scholarly journals The neural correlates of dreaming

2014 ◽  
Author(s):  
Francesca Siclari ◽  
Benjamin Baird ◽  
Lampros Perogamvros ◽  
Giulio Bernardi ◽  
Joshua J LaRocque ◽  
...  
Keyword(s):  
Real Time ◽  
Rem Sleep ◽  
High Frequency ◽  
Low Frequency ◽  
Nrem Sleep ◽  
Neural Correlates ◽  
High Density ◽  
High Frequency Activity ◽  
Cortical Regions ◽  
Hot Zone

Consciousness never fades during wake. However, if awakened from sleep, sometimes we report dreams and sometimes no experiences. Traditionally, dreaming has been identified with REM sleep, characterized by a wake-like, globally "activated", high-frequency EEG. However, dreaming also occurs in NREM sleep, characterized by prominent low-frequency activity. This challenges our understanding of the neural correlates of conscious experiences in sleep. Using high-density EEG, we contrasted the presence and absence of dreaming within NREM and REM sleep. In both NREM and REM sleep, the presence of dreaming was associated with a local decrease in low-frequency activity in posterior cortical regions. High-frequency activity within these regions correlated with specific dream contents. Monitoring this posterior "hot zone" predicted the presence/absence of dreaming during NREM sleep in real time, suggesting that it may constitute a core correlate of conscious experiences in sleep.

scholarly journals The determinants of the subjective perception of sleep: insights from a high-density EEG study with serial awakenings

2021 ◽  
Author(s):  
Aurelie M Stephan ◽  
Sandro Lecci ◽  
Jacinthe Cataldi ◽  
Francesca Siclari
Keyword(s):  
Eye Movement ◽  
Rem Sleep ◽  
High Frequency ◽  
Nrem Sleep ◽  
High Density ◽  
Subjective Perception ◽  
Rapid Eye Movement ◽  
Eeg Activity ◽  
Subjective Sleep ◽  
Sleep Depth

What determines the feeling of being asleep? Standard sleep recordings only incompletely reflect subjective aspects of sleep and some individuals with so-called sleep misperception frequently feel awake although sleep recordings indicate clear-cut sleep. Here we performed 787 awakenings in 20 good sleepers and 10 individuals with severe sleep misperception to interview them about their subjective sleep depth while they underwent high-density EEG sleep recordings (256-channels). Surprisingly, in good sleepers, sleep was subjectively lightest in the first two hours of Non-rapid eye movement (NREM) sleep, generally considered the ′deepest′ sleep, and deepest in rapid eye movement (REM) sleep. Compared to good sleepers, sleep misperceptors felt more frequently awake during sleep, reported overall lighter REM sleep and had more thought-like conscious experiences. In both groups, subjective sleep depth positively correlated with dream-like features of conscious experiences. At the EEG level, spatially widespread high-frequency power was inversely related to subjective sleep depth in NREM sleep in both groups and in REM sleep in misperceptors. Taken together, these findings challenge the widely held notion that ′deep′ (slow wave) sleep best accounts for feeling soundly asleep. Instead, they suggest that subjective sleep depth is inversely related to a neurophysiological process that predominates in NREM sleep early in the night, becomes quiescent in REM sleep and is reflected in high-frequency EEG-activity. In sleep misperceptors, this neurophysiological process is more active and spatially widespread, and abnormally persists into REM sleep. Thus, it is not the presence of ′sleep rhythms′ but rather the absence of ′wake-like′ EEG activity that predicts the feeling of being deeply asleep. These findings will help identify the neuromodulatory systems involved in subjective sleep depth and are therefore relevant for future studies aiming to improve subjective sleep quality.

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

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.

scholarly journals Offline Algorithms in Low-Frequency Trading

Queue ◽  
2020 ◽  
Vol 18 (6) ◽  
pp. 37-51
Author(s):  
Terence Kelly
Keyword(s):  
Real Time ◽  
Real World ◽  
High Frequency ◽  
Low Frequency ◽  
Combinatorial Auctions ◽  
Hard Problem ◽  
Np Hard ◽  
High Stakes ◽  
Drill Bits ◽  
Np Hard Problem

Expectations run high for software that makes real-world decisions, particularly when money hangs in the balance. This third episode of the Drill Bits column shows how well-designed software can effectively create wealth by optimizing gains from trade in combinatorial auctions. We'll unveil a deep connection between auctions and a classic textbook problem, we'll see that clearing an auction resembles a high-stakes mutant Tetris, we'll learn to stop worrying and love an NP-hard problem that's far from intractable in practice, and we'll contrast the deliberative business of combinatorial auctions with the near-real-time hustle of high-frequency trading. The example software that accompanies this installment of Drill Bits implements two algorithms that clear combinatorial auctions.

Arterial blood pressure responses to graded transient arousal from sleep in normal humans

1993 ◽  
Vol 74 (3) ◽  
pp. 1123-1130 ◽  
Author(s):  
R. J. Davies ◽  
P. J. Belt ◽  
S. J. Roberts ◽  
N. J. Ali ◽  
J. R. Stradling
Keyword(s):  
Blood Pressure ◽  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Confidence Interval ◽  
Rem Sleep ◽  
High Frequency ◽  
Pressure Rise ◽  
Nrem Sleep ◽  
Blood Pressure Rise ◽  
Obstructive Sleep

During obstructive sleep apnea, transient arousal at the resumption of breathing is coincident with a substantial rise in blood pressure. To assess the hemodynamic effect of arousal alone, 149 transient stimuli were administered to five normal subjects. Two electroencephalograms (EEG), an electrooculogram, a submental electromyogram (EMG), and beat-to-beat blood pressure (Finapres, Ohmeda) were recorded in all subjects. Stimulus length was varied to produce a range of cortical EEG arousals that were graded as follows: 0, no increase in high-frequency EEG or EMG; 1, increased high-frequency EEG and/or EMG for < 10 s; 2, increased high-frequency EEG and/or EMG for > 10 s. Overall, compared with control values, average systolic pressure rose [nonrapid-eye-movement (NREM) sleep 10.0 +/- 7.69 (SD) mmHg; rapid-eye-movement (REM) sleep 6.0 +/- 6.73 mmHg] and average diastolic pressure rose (NREM sleep 6.1 +/- 4.43 mmHg; REM sleep 3.7 +/- 3.02 mmHg) over the 10 s following the stimulus (NREM sleep, P < 0.0001; REM sleep, P < 0.002). During NREM sleep, there was a trend toward larger blood pressure rises at larger grades of arousal (systolic: r = 0.22, 95% confidence interval 0.02–0.40; diastolic: r = 0.48, 95% confidence interval 0.31–0.62). The average blood pressure rise in response to the grade 2 arousals was approximately 75% of that during obstructive sleep apnea. Arousal stimuli that did not cause EEG arousal still produced a blood pressure rise (mean systolic rise 8.6 +/- 7.0 mmHg, P < 0.0001).(ABSTRACT TRUNCATED AT 250 WORDS)

scholarly journals Fusion of GNSS and Speedometer Based on VMD and Its Application in Bridge Deformation Monitoring

Sensors ◽  
2020 ◽  
Vol 20 (3) ◽  
pp. 694 ◽  
Author(s):  
Ruicheng Zhang ◽  
Chengfa Gao ◽  
Shuguo Pan ◽  
Rui Shang
Keyword(s):  
Real Time ◽  
High Precision ◽  
High Frequency ◽  
Spectral Response ◽  
Low Frequency ◽  
Deformation Monitoring ◽  
Full Time ◽  
Dynamic Displacement ◽  
Mode Decomposition ◽  
Acceleration Sensors

Real-time dynamic displacement and spectral response on the midspan of Jiangyin Bridge were calculated using Global Navigation Satellite System (GNSS) and a speedometer for the purpose of understanding the dynamic behavior and the temporal evolution of the bridge structure. Considering that the GNSS measurement noise is large and the velocity/acceleration sensors cannot measure the low-frequency displacement, the Variational Mode Decomposition (VMD) algorithm was used to extract the low-frequency displacement of GNSS. Then, the low-frequency displacement extracted from the GNSS time series and the high-frequency vibration calculated by speedometer were combined in this paper in order to obtain the high precision three-dimensional dynamic displacement of the bridge in real time. Simulation experiment and measured data show that the VMD algorithm could effectively resist the modal aliasing caused by noise and discontinuous signals compared with the commonly used Empirical Mode Decomposition (EMD) algorithm, which is guaranteed to get high-precision fusion data. Finally, the fused displacement results can identify high-frequency vibrations and low-frequency displacements of a mm level, which can be used to calculate the spectral characteristics of the bridge and provide reference to evaluate the dynamic and static loads, and the health status of the bridge in the full frequency domain and the full time domain.

scholarly journals High-frequency neural activity predicts word parsing in ambiguous speech streams

2016 ◽  
Vol 116 (6) ◽  
pp. 2497-2512 ◽  
Author(s):  
Anne Kösem ◽  
Anahita Basirat ◽  
Leila Azizi ◽  
Virginie van Wassenhove
Keyword(s):  
High Frequency ◽  
Low Frequency ◽  
Acoustic Properties ◽  
Neural Oscillations ◽  
Speech Comprehension ◽  
Top Down ◽  
Linguistic Representations ◽  
High Frequency Activity ◽  
Speech Percept ◽  
The Brain

During speech listening, the brain parses a continuous acoustic stream of information into computational units (e.g., syllables or words) necessary for speech comprehension. Recent neuroscientific hypotheses have proposed that neural oscillations contribute to speech parsing, but whether they do so on the basis of acoustic cues (bottom-up acoustic parsing) or as a function of available linguistic representations (top-down linguistic parsing) is unknown. In this magnetoencephalography study, we contrasted acoustic and linguistic parsing using bistable speech sequences. While listening to the speech sequences, participants were asked to maintain one of the two possible speech percepts through volitional control. We predicted that the tracking of speech dynamics by neural oscillations would not only follow the acoustic properties but also shift in time according to the participant's conscious speech percept. Our results show that the latency of high-frequency activity (specifically, beta and gamma bands) varied as a function of the perceptual report. In contrast, the phase of low-frequency oscillations was not strongly affected by top-down control. Whereas changes in low-frequency neural oscillations were compatible with the encoding of prelexical segmentation cues, high-frequency activity specifically informed on an individual's conscious speech percept.

scholarly journals Brain oscillations and connectivity in autism spectrum disorders (ASD): new approaches to methodology, measurement and modelling

2016 ◽  
Author(s):  
K. Kessler ◽  
R. A. Seymour ◽  
G. Rippon
Keyword(s):  
High Frequency ◽  
Low Frequency ◽  
Autism Spectrum ◽  
List Type ◽  
Brain Oscillations ◽  
New Techniques ◽  
Low Frequencies ◽  
High Frequency Activity ◽  
Recent Classification ◽  
The Brain

AbstractAlthough atypical social behaviour remains a key characterisation of ASD, the presence of sensory and perceptual abnormalities has been given a more central role in recent classification changes. An understanding of the origins of such aberrations could thus prove a fruitful focus for ASD research. Early neurocognitive models of ASD suggested that the study of high frequency activity in the brain as a measure of cortical connectivity might provide the key to understanding the neural correlates of sensory and perceptual deviations in ASD. As our review shows, the findings from subsequent research have been inconsistent, with a lack of agreement about the nature of any high frequency disturbances in ASD brains. Based on the application of new techniques using more sophisticated measures of brain synchronisation, direction of information flow, and invoking the coupling between high and low frequency bands, we propose a framework which could reconcile apparently conflicting findings in this area and would be consistent both with emerging neurocognitive models of autism and with the heterogeneity of the condition.HighlightsSensory and perceptual aberrations are becoming a core feature of the ASD symptom prolife.Brain oscillations and functional connectivity are consistently affected in ASD.Relationships (coupling) between high and low frequencies are also deficient.Novel framework proposes the ASD brain is marked by local dysregulation and reduced top-down connectivityThe ASD brain’s ability to predict stimuli and events in the environment may be affectedThis may underlie perceptual sensitives and cascade into social processing deficits in ASD

Heart Rate Variability during wake and sleep in Huntington’s Disease patients. An observational, cross-sectional, cohort study.

2021 ◽  
Author(s):  
Jessica Marotta ◽  
Carla Piano ◽  
VALERIO BRUNETTI ◽  
Danilo Genovese ◽  
Anna Rita Bentivoglio ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Huntington's Disease ◽  
Huntington’S Disease ◽  
Rem Sleep ◽  
Low Frequency ◽  
Nrem Sleep ◽  
Control Group ◽  
Cross Sectional ◽  
Mean Heart Rate

Introduction Autonomic dysfunction has been reported as one of non-motor manifestations of both pre-symptomatic and manifest Huntington’s Disease (HD). The aim of our study was to evaluate heart rate variability (HRV) during wake and sleep in a cohort of patients with manifest HD. Methods Thirty consecutive patients with manifest HD were enrolled, 14 men and 16 women, mean age 57.3±12.2 years. All patients underwent full-night attended video-polysomnography. HRV was analyzed during wake, NREM and REM sleep, in time and frequency domain. Results were compared with a control group of healthy volunteers matched for age and sex. Results During wake HD patients presented significantly higher mean heart rate than controls (72.4±9.6 vs 58.1±7.3 bpm; p<0.001). During NREM sleep, HD patients showed higher mean heart rate (65.6±11.1 vs 48.8±4.6 bpm; p<0.001) and greater Low Frequency (LF) component of HRV (52.9±22.6 vs 35.5±17.3 n.u.; p=0.004). During REM sleep, we observed lower standard deviation of the R-R interval (SDNN) in HD subjects (3.4±2.2 vs 3.7±1.3 ms; p=0.015). Conclusion Our results showed that HD patients have higher heart rate than controls, during wake and NREM, but not during REM sleep. Among HRV variability parameters, the most relevant difference regarded the LF component, which reflects, at least partially, the ortho-sympathetic output. Our results confirm the involvement of autonomic nervous system in HD and demonstrate that it is evident during both wake and sleep.

Opuntia Ficus Indica Increases Heart-Rate Variability in High-Level Athletes

2008 ◽  
Vol 18 (2) ◽  
pp. 169-178 ◽  
Author(s):  
Laurent Schmitt ◽  
Jean-Pierre Fouillot ◽  
Gérard Nicolet ◽  
Alain Midol
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
High Frequency ◽  
Low Frequency ◽  
Physiological Effects ◽  
Opuntia Ficus Indica ◽  
Diet Supplement ◽  
High Frequency Activity ◽  
High Level

Opuntia ficus indica (OFI) has many physiological effects, but a relationship between OFI and heart-rate variability (HRV) has never been established. The aim of this study was to describe the effects of a diet supplement of OFI on HRV in athletes. The first day, heart rate (HR) was measured at rest in supine (SU) and standing (ST) positions to analyze HRV in 10 athletes, followed by a randomized assignment to an OFI (5) or placebo (5) group. The next day, the athletes repeated the HRV test. One month later the crossover protocol was applied. In OFI, the high-frequency-activity HFSU (1,773 ± 2,927 vs. 5,856 ± 8,326 ms2, p < .05), HFST (295 ± 313 vs. 560 ± 515 ms2, p < .05), and low-frequency LFSU (1,621 ± 1,795 vs. 6,029 ± 9,007 ms2, p < .01) increased. HRSU (66 ± 13 vs. 57 ± 11 beats/min, p < .01) and HRST (87 ± 11 vs. 76 ± 9 beats/min, p < .01) decreased. A diet supplement of OFI increases HF and LF activities and decreases HR.

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