scholarly journals Up and Down States During Slow Oscillations in Slow-Wave Sleep and Different Levels of Anesthesia

2021 ◽  
Vol 15 ◽  
Author(s):  
Melody Torao-Angosto ◽  
Arnau Manasanch ◽  
Maurizio Mattia ◽  
Maria V. Sanchez-Vives
Keyword(s):  
Slow Wave ◽  
Small Area ◽  
Slow Wave Sleep ◽  
Dynamic Regime ◽  
Network Activity ◽  
Oscillatory Regime ◽  
Slow Oscillations ◽  
State Duration ◽  
Up And Down States ◽  
Different Levels

Slow oscillations are a pattern of synchronized network activity generated by the cerebral cortex. They consist of Up and Down states, which are periods of activity interspersed with periods of silence, respectively. However, even when this is a unique dynamic regime of transitions between Up and Down states, this pattern is not constant: there is a range of oscillatory frequencies (0.1–4 Hz), and the duration of Up vs. Down states during the cycles is variable. This opens many questions. Is there a constant relationship between the duration of Up and Down states? How much do they vary across conditions and oscillatory frequencies? Are there different sub regimes within the slow oscillations? To answer these questions, we aimed to explore a concrete aspect of slow oscillations, Up and Down state durations, across three conditions: deep anesthesia, light anesthesia, and slow-wave sleep (SWS), in the same chronically implanted rats. We found that light anesthesia and SWS have rather similar properties, occupying a small area of the Up and Down state duration space. Deeper levels of anesthesia occupy a larger region of this space, revealing that a large variety of Up and Down state durations can emerge within the slow oscillatory regime. In a network model, we investigated the network parameters that can explain the different points within our bifurcation diagram in which slow oscillations are expressed.

scholarly journals Hippocampal Sharp Wave-Ripples Linked to Slow Oscillations in Rat Slow-Wave Sleep

2006 ◽  
Vol 96 (1) ◽  
pp. 62-70 ◽  
Author(s):  
Matthias Mölle ◽  
Oxana Yeshenko ◽  
Lisa Marshall ◽  
Susan J. Sara ◽  
Jan Born
Keyword(s):  
Slow Wave ◽  
Slow Wave Sleep ◽  
Temporal Dynamics ◽  
Slow Oscillation ◽  
Network Activity ◽  
Event Correlation ◽  
Slow Oscillations ◽  
Sharp Wave ◽  
Neuronal Network Activity ◽  
Up And Down States

Slow oscillations originating in the prefrontal neocortex during slow-wave sleep (SWS) group neuronal network activity and thereby presumably support the consolidation of memories. Here, we investigated whether the grouping influence of slow oscillations extends to hippocampal sharp wave-ripple (SPW) activity thought to underlie memory replay processes during SWS. The prefrontal surface EEG and multiunit activity (MUA), along with hippocampal local field potentials (LFP) from CA1, were recorded in rats during sleep. Average spindle and ripple activity and event correlation histograms of SPWs were calculated, time-locked to half-waves of slow oscillations. Results confirm decreased prefrontal MUA and spindle activity during EEG slow oscillation negativity and increases in this activity during subsequent positivity. A remarkably close temporal link was revealed between slow oscillations and hippocampal activity, with ripple activity and SPWs being also distinctly decreased during negative half-waves and increased during slow oscillation positivity. Fine-grained analyses of temporal dynamics revealed for the slow oscillation a phase delay of approximately 90 ms with reference to up and down states of prefrontal MUA, and of only approximately 60 ms with reference to changes in SPWs, indicating that up and down states in prefrontal MUA precede corresponding changes in hippocampal SPWs by approximately 30 ms. Results support the notion that the depolarizing surface-positive phase of the slow oscillation and the associated up state of prefrontal excitation promotes hippocampal SPWs via efferent pathways. The preceding disfacilitation of hippocampal events temporally coupled to the negative slow oscillation half-wave appears to serve a synchronizing role in this neocorticohippocampal interplay.

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

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.

scholarly journals Spatiotemporal Patterns of Adaptation-Induced Slow Oscillations in a Whole-Brain Model of Slow-Wave Sleep

2022 ◽  
Vol 15 ◽  
Author(s):  
Caglar Cakan ◽  
Cristiana Dimulescu ◽  
Liliia Khakimova ◽  
Daniela Obst ◽  
Agnes Flöel ◽  
...  
Keyword(s):  
Slow Wave ◽  
Traveling Waves ◽  
Large Scale ◽  
Slow Wave Sleep ◽  
Brain Area ◽  
Optimization Approach ◽  
Whole Brain ◽  
Slow Oscillations ◽  
Lower Amplitude ◽  
The Brain

During slow-wave sleep, the brain is in a self-organized regime in which slow oscillations (SOs) between up- and down-states travel across the cortex. While an isolated piece of cortex can produce SOs, the brain-wide propagation of these oscillations are thought to be mediated by the long-range axonal connections. We address the mechanism of how SOs emerge and recruit large parts of the brain using a whole-brain model constructed from empirical connectivity data in which SOs are induced independently in each brain area by a local adaptation mechanism. Using an evolutionary optimization approach, good fits to human resting-state fMRI data and sleep EEG data are found at values of the adaptation strength close to a bifurcation where the model produces a balance between local and global SOs with realistic spatiotemporal statistics. Local oscillations are more frequent, last shorter, and have a lower amplitude. Global oscillations spread as waves of silence across the undirected brain graph, traveling from anterior to posterior regions. These traveling waves are caused by heterogeneities in the brain network in which the connection strengths between brain areas determine which areas transition to a down-state first, and thus initiate traveling waves across the cortex. Our results demonstrate the utility of whole-brain models for explaining the origin of large-scale cortical oscillations and how they are shaped by the connectome.

scholarly journals Selection of stimulus parameters for enhancing slow wave sleep events with a neural-field theory thalamocortical model

2021 ◽  
Vol 17 (7) ◽  
pp. e1008758
Author(s):  
Felipe A. Torres ◽  
Patricio Orio ◽  
María-José Escobar
Keyword(s):  
Slow Wave ◽  
Memory Consolidation ◽  
Closed Loop ◽  
Slow Wave Sleep ◽  
Brain Activity ◽  
Sleep Spindles ◽  
Mean Field Model ◽  
Cross Point ◽  
Slow Oscillations ◽  
Closed Loop Stimulation

Slow-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 0°, 45°, and 90° of the phase of the narrow-band filtered ongoing activity, at 0.85 Hz as central frequency. The 0° stimulation produces better results in the power and number of SO and SP than the rhythmic or random stimulation. On the other hand, stimulating at 45° or 90° change the timing distribution of spindles centers but with fewer co-occurrences than rhythmic and 0° 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.

scholarly journals High-Resolution Spectral Sleep Analysis Reveals a Novel Association Between Slow Oscillations and Memory Retention in Elderly Adults

2021 ◽  
Vol 12 ◽  
Author(s):  
Makoto Kawai ◽  
Logan D. Schneider ◽  
Omer Linkovski ◽  
Josh T. Jordan ◽  
Rosy Karna ◽  
...  
Keyword(s):  
Older Adults ◽  
Slow Wave ◽  
Verbal Memory ◽  
Healthy Aging ◽  
Slow Wave Sleep ◽  
Wave Activity ◽  
Slow Wave Activity ◽  
Medium Effect ◽  
Memory Retention ◽  
Slow Oscillations

Objective: In recognition of the mixed associations between traditionally scored slow wave sleep and memory, we sought to explore the relationships between slow wave sleep, electroencephalographic (EEG) power spectra during sleep and overnight verbal memory retention in older adults.Design, Setting, Participants, and Measurements: Participants were 101 adults without dementia (52% female, mean age 70.3 years). Delayed verbal memory was first tested in the evening prior to overnight polysomnography (PSG). The following morning, subjects were asked to recall as many items as possible from the same List (overnight memory retention; OMR). Partial correlation analyses examined the associations of delayed verbal memory and OMR with slow wave sleep (SWS) and two physiologic EEG slow wave activity (SWA) power spectral bands (0.5–1 Hz slow oscillations vs. 1–4 Hz delta activity).Results: In subjects displaying SWS, SWS was associated with enhanced delayed verbal memory, but not with OMR. Interestingly, among participants that did not show SWS, OMR was significantly associated with a higher slow oscillation relative power, during NREM sleep in the first ultradian cycle, with medium effect size.Conclusions: These findings suggest a complex relationship between SWS and memory and illustrate that even in the absence of scorable SWS, older adults demonstrate substantial slow wave activity. Further, these slow oscillations (0.5–1 Hz), in the first ultradian cycle, are positively associated with OMR, but only in those without SWS. Our findings raise the possibility that precise features of slow wave activity play key roles in maintaining memory function in healthy aging. Further, our results underscore that conventional methods of sleep evaluation may not be sufficiently sensitive to detect associations between SWA and memory in older adults.

scholarly journals Enhancement of Sleep Quality and Stability Using Acoustic Stimulation During Slow Wave Sleep

2018 ◽  
Vol 5 (4) ◽  
pp. 126-134
Author(s):  
Aminollah Golrou ◽  
Ali Sheikhani ◽  
Ali Motie Nasrabadi ◽  
Mohammad Reza Saebipour
Keyword(s):  
Sleep Quality ◽  
Slow Wave ◽  
Slow Wave Sleep ◽  
Acoustic Stimulation ◽  
Deep Sleep ◽  
Quality Of Sleep ◽  
Slow Oscillations ◽  
Random Frequency ◽  
Improve Sleep Quality

Background: One of the challenges today is that the quality of sleep has weakened by many external factors, which we are not even aware of and which directly affect sleep. Sleep quality has an essential role in maintaining the cognitive function and memory consolidation of individuals. So far, various studies have been done to improve the quality of sleep by using external electrical stimulation, vestibular and olfactory system stimulation. Methods: In this study, the increase in sleep quality was considered by simultaneous acoustic stimulation in a deep sleep to increase the density of slow oscillations. Slow oscillations are the important events recorded in electroencephalography (EEG) and hallmark deep sleep. Acoustic stimulation of pink noise with random frequency ranging from 0.8 to 1.1 Hz was used to improve sleep quality. Results: Eight healthy adults (mean age: 28.4±7.8 years) studied in 3 nights under 3 conditions: accommodation night, stimulation night (STIM) and no stimulation night (SHAM), in counterbalanced order. Significant characteristics of the objective and subjective quality of sleep have been extracted from the acquired EEG and compared in the last 2 nights. Also, the arousal and cyclic alternating pattern characteristics have been measured to assess sleep stability over 2 nights of STIM and SHAM. Conclusion: Our findings confirm this goal of the study that applying designed acoustic stimulation simultaneously in the slow wave sleep (SWS) stage increases the duration of deep sleep and ultimately improves overall sleep stability and quality. Keywords: Sleep quality enhancement; Acoustic stimulation; Slow wave sleep; CAP & arousals; Sleep stability; EEG

scholarly journals Serotonin suppresses slow oscillations by activating somatostatin interneurons via the 5-HT2A receptor

2020 ◽  
Author(s):  
Roberto De Filippo ◽  
Benjamin R. Rost ◽  
Alexander Stumpf ◽  
Claire Cooper ◽  
John J. Tukker ◽  
...  
Keyword(s):  
Psychiatric Disorders ◽  
Slow Wave Sleep ◽  
Cortical Network ◽  
Psychological Effects ◽  
Network Activity ◽  
Slow Oscillations ◽  
Physiological Processes ◽  
Electrophysiological Recordings ◽  
Serotonergic Drugs ◽  
The Brain

AbstractSerotonin (5-HT) affects multiple physiological processes in the brain and is involved in a number of psychiatric disorders. 5-HT axons reach all cortical areas; however, the precise mechanism by which 5-HT modulates cortical network activity is not yet fully understood. We investigated the effects of 5-HT on slow oscillations (SO), a synchronized cortical network activity universally present across species. SO are observed during slow-wave sleep and anesthesia and are considered the default cortical activity pattern. Combining opto- and pharmacogenetic manipulations with electrophysiological recordings, we discovered that 5-HT inhibits SO within the entorhinal cortex (EC) by activating somatostatin-expressing (Som) interneurons via the 5-HT2A receptor (5-HT2AR). This receptor is involved in the etiology of different psychiatric disorders and mediates the psychological effects of many psychoactive serotonergic drugs, suggesting that 5-HT targeting of Som interneurons may play an important role in these processes.

Extracellular Calcium Fluctuations and Intracellular Potentials in the Cortex During the Slow Sleep Oscillation

2001 ◽  
Vol 85 (3) ◽  
pp. 1346-1350 ◽  
Author(s):  
Marcello Massimini ◽  
Florin Amzica
Keyword(s):  
Slow Wave ◽  
Cortical Neurons ◽  
Calcium Concentration ◽  
Slow Wave Sleep ◽  
High Gain ◽  
Extracellular Calcium ◽  
Cortical Network ◽  
Network Activity ◽  
Slow Sleep ◽  
Main Activity

During slow wave sleep the main activity of cortical neurons consists of synchronous and rhythmic alternations of the membrane potential between depolarized and hyperpolarized values. The latter are long-lasting (200–600 ms) periods of silence. The mechanisms responsible for this periodical interruption of cortical network activity are unknown. Here we report a decrease of ∼20% in the extracellular calcium concentration ([Ca]out) progressively taking place in the cortex between the onset and the offset of the depolarizing phase of the slow sleep oscillation. Since [Ca]outexerts a high gain modulation of synaptic transmission, we estimated the associated transmitter release probability and found a corresponding 50% drop. Thus the periods of silence occurring in the cortical network during slow wave sleep are promoted by recurrent [Ca]out depletions.

Inhibitory Modulation of Cortical Up States

2010 ◽  
Vol 104 (3) ◽  
pp. 1314-1324 ◽  
Author(s):  
Maria V. Sanchez-Vives ◽  
Maurizio Mattia ◽  
Albert Compte ◽  
Maria Perez-Zabalza ◽  
Milena Winograd ◽  
...  
Keyword(s):  
Slow Wave Sleep ◽  
Epileptiform Activity ◽  
Local Network ◽  
Similar Frequency ◽  
Inhibitory Modulation ◽  
State Duration ◽  
Up States ◽  
Activity Dependent ◽  
Different Levels

The balance between excitation and inhibition is critical in the physiology of the cerebral cortex. To understand the influence of inhibitory control on the emergent activity of the cortical network, inhibition was progressively blocked in a slice preparation that generates spontaneous rhythmic up states at a similar frequency to those occurring in vivo during slow-wave sleep or anesthesia. Progressive removal of inhibition induced a parametric shortening of up state duration and elongation of the down states, the frequency of oscillations decaying. Concurrently, a gradual increase in the network firing rate during up states occurred. The slope of transitions between up and down states was quantified for different levels of inhibition. The slope of upward transitions reflects the recruitment of the local network and was progressively increased when inhibition was decreased, whereas the speed of activity propagation became faster. Removal of inhibition eventually resulted in epileptiform activity. Whereas gradual reduction of inhibition induced linear changes in up/down states and their propagation, epileptiform activity was the result of a nonlinear transformation. A computational network model showed that strong recurrence plus activity-dependent hyperpolarizing currents were sufficient to account for the observed up state modulations and predicted an increase in activity-dependent hyperpolarization following up states when inhibition was decreased, which was confirmed experimentally.

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