Breakdown of Effective Connectivity During Slow Wave Sleep: Investigating the Mechanism Underlying a Cortical Gate Using Large-Scale Modeling

Effective connectivity between cortical areas decreases during slow wave sleep. This decline can be observed in the reduced interareal propagation of activity evoked either directly in cortex by transcranial magnetic stimulation (TMS) or by sensory stimulation. We present here a large-scale model of the thalamocortical system that is capable of reproducing these experimental observations. This model was constructed according to a large number of physiological and anatomical constraints and includes over 30,000 spiking neurons interconnected by more than 5 million synaptic connections and organized into three cortical areas. By simulating the different effects of arousal promoting neuromodulators, the model can produce a waking or a slow wave sleep-like mode. In this work, we also seek to explain why intercortical signal transmission decreases in slow wave sleep. The traditional explanation for reduced brain responses during this state, a thalamic gate, cannot account for the reduced propagation between cortical areas. Therefore we propose that a cortical gate is responsible for this diminished intercortical propagation. We used our model to test three candidate mechanisms that might produce a cortical gate during slow wave sleep: a propensity to enter a local down state following perturbation, which blocks the propagation of activity to other areas, increases in potassium channel conductance that reduce neuronal responsiveness, and a shift in the balance of synaptic excitation and inhibition toward inhibition, which decreases network responses to perturbation. Of these mechanisms, we find that only a shift in the balance of synaptic excitation and inhibition can account for the observed in vivo response to direct cortical perturbation as well as many features of spontaneous sleep.

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Increased neural correlations in primate auditory cortex during slow-wave sleep

Journal of Neurophysiology ◽

10.1152/jn.00695.2012 ◽

2013 ◽

Vol 109 (11) ◽

pp. 2732-2738 ◽

Cited By ~ 10

Author(s):

Elias B. Issa ◽

Xiaoqin Wang

Keyword(s):

Auditory Cortex ◽

Spontaneous Activity ◽

Slow Wave ◽

Local Field ◽

Local Field Potential ◽

Slow Wave Sleep ◽

Field Potential ◽

Sensory Stimulation ◽

Acoustic Stimulation ◽

Functional Connections

During sleep, changes in brain rhythms and neuromodulator levels in cortex modify the properties of individual neurons and the network as a whole. In principle, network-level interactions during sleep can be studied by observing covariation in spontaneous activity between neurons. Spontaneous activity, however, reflects only a portion of the effective functional connectivity that is activated by external and internal inputs (e.g., sensory stimulation, motor behavior, and mental activity), and it has been shown that neural responses are less correlated during external sensory stimulation than during spontaneous activity. Here, we took advantage of the unique property that the auditory cortex continues to respond to sounds during sleep and used external acoustic stimuli to activate cortical networks for studying neural interactions during sleep. We found that during slow-wave sleep (SWS), local (neuron-neuron) correlations are not reduced by acoustic stimulation remaining higher than in wakefulness and rapid eye movement sleep and remaining similar to spontaneous activity correlations. This high level of correlations during SWS complements previous work finding elevated global (local field potential-local field potential) correlations during sleep. Contrary to the prediction that slow oscillations in SWS would increase neural correlations during spontaneous activity, we found little change in neural correlations outside of periods of acoustic stimulation. Rather, these findings suggest that functional connections recruited in sound processing are modified during SWS and that slow rhythms, which in general are suppressed by sensory stimulation, are not the sole mechanism leading to elevated network correlations during sleep.

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Selection of stimulus parameters for enhancing slow wave sleep events with a Neural-field theory thalamocortical computational model

10.1101/2021.02.03.429528 ◽

2021 ◽

Author(s):

Felipe A. Torres ◽

Patricio Orio ◽

María-José Escobar

Keyword(s):

Computational Model ◽

Slow Wave ◽

Memory Consolidation ◽

Closed Loop ◽

Slow Wave Sleep ◽

Brain Activity ◽

Sensory Stimulation ◽

Sleep Spindles ◽

Slow Oscillations ◽

Closed Loop Stimulation

AbstractSlow-wave sleep cortical brain activity, conformed by slow-oscillations and sleep spindles, plays a key role in memory consolidation. The increase of the power of the slow-wave events, obtained by auditory sensory stimulation, positively correlates to memory consolidation performance. However, little is known about the experimental protocol maximizing this effect, which could be induced by the power of slow-oscillation, the number of sleep spindles, or the timing of both events’ co-occurrence. Using a mean-field model of thalamocortical activity, we studied the effect of several stimulation protocols, varying the pulse shape, duration, amplitude, and frequency, as well as a target-phase using a closed-loop approach. We evaluated the effect of these parameters on slow-oscillations (SO) and sleep-spindles (SP), considering: (i) the power at the frequency bands of interest, (ii) the number of SO and SP, (iii) co-occurrences between SO and SP, and (iv) synchronization of SP with the up-peak of the SO. The first three targets are maximized using a decreasing ramp pulse with a pulse duration of 50 ms. Also, we observed a reduction in the number of SO when increasing the stimulus energy by rising its amplitude. To assess the target-phase parameter, we applied closed-loop stimulation at 0º, 45º, and 90º of the phase of the narrow-band filtered ongoing activity, at 0.85 Hz as central frequency. The 0º stimulation produces better results in the power and number of SO and SP than the rhythmic or aleatory stimulation. On the other hand, stimulating at 45º or 90º change the timing distribution of spindles centers but with fewer co-occurrences than rhythmic and 0º phase. Finally, we propose the application of closed-loop stimulation at the rising zero-cross point using pulses with a decreasing ramp shape and 50 ms of duration for future experimental work.Author summaryDuring the non-REM (NREM) phase of sleep, events that are known as slow oscillations (SO) and spindles (SP) can be detected by EEG. These events have been associated with the consolidation of declarative memories and learning. Thus, there is an ongoing interest in promoting them during sleep by non-invasive manipulations such as sensory stimulation. In this paper, we used a computational model of brain activity that generates SO and SP, to investigate which type of sensory stimulus –shape, amplitude, duration, periodicity– would be optimal for increasing the events’ frequency and their co-occurrence. We found that a decreasing ramp of 50 ms duration is the most effective. The effectiveness increases when the stimulus pulse is delivered in a closed-loop configuration triggering the pulse at a target phase of the ongoing SO activity. A desirable secondary effect is to promote SPs at the rising phase of the SO oscillation.

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Interactions Between Membrane Conductances Underlying Thalamocortical Slow-Wave Oscillations

Physiological Reviews ◽

10.1152/physrev.00012.2003 ◽

2003 ◽

Vol 83 (4) ◽

pp. 1401-1453 ◽

Cited By ~ 151

Author(s):

A. DESTEXHE ◽

T. J. SEJNOWSKI

Keyword(s):

Experimental Data ◽

Single Cell ◽

Slow Wave ◽

Large Scale ◽

Slow Wave Sleep ◽

Large Body ◽

Electrophysiological Properties ◽

Membrane Conductances ◽

Synaptic Receptors ◽

Slow Wave Oscillations

Destexhe, A., and T. J. Sejnowski. Interactions Between Membrane Conductances Underlying Thalamocortical Slow-Wave Oscillations. Physiol Rev 83: 1401-1453, 2003; 10.1152/physrev.00012.2003.—Neurons of the central nervous system display a broad spectrum of intrinsic electrophysiological properties that are absent in the traditional “integrate-and-fire” model. A network of neurons with these properties interacting through synaptic receptors with many time scales can produce complex patterns of activity that cannot be intuitively predicted. Computational methods, tightly linked to experimental data, provide insights into the dynamics of neural networks. We review this approach for the case of bursting neurons of the thalamus, with a focus on thalamic and thalamocortical slow-wave oscillations. At the single-cell level, intrinsic bursting or oscillations can be explained by interactions between calcium- and voltage-dependent channels. At the network level, the genesis of oscillations, their initiation, propagation, termination, and large-scale synchrony can be explained by interactions between neurons with a variety of intrinsic cellular properties through different types of synaptic receptors. These interactions can be altered by neuromodulators, which can dramatically shift the large-scale behavior of the network, and can also be disrupted in many ways, resulting in pathological patterns of activity, such as seizures. We suggest a coherent framework that accounts for a large body of experimental data at the ion-channel, single-cell, and network levels. This framework suggests physiological roles for the highly synchronized oscillations of slow-wave sleep.

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Increased Stability and Breakdown of Brain Effective Connectivity During Slow-Wave Sleep: Mechanistic Insights from Whole-Brain Computational Modelling

Scientific Reports ◽

10.1038/s41598-017-04522-x ◽

2017 ◽

Vol 7 (1) ◽

Cited By ~ 38

Author(s):

Beatrice M. Jobst ◽

Rikkert Hindriks ◽

Helmut Laufs ◽

Enzo Tagliazucchi ◽

Gerald Hahn ◽

...

Keyword(s):

Slow Wave ◽

Slow Wave Sleep ◽

Effective Connectivity ◽

Computational Modelling ◽

Whole Brain

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Effect of Interaction Between Slow Wave Sleep and Obstructive Sleep Apnea on Insulin Resistance: A Large-scale Study

10.21203/rs.3.rs-135755/v1 ◽

2020 ◽

Author(s):

Weijun Huang ◽

Xiaoting Wang ◽

Yuenan Liu ◽

Xinyi Li ◽

Yupu Liu ◽

...

Keyword(s):

Insulin Resistance ◽

Obstructive Sleep Apnea ◽

Sleep Apnea ◽

Slow Wave ◽

Large Scale ◽

Slow Wave Sleep ◽

Harmful Effect ◽

Joint Effect ◽

Obstructive Sleep ◽

The Status

Abstract Objectives: Slow wave sleep (SWS) and obstructive sleep apnea (OSA) have attracted more and more attention. Their joint effect on insulin resistance (IR) remains to be further studied. This study explored whether less SWS influences the relationship between OSA and IR.Methods: We enrolled potential participants in our sleep center from 2007 to 2019. We collected demographic and clinical characteristics and gauged the IR status. SWS was derived from polysomnography data. Logistic regression analyses were used to reveal the associations between SWS and IR.Results: In all, 6966 participants (5709 OSA and 1257 primary snoring [PS] subjects) were enrolled. Less SWS increases the risk of IR in OSA patients but not in PS patients. OSA patients with SWS < 6.5% were more likely to have IR than those with SWS > 21.3%. OSA was an independent risk factor for IR after adjusting for all potential confounding factors. In stratified analyses according to the percentage of SWS, patients with OSA with SWS < 6.5% had 38.2% higher odds of IR than the PS group after adjusting for all potential confounders. Conclusions: Less SWS is associated with higher odds for IR in OSA patients but not in PS patients. OSA is independently correlated with IR. In addition, OSA combined with an extreme lack of SWS has a more harmful effect on the status of IR than OSA itself.

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Convergence of cortical types and functional motifs in the human mesiotemporal lobe

eLife ◽

10.7554/elife.60673 ◽

2020 ◽

Vol 9 ◽

Cited By ~ 1

Author(s):

Casey Paquola ◽

Oualid Benkarim ◽

Jordan DeKraker ◽

Sara Larivière ◽

Stefan Frässle ◽

...

Keyword(s):

High Resolution ◽

Cognitive Processes ◽

Large Scale ◽

Effective Connectivity ◽

Brain Disorders ◽

Neuronal Density ◽

Functional Organisation ◽

Large Scale Networks ◽

Anterior Posterior

The mesiotemporal lobe (MTL) is implicated in many cognitive processes, is compromised in numerous brain disorders, and exhibits a gradual cytoarchitectural transition from six-layered parahippocampal isocortex to three-layered hippocampal allocortex. Leveraging an ultra-high-resolution histological reconstruction of a human brain, our study showed that the dominant axis of MTL cytoarchitectural differentiation follows the iso-to-allocortical transition and depth-specific variations in neuronal density. Projecting the histology-derived MTL model to in-vivo functional MRI, we furthermore determined how its cytoarchitecture underpins its intrinsic effective connectivity and association to large-scale networks. Here, the cytoarchitectural gradient was found to underpin intrinsic effective connectivity of the MTL, but patterns differed along the anterior-posterior axis. Moreover, while the iso-to-allocortical gradient parametrically represented the multiple-demand relative to task-negative networks, anterior-posterior gradients represented transmodal versus unimodal networks. Our findings establish that the combination of micro- and macrostructural features allow the MTL to represent dominant motifs of whole-brain functional organisation.

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0078 Influence of Light on Brain Activity Upon Waking From Slow Wave Sleep

SLEEP ◽

10.1093/sleep/zsaa056.076 ◽

2020 ◽

Vol 43 (Supplement_1) ◽

pp. A31-A32 ◽

Cited By ~ 1

Author(s):

E E Flynn-Evans ◽

C J Hilditch ◽

R Chachad ◽

K Bansal ◽

L R Wong ◽

...

Keyword(s):

Slow Wave ◽

Slow Wave Sleep ◽

Brain Activity ◽

Effective Connectivity ◽

Red Light ◽

Spectral Composition ◽

Brain Regions ◽

Graphical Analysis ◽

Sleep Inertia ◽

Temporal Persistence

Abstract Introduction Waking from sleep is associated with reduced alertness due to sleep inertia. Light acutely improves alertness during sleep deprivation. In this study we assessed the influence of light on brain activity and connectivity after waking from slow wave sleep (SWS). Methods Twelve participants kept an actigraphy-confirmed stable sleep schedule with 8.5 hours for five nights and five hours for one night prior to an overnight laboratory visit. Participants completed two three-minute Karolinska Drowsiness Tests (KDT) before going to bed at their habitual bedtime. They were monitored continuously using high-density EEG (32-channel; Brain Products GmbH). Participants were woken twice and exposed to red light (0.01 melanopic-lux; control) or blue-enriched light (63.62 melanopic-lux) for one hour, in a randomized order, following at least five minutes of SWS. EEG artifact were removed algorithmically and the spectral composition of each electrode (i.e., fast fourier transform, FFT) and effective connectivity (i.e., partial directed coherence, PDC) between each electrode were estimated. A graphical analysis was conducted to extract features relevant to the facilitation of efficient communication between electrodes. All data were averaged within frequency bins of interest that correspond to delta (1-3Hz), theta (4-7Hz), alpha (8-12Hz), and beta (13-25Hz) bands and expressed relative to the pre-sleep baseline. Results Compared to the pre-sleep baseline, participants exposed to blue-enriched light experienced reduced theta and alpha activity; however, these results were not significantly different from the control. In contrast, the communication of frontal electrodes significantly increased across all frequency bands compared to the control, and this effect was most prominent in the alpha (t(11)=3.80, p=.005) and beta bands (t(11)=3.92, p=.004). Conclusion Exposure to blue-enriched light immediately after waking from SWS may accelerate the process of waking and help to improve alertness by facilitating communication between brain regions. Future analyses will explore the temporal persistence and granularity of the communicative properties associated with this response. Support Naval Postgraduate School Grant. NASA Airspace Operations and Safety Program, System-Wide Safety Project.

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