns as coupled or networked activity-integrators that transition between sleep and waking states based on thresholds on the total activity. The model dynamics for three canonical experiments (which we have studied both through simulation and system-theoretic analysis) match with experimentally observed characteristics of the cortical-column network. Most notably, assuming connectedness of the network graph, our model predicts the recovery of the columns to a synchronized state upon temporary overstimulation of a single column and/or randomization of the initial sleep and activity-integration states. In analogy with other models for networked oscillators, our model also predicts the possibility for such phenomena as mode-locking.

Oscillations and synchrony in large-scale cortical network models

Intrinsic neuronal and circuit properties control the responses of large ensembles of neurons by creating spatiotemporal patterns of activity that are used for sensory processing, memory formation, and other cognitive tasks. The modeling of such systems requires computationally efficient single-neuron models capable of displaying realistic response properties. We developed a set of reduced models based on difference equations (map-based models) to simulate the intrinsic dynamics of biological neurons. These phenomenological models were designed to capture the main response properties of specific types of neurons while ensuring realistic model behavior across a sufficient dynamic range of inputs. This approach allows for fast simulations and efficient parameter space analysis of networks containing hundreds of thousands of neurons of different types using a conventional workstation. Drawing on results obtained using large-scale networks of map-based neurons, we discuss spatiotemporal cortical network dynamics as a function of parameters that affect synaptic interactions and intrinsic states of the neurons.

Influence of norepinephrine on somatosensory neuronal responses in the rat thalamus: a combined modeling and in vivo multi-channel, multi-neuron recording study

Norepinephrine released within primary sensory circuits from locus coeruleus afferent fibers can produce a spectrum of modulatory actions on spontaneous or sensory-evoked activity of individual neurons. Within the ventral posterior medial thalamus, membrane currents modulated by norepinephrine have been identified. However, the relationship between the cellular effects of norepinephrine and the impact of norepinephrine release on populations of neurons encoding sensory signals is still open to question. To address this lacuna in understanding the net impact of the noradrenergic system on sensory signal processing, a computational model of the rat trigeminal somatosensory thalamus was generated. The effects of independent manipulation of different cellular actions of norepinephrine on simulated afferent input to the computational model were then examined. The results of these simulations aided in the design of in vivo neural ensemble recording experiments where sensory-driven responses of thalamic neurons were measured before and during locus coeruleus activation in waking animals. Together the simulated and experimental results reveal several key insights regarding the regulation of neural network operation by norepinephrine including: 1) cell-specific modulatory actions of norepinephrine, 2) mechanisms of norepinephrine action that can improve the tuning of the network and increase the signal-to-noise ratio of cellular responses in order to enhance network representation of salient stimulus features and 3) identification of the dynamic range of thalamic neuron function through which norepinephrine operates.

A population-based model of the nonlinear dynamics of the thalamocortical feedback network displays intrinsic oscillations in the spindling (7-14 Hz) range

The thalamocortical network is modelled using the Wilson-Cowan equations for neuronal population activity. We show that this population model with biologically derived parameters possesses intrinsic nonlinear oscillatory dynamics, and that the frequency of oscillation lies within the spindle range. Spindle oscillations are an early sleep oscillation characterized by high-frequency bursts of action potentials followed by a period of quiescence, at a frequency of 7-14 Hz. Spindles are generally regarded as being generated by intrathalamic circuitry, as decorticated thalamic slices and the isolated thalamic reticular nucleus exhibit spindles. However, the role of cortical feedback has been shown to regulate and synchronize the oscillation. Previous modelling studies have mainly used conductance-based models and hence the mechanism relied upon the inclusion of ionic currents, particularly the T-type calcium current. Here we demonstrate that spindle-frequency oscillatory activity can also arise from the nonlinear dynamics of the thalamocortical circuit, and we use bifurcation analysis to examine the robustness of this oscillation in terms of the functional range of the parameters used in the model. The results suggest that the thalamocortical circuit has intrinsic nonlinear population dynamics which are capable of providing robust support for oscillatory activity within the frequency range of spindle oscillations.

Coexistence of tonic spiking oscillations in a leech neuron model

The leech neuron model studied here has a remarkable dynamical plasticity. It exhibits a wide range of activities including various types of tonic spiking and bursting. In this study we apply methods of the qualitative theory of dynamical systems and the bifurcation theory to analyze the dynamics of the leech neuron model with emphasis on tonic spiking regimes. We show that the model can demonstrate bi-stability, such that two modes of tonic spiking coexist. Under a certain parameter regime, both tonic spiking modes are represented by the periodic attractors. As a bifurcation parameter is varied, one of the attractors becomes chaotic through a cascade of period-doubling bifurcations, while the other remains periodic. Thus, the system can demonstrate co-existence of a periodic tonic spiking with either periodic or chaotic tonic spiking. Pontryagin's averaging technique is used to locate the periodic orbits in the phase space.

A FRAMEWORK FOR INVESTIGATING THALAMOCORTICAL ACTIVITY IN MULTISTAGE INFORMATION PROCESSING

A framework for investigating information processing in cortico-thalamocortical (cortico-TC) networks is presented, that in part can be used to model and interpret individual changes in electroencephalographic spectra and event-related potentials such as those from the Brain Resource International Database. Scientific work covering neurophysiology, TC firing modes, and TC models are explored in the framework to explain how the brain might process complex information in a multistage process. It is proposed that the thalamus and the cortico-TC system have unique ionic properties and transmission delays (in humans), which are suited to the function of taking "snapshots" or samples of complex environmental stimuli, rather than continuous data streams. This leads to careful and sequential coordination of stimulus and response processes, and increases the probability of information transfer and the resulting information complexity in higher cortical regions. Given the scope of this framework, the multidimensional and standardized Brain Resource International Database provides a pertinent set of measures for both testing hypotheses generated from the model, and for fitting the model to experimental data to investigate mechanisms underlying information processing.

Modeling Sleep and Wakefulness in the Thalamocortical System

When the brain goes from wakefulness to sleep, cortical neurons begin to undergo slow oscillations in their membrane potential that are synchronized by thalamocortical circuits and reflected in EEG slow waves. To provide a self-consistent account of the transition from wakefulness to sleep and of the generation of sleep slow waves, we have constructed a large-scale computer model that encompasses portions of two visual areas and associated thalamic and reticular thalamic nuclei. Thousands of model neurons, incorporating several intrinsic currents, are interconnected with millions of thalamocortical, corticothalamic, and both intra- and interareal corticocortical connections. In the waking mode, the model exhibits irregular spontaneous firing and selective responses to visual stimuli. In the sleep mode, neuromodulatory changes lead to slow oscillations that closely resemble those observed in vivo and in vitro. A systematic exploration of the effects of intrinsic currents and network parameters on the initiation, maintenance, and termination of slow oscillations shows the following. 1) An increase in potassium leak conductances is sufficient to trigger the transition from wakefulness to sleep. 2) The activation of persistent sodium currents is sufficient to initiate the up-state of the slow oscillation. 3) A combination of intrinsic and synaptic currents is sufficient to maintain the up-state. 4) Depolarization-activated potassium currents and synaptic depression terminate the up-state. 5) Corticocortical connections synchronize the slow oscillation. The model is the first to integrate intrinsic neuronal properties with detailed thalamocortical anatomy and reproduce neural activity patterns in both wakefulness and sleep, thereby providing a powerful tool to investigate the role of sleep in information transmission and plasticity.

Membrane bistability in thalamic reticular neurons during spindle oscillations

The thalamic reticular (RE) nucleus is a major source of inhibition in the thalamus. It plays a crucial role in regulating the excitability of thalamocortical networks and in generating some sleep rhythms. Current-clamp intracellular recordings of RE neurons in cats under barbiturate anesthesia revealed the presence of membrane bistability in approximately 20% of neurons. Bistability consisted of two alternate membrane potentials, separated by approximately 17-20 mV. While non-bistable (common) RE neurons fired rhythmic spike-bursts during spindles, bistable RE neurons fired tonically, with burst modulation, throughout spindle sequences. Bistability was strongly voltage dependent and only expressed under resting conditions (i.e. no current injection). The transition from the silent to the active state was a regenerative event that could be activated by brief depolarization, whereas brief hyperpolarizations could switch the membrane potential from the active to the silent state. These effects outlasted the current pulses. Corticothalamic stimulation could also switch the membrane potential from silent to active states. Addition of QX-314 in the recording micropipette either abolished or disrupted membrane bistability, suggesting I(Na(p)) to be responsible for its generation. Thalamocortical cells presented various patterns of spindling that reflected the membrane bistability in RE neurons. Finally, experimental data and computer simulations predicted a role for RE neurons' membrane bistability in inducing various patterns of spindling in target thalamocortical cells. We conclude that membrane bistability of RE neurons is an intrinsic property, likely generated by I(Na(p)) and modulated by cortical influences, as well as a factor that determines different patterns of spindle rhythms in thalamocortical neurons.