Interhemispheric asymmetry during NREM sleep in the dog

AbstractFunctional hemispheric asymmetry was evidenced in many species during sleep. Dogs seem to show hemispheric asymmetry during wakefulness; however, their asymmetric neural activity during sleep was not yet explored. The present study investigated interhemispheric asymmetry in family dogs using non-invasive polysomnography. EEG recordings during 3-h-long afternoon naps were carried out (N = 19) on two occasions at the same location. Hemispheric asymmetry was assessed during NREM sleep, using bilateral EEG channels. To include periods with high homeostatic sleep pressure and to reduce the variance of the time spent in NREM sleep between dogs, the first two sleep cycles were analysed. Left hemispheric predominance of slow frequency range was detected in the first sleep cycle of sleep recording 1, compared to the baseline level of zero asymmetry as well as to the first sleep cycle of sleep recording 2. Regarding the strength of hemispheric asymmetry, we found greater absolute hemispheric asymmetry in the second sleep cycle of sleep recording 1 and 2 in the frequency ranges of alpha, sigma and beta, compared to the first sleep cycle. Differences between sleep recordings and consecutive sleep cycles might be indicative of adaptation-like processes, but do not closely resemble the results described in humans.

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Correlations using the NREM-REM sleep cycle frequency support distinct regulation mechanisms for REM and NREM sleep

Journal of Applied Physiology ◽

10.1152/japplphysiol.00917.2001 ◽

2002 ◽

Vol 93 (1) ◽

pp. 141-146 ◽

Cited By ~ 21

Author(s):

O. Le Bon ◽

L. Staner ◽

S. K. Rivelli ◽

G. Hoffmann ◽

I. Pelc ◽

...

Keyword(s):

Rem Sleep ◽

Healthy Subjects ◽

Nrem Sleep ◽

Sleep Cycle ◽

Cycle Frequency ◽

Regulation Mechanisms ◽

The Mean ◽

Number Of Cycles ◽

The Relationship ◽

Sleep Cycles

Polysomnograms of most homeothermic species distinguish two states, rapid eye movement (REM) and non-REM (NREM) sleep. These alternate several times during the night for reasons and following rules that remain poorly understood. It is unknown whether each state has its own function and regulation or whether they represent two facets of the same process. The present study compared the mean REM/NREM sleep ratio and the mean number of NREM-REM sleep cycles across 3 consecutive nights. The rationale was that, if REM and NREM sleep are tightly associated, their ratio should be comparable whatever the cycle frequency in the night. Twenty-six healthy subjects of both sexes were recorded at their home for 4 consecutive nights. The correlation between the REM/NREM sleep ratio and the number of cycles was highly significant. Of the two sleep components, REM sleep was associated to the number of cycles, whereas NREM sleep was not. This suggests that the relationship between REM sleep and NREM sleep is rather weak within cycles, does not support the concept of NREM-REM sleep cycles as miniature units of the sleep process, and favors the concept of distinct mechanisms of regulation for the two components.

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The looping lullaby: closed-loop neurostimulation decreases sleepers' sensitivity to environmental noise

10.1101/2021.08.07.455505 ◽

2021 ◽

Author(s):

Vidushi Pathak ◽

Elsa Juan ◽

Reina van der Goot ◽

Lucia Talamini

Keyword(s):

Closed Loop ◽

Real Life ◽

Nrem Sleep ◽

Environmental Noise ◽

Physical And Mental Health ◽

Study Objective ◽

Non Invasive ◽

Eeg Recordings ◽

Sound Pulses ◽

First Time

Study Objective: Sleep is critical for physical and mental health. However, sleep disruption due to noise is a growing problem, causing long-lasting distress and fragilizing entire populations mentally and physically. Here for the first time, we tested an innovative and non-invasive potential countermeasure for sleep disruptions due to noise. Methods: We developed a new, modeling-based, closed-loop acoustic neurostimulation procedure (CLNS) to precisely phase-lock stimuli to slow oscillations (SO). We used CLNS to align, soft sound pulses to the start of the SO positive deflection to boost SO and sleep spindles during non-rapid eye movement (NREM) sleep. Participants underwent three overnight EEG recordings. The first night served to determine each participant ′s individual noise arousal threshold. The remaining two nights occurred in counterbalanced order: in the Disturbing night, loud, real-life noises were repeatedly presented; in the Intervention night, similar loud noises were played while using the CLNS to boost SO. All experimental manipulations were performed in the first three hours of sleep; participants slept undisturbed for the rest of the night. Results: In contrast to the Disturbing night, the probability of arousals caused by noise was significantly decreased in the Intervention night. Moreover, the CLNS intervention increased NREM duration and sleep spindle power across the night. Conclusions: These results show that our CLNS procedure can effectively protect sleep from disruptions caused by noise. Remarkably, even in the presence of loud environmental noise, CLNS ′ soft and precisely timed sound pulses played a beneficial role in protecting sleep continuity. This represents the first successful attempt at using CLNS in a noisy environment.

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Interictal epileptiform activity in sleep and wakefulness in patients with temporal lobe epilepsy

Bulletin of Russian State Medical University ◽

10.24075/brsmu.2019.073 ◽

2019 ◽

pp. 21-26

Author(s):

A.G. Broutian ◽

A.I. Belyakova-Bodina ◽

S.M. Dolgova ◽

T.N. Pushkar ◽

A.A. Abramova

Keyword(s):

Cortical Neurons ◽

Epileptiform Activity ◽

Nrem Sleep ◽

Epileptiform Discharge ◽

Sleep Stages ◽

Recording Time ◽

Temporal Epilepsy ◽

Major Mechanism ◽

Eeg Recordings ◽

Sleep Recording

Sleep is an important activator of epileptiform activity, with epileptiform discharge (ED) probability varying among sleep stages. The aim of our study was to analyze the association between epileptiform activity and sleep stages or wakefulness in adults with temporal discharges. We analyzed 32 long-term overnight EEG recordings. All focal discharges were marked, and the entire sleep was staged. Absolute general epileptiform discharge index (EDI), defined as a ratio of total ED number to the full recording time in hours, as well as absolute EDIs for REM, N1, N2 and N3 stages were calculated. The majority of patients (28) had the highest EDI in N3. EDI increased significantly while sleep progressed to deeper stages, reaching its peak in N3. In REM sleep, EDI sharply declined (p < 0.01) reaching the levels of wakefulness. Increasing synchronization of cortical neurons is thought to be the major mechanism of EDI rise in NREM sleep. Hence, N3 seems to be the most sensitive stage to capture EDs, which highlights the importance of deep sleep recording in patients with temporal epilepsy.

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Endogenous memory reactivation during sleep in humans is clocked by slow oscillation-spindle complexes

Nature Communications ◽

10.1038/s41467-021-23520-2 ◽

2021 ◽

Vol 12 (1) ◽

Author(s):

Thomas Schreiner ◽

Marit Petzka ◽

Tobias Staudigl ◽

Bernhard P. Staresina

Keyword(s):

Memory Function ◽

Nrem Sleep ◽

Stimulus Category ◽

Learning Material ◽

Memory Reactivation ◽

Eeg Recordings ◽

Surface Eeg ◽

Function Of Sleep ◽

Prior Experiences

AbstractSleep is thought to support memory consolidation via reactivation of prior experiences, with particular electrophysiological sleep signatures (slow oscillations (SOs) and sleep spindles) gating the information flow between relevant brain areas. However, empirical evidence for a role of endogenous memory reactivation (i.e., without experimentally delivered memory cues) for consolidation in humans is lacking. Here, we devised a paradigm in which participants acquired associative memories before taking a nap. Multivariate decoding was then used to capture endogenous memory reactivation during non-rapid eye movement (NREM) sleep in surface EEG recordings. Our results reveal reactivation of learning material during SO-spindle complexes, with the precision of SO-spindle coupling predicting reactivation strength. Critically, reactivation strength (i.e. classifier evidence in favor of the previously studied stimulus category) in turn predicts the level of consolidation across participants. These results elucidate the memory function of sleep in humans and emphasize the importance of SOs and spindles in clocking endogenous consolidation processes.

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

npj Parkinson s Disease ◽

10.1038/s41531-021-00211-9 ◽

2021 ◽

Vol 7 (1) ◽

Author(s):

Jing Guang ◽

Halen Baker ◽

Orilia Ben-Yishay Nizri ◽

Shimon Firman ◽

Uri Werner-Reiss ◽

...

Keyword(s):

Basal Ganglia ◽

Rem Sleep ◽

Standard Procedure ◽

Low Frequency ◽

Nrem Sleep ◽

Sleep Cycle ◽

Advanced Parkinson’S Disease ◽

Low Frequency Power ◽

The Brain ◽

Frequency Power

AbstractDeep 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.

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A Novel Modular Headmount Design for non-invasive Scalp EEG Recordings in Awake Animal Models*

2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) ◽

10.1109/embc.2018.8513686 ◽

2018 ◽

Author(s):

Catherine Paulson ◽

Daniel Chien ◽

Francis Lin ◽

Stephanie Seidlits ◽

Yan Cai ◽

...

Keyword(s):

Animal Models ◽

Non Invasive ◽

Scalp Eeg ◽

Eeg Recordings ◽

Awake Animal

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A Neuromorphic Spiking Neural Network Detects Epileptic High Frequency Oscillations in the Scalp EEG

10.21203/rs.3.rs-1061301/v1 ◽

2021 ◽

Author(s):

Karla Burelo ◽

Georgia Ramantani ◽

Giacomo Indiveri ◽

Johannes Sarnthein

Keyword(s):

Low Power ◽

Seizure Frequency ◽

High Frequency ◽

Therapy Monitoring ◽

Non Invasive ◽

Scalp Eeg ◽

High Frequency Oscillations ◽

Eeg Recordings ◽

Active Epilepsy ◽

Wearable Electronic Devices

Abstract Background: Interictal High Frequency Oscillations (HFO) are measurable in scalp EEG. This has aroused interest in investigating their potential as biomarkers of epileptogenesis, seizure propensity, disease severity, and treatment response. The demand for therapy monitoring in epilepsy has kindled interest in compact wearable electronic devices for long- term EEG recording. Spiking neural networks (SNN) have been shown to be optimal architectures for being embedded in compact low-power signal processing hardware. Methods: We analyzed 20 scalp EEG recordings from 11 patients with pediatric focal lesional epilepsy. We designed a custom SNN to detect events of interest (EoI) in the 80-250 Hz ripple band and reject artifacts in the 500-900 Hz band. Results: We identified the optimal SNN parameters to automatically detect EoI and reject artifacts. The occurrence of HFO thus detected was associated with active epilepsy with 80% accuracy. The HFO rate mirrored the decrease in seizure frequency in 8 patients (p = 0.0047). Overall, the HFO rate correlated with seizure frequency (rho = 0.83, p < 0.0001, Spearman’s correlation).Conclusions: The fully automated SNN detected clinically relevant HFO in the scalp EEG. This is a further step towards non-invasive epilepsy monitoring with a low-power wearable device.

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MEG/EEG in the Study of Brain Function

MEG-EEG Primer ◽

10.1093/med/9780190497774.003.0020 ◽

2017 ◽

pp. 304-310

Author(s):

Riitta Hari ◽

Aina Puce

Keyword(s):

Human Brain ◽

Brain Function ◽

Social Neuroscience ◽

Future Research ◽

Noninvasive Methods ◽

Advantages And Disadvantages ◽

Non Invasive ◽

Combined Use ◽

Eeg Recordings ◽

Two Sides

This chapter summarizes some relative advantages and disadvantages of MEG and EEG, most of which have been previously elaborated. MEG and EEG are the two sides of the same coin and provide complementary information about the human brain’s neurodynamics. The combined use of MEG or EEG together and with other noninvasive methods used to study human brain function is advocated to be important for future research in systems and cognitive/social neuroscience. This chapter also examines combined use and interpretation of MEG/EEG with MRI/fMRI, and performing EEG recordings during non-invasive brain stimulation.

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