Desynchronization of slow oscillations in the basal ganglia during natural sleep

Contributions of Basal Ganglia Circuits to Perception, Attention, and Consciousness

Research into ascending sensory pathways and cortical networks has generated detailed models of perception. These same cortical regions are strongly connected to subcortical structures, such as the basal ganglia (BG), which have been conceptualized as playing key roles in reinforcement learning and action selection. However, because the BG amasses experiential evidence from higher and lower levels of cortical hierarchies, as well as higher-order thalamus, it is well positioned to dynamically influence perception. Here, we review anatomical, functional, and clinical evidence to demonstrate how the BG can influence perceptual processing and conscious states. This depends on the integrative relationship between cortex, BG, and thalamus, which allows contributions to sensory gating, predictive processing, selective attention, and representation of the temporal structure of events.

Consciousness and sleep

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

Phase Delays between Mouse Globus Pallidus Neurons Entrained by Common Oscillatory Drive Arise from Their Intrinsic Properties, Not Their Coupling

A hallmark of Parkinson's disease is the appearance of correlated oscillatory discharge throughout the cortico-basal ganglia (BG) circuits. In the primate globus pallidus (GP), where the discharge of GP neurons is normally uncorrelated, pairs of GP neurons exhibit oscillatory spike correlations with a broad distribution of pairwise phase delays in experimental parkinsonism. The transition to oscillatory correlations is thought to indicate the collapse of the normally segregated information channels traversing the BG. The large phase delays are thought to reflect pathological changes in synaptic connectivity in the BG. Here we study the structure and phase delays of spike correlations measured from neurons in the mouse external GP (GPe) subjected to identical 1-100 Hz sinusoidal drive but recorded in separate experiments. First, we found that spectral modes of a GPe neuron's empirical instantaneous phase response curve (iPRC) elucidate at what phases of the oscillatory drive the GPe neuron locks when it is entrained and the distribution of phases at which it spikes when it is not. Then, we show that in this case the pairwise spike cross-correlation equals the cross-correlation function of these spike phase distributions. Finally, we show that the distribution of GPe phase delays arises from the diversity of iPRCs and is broadened when the neurons become entrained. Modeling GPe networks with realistic intranuclear connectivity demonstrates that the connectivity decorrelates GPe neurons without affecting phase delays. Thus, common oscillatory input gives rise to GPe correlations whose structure and pairwise phase delays reflect their intrinsic properties captured by their iPRCs.

Multi-night cortico-basal recordings reveal mechanisms of NREM slow-wave suppression and spontaneous awakenings in Parkinson's disease

Sleep disturbance is a prevalent and disabling comorbidity in Parkinson's disease (PD). We performed multi-night (n = 57) at-home intracranial recordings from electrocorticography and subcortical electrodes using sensing-enabled Deep Brain Stimulation (DBS), paired with portable polysomnography in four PD participants and one with cervical dystonia (clinical trial: NCT03582891). Cortico-basal activity in delta increased and in beta decreased during NREM (N2 + N3) versus wakefulness in PD. DBS caused further elevation in cortical delta and decrease in alpha and low-beta compared to DBS OFF state. Our primary outcome demonstrated an inverse interaction between subcortical beta and cortical slow-wave during NREM. Our secondary outcome revealed subcortical beta increases prior to spontaneous awakenings in PD. We classified NREM vs. wakefulness with high accuracy in both traditional (30 s: 92.6 ± 1.7%) and rapid (5 s: 88.3 ± 2.1%) data epochs of intracranial signals. Our findings elucidate sleep neurophysiology and impacts of DBS on sleep in PD informing adaptive DBS for sleep dysfunction.

Multi-night cortico-basal recordings reveal mechanisms of NREM slow wave suppression and spontaneous awakenings at high-temporal resolution in Parkinson's disease

Background

Sleep disturbance is a prevalent and highly disabling comorbidity in individuals with Parkinson's disease (PD) that leads to worsening of daytime symptoms, reduced quality of life and accelerated disease progression.

Objectives

We aimed to record naturalistic overnight cortico-basal neural activity in people with PD, in order to determine the neurophysiology of spontaneous awakenings and slow wave suppression in non-rapid eye movement (NREM) sleep, towards the development of novel sleep-targeted neurostimulation therapies.

Methods

Multi-night (n=58) intracranial recordings were performed at-home, from chronic electrocorticography and subcortical electrodes, with sensing-enabled Deep Brain Stimulation (DBS), paired with portable polysomnography. Four participants with PD and one participant with cervical dystonia were evaluated to determine the neural structures, signals and functional connectivity modulated during NREM sleep and prior to spontaneous awakenings. Intracranial recordings were performed both ON and OFF DBS to evaluate the impact of stimulation. Sleep staging was then classified with machine-learning models using intracranial cortico-basal signals on classical (30 s) and rapid (5 s) timescales.

Results

We demonstrate an increase in cortico-basal slow wave delta (1-4 Hz) activity and a decrease in beta (13-31 Hz) activity during NREM (N2 and N3) versus wakefulness in PD. Cortical-basal ganglia coherence was also found to be higher in the delta range and lower in the beta range during NREM. DBS stimulation resulted in a further elevation in cortical delta and a decrease in alpha (8-13 Hz) and low beta (13-15 Hz) power compared to the OFF stimulation state. Within NREM sleep, we observed a strong inverse interaction between subcortical beta and cortical slow wave activity and found that subcortical beta increases prior to spontaneous awakenings at high-temporal resolution (5s). Our machine-learning models trained on intracranial cortical or subcortical power features achieved high accuracy in both traditional (30s) and rapid (5s) time windows for NREM vs. wakefulness classification (30s: 92.6±1.7%; 5s: 88.3±2.1%).

Conclusions

Chronic, multi-night recordings in PD reveal increased cortico-basal slow wave, decreased beta activity, and changes in functional connectivity in NREM vs wakefulness, effects that are enhanced in the presence of DBS. Within NREM, subcortical beta and cortical delta are strongly inversely correlated and subcortical beta power increases prior to spontaneous awakenings. Our findings elucidate the network-level neurophysiology of sleep dysfunction in PD and the mechanistic impact of conventional DBS. Additionally, through accurate machine-learning classification of spontaneous awakenings, this study also provides a foundation for future personalized adaptive DBS therapies for sleep dysfunction in PD.

Effects of deep brain stimulation on quantitative sleep electroencephalogram during non-rapid eye movement in Parkinson's disease

Introduction

Sleep dysfunction is frequently experienced by people with Parkinson's disease (PD) and negatively influences quality of life. Although subthalamic nucleus (STN) deep brain stimulation (DBS) can improve sleep in PD, sleep microstructural features such as sleep spindles provide additional insights about healthy sleep. For example, sleep spindles are important for better cognitive performance and for sleep consolidation in healthy adults. We hypothesized that conventional STN DBS settings would yield a greater enhancement in spindle density compared to OFF and low frequency DBS.

Methods

In a previous within-subject, cross-sectional study, we evaluated effects of low (60 Hz) and conventional high (≥130 Hz) frequency STN DBS settings on sleep macroarchitectural features in individuals with PD. In this post hoc, exploratory analysis, we conducted polysomnography (PSG)-derived quantitative electroencephalography (qEEG) assessments in a cohort of 15 individuals with PD who had undergone STN DBS treatment a median 13.5 months prior to study participation. Fourteen participants had unilateral DBS and 1 had bilateral DBS. During three nonconsecutive nights of PSG, the participants were assessed under three different DBS conditions: DBS OFF, DBS LOW frequency (60 Hz), and DBS HIGH frequency (≥130 Hz). The primary objective of this study was to investigate the changes in sleep spindle density across the three DBS conditions using repeated-measures analysis of variance. Additionally, we examined various secondary outcomes related to sleep qEEG features. For all participants, PSG-derived EEG data underwent meticulous manual inspection, with the exclusion of any segments affected by movement artifact. Following artifact rejection, sleep qEEG analysis was conducted on frontal and central leads. The measures included slow wave (SW) and spindle density and morphological characteristics, SW-spindle phase-amplitude coupling, and spectral power analysis during non-rapid eye movement (NREM) sleep.

Results

The analysis revealed that spindle density was significantly higher in the DBS HIGH condition compared to the DBS LOW condition. Surprisingly, we found that SW amplitude during NREM was significantly higher in the DBS LOW condition compared to DBS OFF and DBS HIGH conditions. However, no significant differences were observed in the other sleep qEEG features during sleep at different DBS conditions.

Conclusion

This study presents preliminary evidence suggesting that conventional HIGH frequency DBS settings enhance sleep spindle density in PD. Conversely, LOW frequency settings may have beneficial effects on increasing slow wave amplitude during sleep. These findings may inform mechanisms underlying subjective improvements in sleep quality reported in association with DBS. Moreover, this work supports the need for additional research on the influence of surgical interventions on sleep disorders, which are prevalent and debilitating non-motor symptoms in PD.

Propagation of Oscillations in the Indirect Pathway of the Basal Ganglia

Oscillatory signals propagate in the basal ganglia from prototypic neurons in the external globus pallidus (GPe) to their target neurons in the substantia nigra pars reticulata (SNr), internal pallidal segment, and subthalamic nucleus. Neurons in the GPe fire spontaneously, so oscillatory input signals can be encoded as changes in timing of action potentials within an ongoing spike train. When GPe neurons were driven by an oscillatory current in male and female mice, these spike-timing changes produced spike-oscillation coherence over a range of frequencies extending at least to 100 Hz. Using the known kinetics of the GPe→SNr synapse, we calculated the postsynaptic currents that would be generated in SNr neurons from the recorded GPe spike trains. The ongoing synaptic barrage from spontaneous firing, frequency-dependent short-term depression, and stochastic fluctuations at the synapse embed the input oscillation into a noisy sequence of synaptic currents in the SNr. The oscillatory component of the resulting synaptic current must compete with the noisy spontaneous synaptic barrage for control of postsynaptic SNr neurons, which have their own frequency-dependent sensitivities. Despite this, SNr neurons subjected to synaptic conductance changes generated from recorded GPe neuron firing patterns also became coherent with oscillations over a broad range of frequencies. The presynaptic, synaptic, and postsynaptic frequency sensitivities were all dependent on the firing rates of presynaptic and postsynaptic neurons. Firing rate changes, often assumed to be the propagating signal in these circuits, do not encode most oscillation frequencies, but instead determine which signal frequencies propagate effectively and which are suppressed.SIGNIFICANCE STATEMENT Oscillations are present in all the basal ganglia nuclei, include a range of frequencies, and change over the course of learning and behavior. Exaggerated oscillations are a hallmark of basal ganglia pathologies, and each has a specific frequency range. Because of its position as a hub in the basal ganglia circuitry, the globus pallidus is a candidate origin for oscillations propagating between nuclei. We imposed low-amplitude oscillations on individual globus pallidus neurons at specific frequencies and measured the coherence between the oscillation and firing as a function of frequency. We then used these responses to measure the effectiveness of oscillatory propagation to other basal ganglia nuclei. Propagation was effective for oscillation frequencies as high as 100 Hz.

Dichotomous activity and function of neurons with low- and high-frequency discharge in the external globus pallidus of non-human primates

To date, there is a consensus that there are at least two neuronal populations in the non-human primate (NHP) external globus pallidus (GPe): low-frequency discharge (LFD) and high-frequency discharge (HFD) neurons. Nevertheless, almost all NHP physiological studies have neglected the functional importance of LFD neurons. This study examined the discharge features of these two GPe neuronal subpopulations recorded in four NHPs engaged in a classical conditioning task with cues predicting reward, neutral and aversive outcomes. The results show that LFD neurons tended to burst, encoded the salience of behavioral cues, and exhibited correlated spiking activity. By contrast, the HFD neurons tended to pause, encoded cue valence, and exhibited uncorrelated spiking activity. Overall, these findings point to the dichotomic organization of the NHP GPe, which is likely to be critical to the implementation of normal basal ganglia functions and computations.

Entrainment to sleep spindles reflects dissociable patterns of connectivity between cortex and basal ganglia

Sleep spindles are crucial for learning in the cortex and basal ganglia (BG) because they facilitate the reactivation of previously active neuronal ensembles. Studying field potentials (FPs) and spiking in the cortex and BG during sleep in non-human primates following pre-sleep learning, we show that FP sleep spindles are widespread in the BG and are similar to cortical spindles in morphology, spectral content, and response to the pre-sleep task. Further, BG spindles are concordant with electroencephalogram (EEG) spindles and associated with increased cortico-BG correlation. However, spindles across the BG differ markedly in their entrainment of local spiking. The spiking activity of striatal projection neurons exhibits consistent phase locking to striatal and EEG spindles, producing phase windows of peaked cross-region spindling. In contrast, firing in other BG nuclei is not entrained to either local or EEG sleep spindles. These results suggest corticostriatal synapses as the main hub for offline cortico-BG communication.

Non-uniform distribution of dendritic nonlinearities differentially engages thalamostriatal and corticostriatal inputs onto cholinergic interneurons

The tonic activity of striatal cholinergic interneurons (CINs) is modified differentially by their afferent inputs. Although their unitary synaptic currents are identical, in most CINs cortical inputs onto distal dendrites only weakly entrain them, whereas proximal thalamic inputs trigger abrupt pauses in discharge in response to salient external stimuli. To test whether the dendritic expression of the active conductances that drive autonomous discharge contribute to the CINs’ capacity to dissociate cortical from thalamic inputs, we used an optogenetics-based method to quantify dendritic excitability in mouse CINs. We found that the persistent sodium (NaP) current gave rise to dendritic boosting, and that the hyperpolarization-activated cyclic nucleotide-gated (HCN) current gave rise to a subhertz membrane resonance. This resonance may underlie our novel finding of an association between CIN pauses and internally-generated slow wave events in sleeping non-human primates. Moreover, our method indicated that dendritic NaP and HCN currents were preferentially expressed in proximal dendrites. We validated the non-uniform distribution of NaP currents: pharmacologically; with two-photon imaging of dendritic back-propagating action potentials; and by demonstrating boosting of thalamic, but not cortical, inputs by NaP currents. Thus, the localization of active dendritic conductances in CIN dendrites mirrors the spatial distribution of afferent terminals and may promote their differential responses to thalamic vs. cortical inputs.

Slow oscillations promote long-range effective communication: The key for memory consolidation in a broken-down network

This work introduces a noninvasive approach to understanding information processing during sleep. Our results demonstrate that slow oscillations (SOs) provide the temporal-topographical event framework whereby long-range information flow increases dramatically compared to the relatively local activity patterns of the rest of sleep. The findings represent a conceptual leap in understanding how SOs unlock memory consolidation in a broken-down network, which is by promoting long-range, effective communication. This research will promote further investigations of understanding how brain oscillations alone and in nested rhythms promote network communication, as well as investigate how these properties vary and predict patterns of deficits in clinical populations and aging humans.

A prominent and robust finding in cognitive neuroscience is the strengthening of memories during nonrapid eye movement (NREM) sleep, with slow oscillations (SOs;<1Hz) playing a critical role in systems-level consolidation. However, NREM generally shows a breakdown in connectivity and reduction of synaptic plasticity with increasing depth: a brain state seemingly unfavorable to memory consolidation. Here, we present an approach to address this apparent paradox that leverages an event-related causality measure to estimate directional information flow during NREM in epochs with and without SOs. Our results confirm that NREM is generally a state of dampened neural communication but reveals that SOs provide two windows of enhanced large-scale communication before and after the SO trough. These peaks in communication are significantly higher when SOs are coupled with sleep spindles compared with uncoupled SOs. To probe the functional relevance of these SO-selective peaks of information flow, we tested the temporal and topographic conditions that predict overnight episodic memory improvement. Our results show that global, long-range communication during SOs promotes sleep-dependent systems consolidation of episodic memories. A significant correlation between peaks of information flow and memory improvement lends predictive validity to our measurements of effective connectivity. In other words, we were able to predict memory improvement based on independent electrophysiological observations during sleep. This work introduces a noninvasive approach to understanding information processing during sleep and provides a mechanism for how systems-level brain communication can occur during an otherwise low connectivity sleep state. In short, SOs are a gating mechanism for large-scale neural communication, a necessary substrate for systems consolidation and long-term memory formation.

Spontaneous pauses in firing of external pallidum neurons are associated with exploratory behavior

Spontaneous pauses in firing are the hallmark of external pallidum (GPe) neurons. However, the role of GPe pauses in the basal ganglia network remains unknown. Pupil size and saccadic eye movements have been linked to attention and exploration. Here, we recorded GPe spiking activity and the corresponding pupil sizes and eye positions in non-human primates. We show that pauses, rather than the GPe discharge rate per se, were associated with dilated pupils. In addition, following pause initiation there was a considerable increase in the rate of spontaneous saccades. These results suggest that pauses are a powerful mechanism by which the GPe may influence basal ganglia downstream structures and play a role in exploratory behavior.

Integrated analysis of external pallidum (GPe) neuronal firing, pupil size, and saccadic movements in non-human primates reveals that pauses in GPe firing are associated with pupil dilation. These results suggest that pauses in GPe activity might influence downstream structures in the basal ganglia network and influence exploratory behavior.

Visuomotor Adaptation Modulates the Clustering of Sleep Spindles Into Trains

Sleep spindles are thought to promote memory consolidation. Recently, we have shown that visuomotor adaptation (VMA) learning increases the density of spindles and promotes the coupling between spindles and slow oscillations, locally, with the level of spindle-SO synchrony predicting overnight memory retention. Yet, growing evidence suggests that the rhythmicity in spindle occurrence may also influence the stabilization of declarative and procedural memories. Here, we examined if VMA learning promotes the temporal organization of sleep spindles into trains. We found that VMA increased the proportion of spindles and spindle-SO couplings in trains. In agreement with our previous work, this modulation was observed over the contralateral hemisphere to the trained hand, and predicted overnight memory retention. Interestingly, spindles grouped in a cluster showed greater amplitude and duration than isolated spindles. The fact that these features increased as a function of train length, provides evidence supporting a biological advantage of this temporal arrangement. Our work opens the possibility that the periodicity of NREM oscillations may be relevant in the stabilization of procedural memories.

Etiologies of insomnia in Parkinson's disease - Lessons from human studies and animal models

Sleep disorders are integral to Parkinson's disease (PD). Insomnia, an inability to maintain stable sleep, affects most patients and is widely rated as one of the most debilitating facets of this disease. PD insomnia is often perceived as a multifactorial entity - a consequence of several of the disease symptoms, comorbidities and therapeutic strategies. Yet, this view evolved against a backdrop of a relative scarcity of works trying to directly dissect the underlying neural correlates and mechanisms in animal models. The last years have seen the emergence of a wealth of new evidence regarding the neural underpinnings of insomnia in PD. Here, we review early and recent reports from patients and animal models evaluating the etiology of PD insomnia. We start by outlining the phenomenology of PD insomnia and continue to analyze the evidence supporting insomnia as emanating from four distinct subdivisions of etiologies - the symptoms and comorbidities of the disease, the medical therapy, the degeneration of non-dopaminergic cell groups and subsequent alterations in circadian rhythms, and the degeneration of dopaminergic neurons in the brainstem and its resulting effect on the basal ganglia. Finally, we review emerging neuromodulation-based therapeutic avenues for PD insomnia.

Basal Ganglia Local Field Potentials as a Potential Biomarker for Sleep Disturbance in Parkinson's Disease

Sleep disturbances, specifically decreases in total sleep time and sleep efficiency as well as increased sleep onset latency and wakefulness after sleep onset, are highly prevalent in patients with Parkinson's disease (PD). Impairment of sleep significantly and adversely impacts several comorbidities in this patient population, including cognition, mood, and quality of life. Sleep disturbances and other non-motor symptoms of PD have come to the fore as the effectiveness of advanced therapies such as deep brain stimulation (DBS) optimally manage the motor symptoms. Although some studies have suggested that DBS provides benefit for sleep disturbances in PD, the mechanisms by which this might occur, as well as the optimal stimulation parameters for treating sleep dysfunction, remain unknown. In patients treated with DBS, electrophysiologic recording from the stimulating electrode, in the form of local field potentials (LFPs), has led to the identification of several findings associated with both motor and non-motor symptoms including sleep. For example, beta frequency (13–30 Hz) oscillations are associated with worsened bradykinesia while awake and decrease during non-rapid eye movement sleep. LFP investigation of sleep has largely focused on the subthalamic nucleus (STN), though corresponding oscillatory activity has been found in the globus pallidus internus (GPi) and thalamus as well. LFPs are increasingly being recognized as a potential biomarker for sleep states in PD, which may allow for closed-loop optimization of DBS parameters to treat sleep disturbances in this population. In this review, we discuss the relationship between LFP oscillations in STN and the sleep architecture of PD patients, current trends in utilizing DBS to treat sleep disturbance, and future directions for research. In particular, we highlight the capability of novel technologies to capture and record LFP data in vivo, while patients continue therapeutic stimulation for motor symptoms. These technological advances may soon allow for real-time adaptive stimulation to treat sleep disturbances.

Motor Learning Promotes the Coupling between Fast Spindles and Slow Oscillations Locally over the Contralateral Motor Network

Recent studies from us and others suggest that traditionally declarative structures mediate some aspects of the encoding and consolidation of procedural memories. This evidence points to the existence of converging physiological pathways across memory systems. Here, we examined whether the coupling between slow oscillations (SO) and spindles, a mechanism well established in the consolidation of declarative memories, is relevant for the stabilization of human motor memories. To this aim, we conducted an electroencephalography study in which we quantified various parameters of these oscillations during a night of sleep that took place immediately after learning a visuomotor adaptation (VMA) task. We found that VMA increased the overall density of fast (≥12 Hz), but not slow (<12 Hz), spindles during nonrapid eye movement sleep, stage 3 (NREM3). This modulation occurred rather locally over the hemisphere contralateral to the trained hand. Although adaptation learning did not affect the density of SOs, it substantially enhanced the number of fast spindles locked to the active phase of SOs. The fact that only coupled spindles predicted overnight memory retention points to the relevance of this association in motor memory consolidation. Our work provides evidence in favor of a common mechanism at the basis of the stabilization of declarative and motor memories.

Heterogenous electrophysiological responses of functionally distinct striatal subregions to circadian and sleep-related homeostatic processes

Basal Ganglia (BG) are a set of subcortical nuclei that are involved in the control of a wide variety of motor, cognitive and affective behaviors. Although many behavioral abnormalities associated with BG dysfunction overlap with the clinical picture precipitated by the lack of sleep, the impact of sleep alterations on neuronal activity in BG is unknown. Using wildtype C57BI mice, we investigated the circadian and sleep-related homeostatic modulation of neuronal activity in the 3 functional subdivisions of the striatum (i.e. sensorimotor, associative and limbic striatum). We found no circadian modulation of activity in both ventral and dorso-medial striatum while the dorso-lateral striatum displayed a significant circadian rhythm with increased firing rates during the subjective dark, active phase. By combining neuronal activity recordings with electroencephalogram (EEG) recordings, we found a strong modulation of neuronal activity by the nature of vigilance states with increased activity during wakefulness and rapid eye movement sleep relative to non-rapid eye movement sleep in all striatal subregions. Depriving animals of sleep for 6 hours induced significant, but heterogenous alterations in the neuronal activity across striatal subregions. Notably, these alterations lasted for up to 48 hours in the sensorimotor striatum and persisted even after the normalization of cortical EEG power densities. Our results show that vigilance and sleep states as well as their disturbances significantly affect neuronal activity within the striatum. We propose that these changes in neuronal activity underlie both the well-established links between sleep alterations and several disorders involving BG dysfunction as well as the maladaptive changes in behavior induced in healthy subjects following sleep loss.

Factor Structure of the Children's Sleep Habits Questionnaire in Young Children with and Without Autism

The Children's Sleep Habits Questionnaire (CSHQ) is often used to assess sleep in children with autism spectrum disorder (ASD), but little is known about its factor structure in younger children with ASD. We evaluated alternative factor structures and measurement invariance for CSHQ items in 2- to 4-year-olds with ASD or typical development (TD). Bifactor models indicated subscales' variance was subsumed by a general factor predominantly reflecting sleep initiation and nighttime awakening items. A factor consisting of 7 of these items was measurement invariant across ASD and TD. Thus, comparisons between young children with ASD and TD is appropriate for a measure composed of 7 CSHQ items relating to sleep initiation and awakenings but not for other CSHQ item composites.

Toward asleep DBS: cortico-basal ganglia spectral and coherence activity during interleaved propofol/ketamine sedation mimics NREM/REM sleep activity

Deep brain stimulation (DBS) is currently a standard procedure for advanced Parkinson's disease. Many centers employ awake physiological navigation and stimulation assessment to optimize DBS localization and outcome. To enable DBS under sedation, asleep DBS, we characterized the cortico-basal ganglia neuronal network of two nonhuman primates under propofol, ketamine, and interleaved propofol-ketamine (IPK) sedation. Further, we compared these sedation states in the healthy and Parkinsonian condition to those of healthy sleep. Ketamine increases high-frequency power and synchronization while propofol increases low-frequency power and synchronization in polysomnography and neuronal activity recordings. Thus, ketamine does not mask the low-frequency oscillations used for physiological navigation toward the basal ganglia DBS targets. The brain spectral state under ketamine and propofol mimicked rapid eye movement (REM) and Non-REM (NREM) sleep activity, respectively, and the IPK protocol resembles the NREM-REM sleep cycle. These promising results are a meaningful step toward asleep DBS with nondistorted physiological navigation.

The Neurophysiology of Sleep in Parkinson's Disease

Sleep disturbances are among the most common nonmotor complications of Parkinson's disease (PD), can present in prodromal stages, and progress with advancing disease. In addition to being a symptom of neurodegeneration, sleep disturbances may also contribute to disease progression. Currently, limited options exist to modulate sleep disturbances in PD. Studying the neurophysiological changes that affect sleep in PD at the cortical and subcortical level may yield new insights into mechanisms for reversal of sleep disruption. In this article, we review cortical and subcortical recording studies of sleep in PD with a particular focus on dissecting reported electrophysiological changes. These studies show that slow-wave sleep and rapid eye movement sleep are both notably disrupted in PD. We further explore the impact of these electrophysiological changes and discuss the potential for targeting sleep via stimulation therapy to modify PD-related motor and nonmotor symptoms. © 2021 International Parkinson and Movement Disorder Society.

Dissociation of tic generation from tic expression during the sleep-wake cycle

Motor tics, the hallmark of Tourette syndrome (TS), are modulated by different behavioral and environmental factors. A major modulating factor is the sleep-wake cycle in which tics are attenuated to a large extent during sleep. This study demonstrates a similar reduction in tic expression during sleep in an animal model of chronic tic disorders and investigates the underlying neural mechanism. We recorded the neuronal activity during spontaneous sleep-wake cycles throughout continuous GABA_A antagonist infusion into the striatum. Analysis of video streams and concurrent kinematic assessments indicated tic reduction during sleep in both frequency and intensity. Extracellular recordings in the striatum revealed a state-dependent dissociation between motor tic expression and their macro-level neural correlates ("LFP spikes") during the sleep-wake cycle. Local field potential (LFP) spikes, which are highly correlated with tic expression during wakefulness, persisted during tic-free sleep and did not change their properties despite the reduced behavioral expression. Local, micro-level, activity near the infusion site was time-locked to the LFP spikes during wakefulness, but this locking decreased significantly during sleep. These results suggest that whereas LFP spikes encode motor tic generation and feasibility, the behavioral expression of tics requires local striatal neural activity entrained to the LFP spikes, leading to the propagation of the activity to downstream targets and consequently their motor expression. These findings point to a possible mechanism for the modulation of tic expression in patients with TS during sleep and potentially during other behavioral states.

Anesthetics fragment hippocampal network activity, alter spine dynamics, and affect memory consolidation

General anesthesia is characterized by reversible loss of consciousness accompanied by transient amnesia. Yet, long-term memory impairment is an undesirable side effect. How different types of general anesthetics (GAs) affect the hippocampus, a brain region central to memory formation and consolidation, is poorly understood. Using extracellular recordings, chronic 2-photon imaging, and behavioral analysis, we monitor the effects of isoflurane (Iso), medetomidine/midazolam/fentanyl (MMF), and ketamine/xylazine (Keta/Xyl) on network activity and structural spine dynamics in the hippocampal CA1 area of adult mice. GAs robustly reduced spiking activity, decorrelated cellular ensembles, albeit with distinct activity signatures, and altered spine dynamics. CA1 network activity under all 3 anesthetics was different to natural sleep. Iso anesthesia most closely resembled unperturbed activity during wakefulness and sleep, and network alterations recovered more readily than with Keta/Xyl and MMF. Correspondingly, memory consolidation was impaired after exposure to Keta/Xyl and MMF, but not Iso. Thus, different anesthetics distinctly alter hippocampal network dynamics, synaptic connectivity, and memory consolidation, with implications for GA strategy appraisal in animal research and clinical settings.

Time in Brain: How Biological Rhythms Impact on EEG Signals and on EEG-Derived Brain Networks

Electroencephalography (EEG) is a widely employed tool for exploring brain dynamics and is used extensively in various domains, ranging from clinical diagnosis via neuroscience, cognitive science, cognitive psychology, psychophysiology, neuromarketing, neurolinguistics, and pharmacology to research on brain computer interfaces. EEG is the only technique that enables the continuous recording of brain dynamics over periods of time that range from a few seconds to hours and days and beyond. When taking long-term recordings, various endogenous and exogenous biological rhythms may impinge on characteristics of EEG signals. While the impact of the circadian rhythm and of ultradian rhythms on spectral characteristics of EEG signals has been investigated for more than half a century, only little is known on how biological rhythms influence characteristics of brain dynamics assessed with modern EEG analysis techniques. At the example of multiday, multichannel non-invasive and invasive EEG recordings, we here discuss the impact of biological rhythms on temporal changes of various characteristics of human brain dynamics: higher-order statistical moments and interaction properties of multichannel EEG signals as well as local and global characteristics of EEG-derived evolving functional brain networks. Our findings emphasize the need to take into account the impact of biological rhythms in order to avoid erroneous statements about brain dynamics and about evolving functional brain networks.

Basal ganglia beta oscillations during sleep underlie Parkinsonian insomnia

Sleep disorders are among the most debilitating comorbidities of Parkinson's disease (PD) and affect the majority of patients. Of these, the most common is insomnia, the difficulty to initiate and maintain sleep. The degree of insomnia correlates with PD severity and it responds to treatments that decrease pathological basal ganglia (BG) beta oscillations (10-17 Hz in primates), suggesting that beta activity in the BG may contribute to insomnia. We used multiple electrodes to record BG spiking and field potentials during normal sleep and in 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-induced Parkinsonism in nonhuman primates. MPTP intoxication resulted in severe insomnia with delayed sleep onset, sleep fragmentation, and increased wakefulness. Insomnia was accompanied by the onset of nonrapid eye movement (NREM) sleep beta oscillations that were synchronized across the BG and cerebral cortex. The BG beta oscillatory activity was associated with a decrease in slow oscillations (0.1-2 Hz) throughout the cortex, and spontaneous awakenings were preceded by an increase in BG beta activity and cortico-BG beta coherence. Finally, the increase in beta oscillations in the basal ganglia during sleep paralleled decreased NREM sleep, increased wakefulness, and more frequent awakenings. These results identify NREM sleep beta oscillation in the BG as a neural correlate of PD insomnia and suggest a mechanism by which this disorder could emerge.

Low-frequency oscillations in coupled phase oscillators with inertia

This work considers a second-order Kuramoto oscillator network periodically driven at one node to model low-frequency forced oscillations in power grids. The phase fluctuation magnitude at each node and the disturbance propagation in the network are numerically analyzed. The coupling strengths in this work are sufficiently large to ensure the stability of equilibria in the unforced system. It is found that the phase fluctuation is primarily determined by the network structural properties and forcing parameters, not the parameters specific to individual nodes such as power and damping. A new "resonance" phenomenon is observed in which the phase fluctuation magnitudes peak at certain critical coupling strength in the forced system. In the cases of long chain and ring-shaped networks, the Kuramoto model yields an important but somehow counter-intuitive result that the fluctuation magnitude distribution does not necessarily follow a simple attenuating trend along the propagation path and the fluctuation at nodes far from the disturbance source could be stronger than that at the source. These findings are relevant to low-frequency forced oscillations in power grids and will help advance the understanding of their dynamics and mechanisms and improve the detection and mitigation techniques.

Population dynamics and entrainment of basal ganglia pacemakers are shaped by their dendritic arbors

The theory of phase oscillators is an essential tool for understanding population dynamics of pacemaking neurons. GABAergic pacemakers in the substantia nigra pars reticulata (SNr), a main basal ganglia (BG) output nucleus, receive inputs from the direct and indirect pathways at distal and proximal regions of their dendritic arbors, respectively. We combine theory, optogenetic stimulation and electrophysiological experiments in acute brain slices to ask how dendritic properties impact the propensity of the various inputs, arriving at different locations along the dendrite, to recruit or entrain SNr pacemakers. By combining cable theory with sinusoidally-modulated optogenetic activation of either proximal somatodendritic regions or the entire somatodendritic arbor of SNr neurons, we construct an analytical model that accurately fits the empirically measured somatic current response to inputs arising from illuminating the soma and various portions of the dendritic field. We show that the extent of the dendritic tree that is illuminated generates measurable and systematic differences in the pacemaker’s phase response curve (PRC), causing a shift in its peak. Finally, we show that the divergent PRCs correctly predict differences in two major features of the collective dynamics of SNr neurons: the fidelity of population responses to sudden step-like changes in inputs; and the phase latency at which SNr neurons are entrained by rhythmic stimulation, which can occur in the BG under both physiological and pathophysiological conditions. Our novel method generates measurable and physiologically meaningful spatial effects, and provides the first empirical demonstration of how the collective responses of SNr pacemakers are determined by the transmission properties of their dendrites. SNr dendrites may serve to delay distal striatal inputs so that they impinge on the spike initiation zone simultaneously with pallidal and subthalamic inputs in order to guarantee a fair competition between the influence of the monosynaptic direct- and polysynaptic indirect pathways.

The substantia nigra pars reticulata (SNr) is a main output nucleus of the basal ganglia (BG), where inputs from the competing direct and indirect pathways converge onto the same neurons. Interestingly, these inputs are differentially distributed with direct and indirect pathway projections arriving at distal and proximal regions of the dendritic arbor, respectively. We employ a novel method combining theory with electrophysiological experiments and optogenetics to study the distinct effects of inputs arriving at different locations along the dendrite. Our approach represents a useful compromise between complexity and reduction in modelling. Our work addresses the question of high fidelity encoding of inputs by networks of neurons in the new context of pacemaking neurons, which are driven to fire by their intrinsic dynamics rather than by a network state. We provide the first empirical demonstration that dendritic delays can introduce latencies in the responses of a population of neurons that are commensurate with synaptic delays, suggesting a new role for SNr dendrites with implications for BG function.