Expanding Nielsen's covert REM model, questioning Solms's approach to dreaming and REM sleep, and reinterpreting the Vertes & Eastman view of REM sleep and memory

2000 ◽  
Vol 23 (6) ◽  
pp. 981-983 ◽  
Author(s):  
Robert D. Ogilvie ◽  
Tomoka Takeuchi ◽  
Timothy I. Murphy
Keyword(s):  
Cognitive Processes ◽  
Rem Sleep ◽  
Process Model ◽  
Nrem Sleep ◽  
Present Problem ◽  
Dream Theory

Nielsen's covert REM process model explains much of the mentation found in REM and NREM sleep, but stops short of postulating an interaction of waking cognitive processes with the dream mechanisms of REM sleep. It ranks with the Hobson et al. paper as a major theoretical advance. The Solms article does not surmount the ever-present problem of defining dreams in a manner conducive to advancing dream theory. Vertes & Eastman review the REM sleep and learning literature, but make questionable assumptions in doing so.[Hobson et al.; Nielsen; Solms; Vertes & Eastman]

Vigilance states, EEG spectra, and cortical temperature in the guinea pig

1993 ◽  
Vol 264 (6) ◽  
pp. R1125-R1132 ◽  
Author(s):  
I. Tobler ◽  
P. Franken ◽  
K. Jaggi
Keyword(s):  
Guinea Pig ◽  
Rem Sleep ◽  
Guinea Pigs ◽  
Process Model ◽  
Dark Period ◽  
Nrem Sleep ◽  
Light Period ◽  
Recording Time ◽  
Cortical Temperature ◽  
Eeg Power

Vigilance states, electroencephalogram (EEG) power spectra (0.25-25.0 Hz), and cortical temperature (TCRT) were obtained in nine guinea pigs for 24 h in a 12:12-h light-dark (LD 12:12) schedule. Sleep was markedly polyphasic and fragmented and amounted to 32% of recording time, which is a low value compared with sleep in other rodents. There was 6.8% more sleep in the light period than in the dark period. EEG power density in non-rapid eye movement (NREM) sleep showed no significant temporal trend within the light or the dark period. The homeostatic aspects of sleep regulation, as proposed in the two-process model, can account for the slow-wave activity (SWA) pattern also in the guinea pig: The small 24-h amplitude of the sleep-wakefulness pattern resulted in a small, 12% decline of SWA within the light period. In contrast to more distinctly nocturnal rodents, SWA in the dark period was not higher than in the light period. TCRT showed no difference between the light and the dark period. TCRT in REM sleep and waking was higher than TCRT in NREM sleep. TCRT increased after the transition from NREM sleep to either REM sleep or waking, and decreased in the last minute before the transition and after the transition from waking to NREM sleep. Motor activity measured in six animals for 11 days in constant darkness showed no apparent rhythm in three animals and a significant circadian rhythm in three others. Our data support the notion that guinea pigs exhibit only a weak circadian rest-activity rhythm.

scholarly journals Dream Generation and Recall in Daytime NREM Sleep of Patients With Narcolepsy Type 1

2020 ◽  
Vol 14 ◽  
Author(s):  
Carlo Cipolli ◽  
Fabio Pizza ◽  
Claudia Bellucci ◽  
Michela Mazzetti ◽  
Giovanni Tuozzi ◽  
...  
Keyword(s):  
Cognitive Processes ◽  
Rem Sleep ◽  
Healthy Subjects ◽  
Structural Organization ◽  
Sleep Onset ◽  
Negative Attitude ◽  
Nrem Sleep ◽  
The Difference ◽  
Multiple Sleep Latency

The less rigid architecture of sleep in patients with narcolepsy type 1 (NT1) compared with healthy subjects may provide new insights into some unresolved issues of dream experience (DE), under the assumption that their DE frequencies are comparable. The multiple transition from wakefulness to REM sleep (sleep onset REM period: SOREMP) during the five trials of the Multiple Sleep Latency Test (MSLT) appears of particular interest. In MSLT studies, NT1 patients reported a DE after about 80% of SOREMP naps (as often as after nighttime REM sleep of themselves and healthy subjects), but only after about 30% of NREM naps compared to 60% of daytime and nighttime NREM sleep of healthy subjects. To estimate accurately the “real” DE frequency, we asked participants to report DE (“dream”) after each MSLT nap and, in case of failure, to specify if they were unable to retrieve any content (“white dream”) or DE did not occur (“no-dream”). The proportions of dreams, white dreams, and no dreams and the indicators of structural organization of DEs reported after NREM naps by 17 adult NT1 patients were compared with those reported by 25 subjects with subjective complaints of excessive daytime sleepiness (sc-EDS), who take multiple daytime NREM naps. Findings were consistent with the hypothesis of a failure in recall after awakening rather than in generation during sleep: white dreams were more frequent in NT1 patients than in sc-EDS subjects (42.86 vs 17.64%), while their frequency of dreams plus white dreams were similar (67.86 and 61.78%) and comparable with that of NREM-DEs in healthy subjects. The longer and more complex NREM-DEs of NT1 patients compared with sc-EDS subjects suggest that the difficulty in DE reporting depends on their negative attitude toward recall of contents less vivid and bizarre than those they usually retrieve after daytime SOREMP and nighttime REM sleep. As this attitude may be reversed by some recall training before MSLT, collecting wider amounts of DE reports after NREM naps would cast light on both the across-stage continuity in the functioning of cognitive processes underlying DE and the difference in content and structural organization of SOREM-DEs preceded by N1 or also N2 sleep.

Embodying algorithms, enactive artificial intelligence and the extended cognition: You can see as much as you know about algorithm

2021 ◽  
pp. 016555152098549
Author(s):  
Donghee Shin
Keyword(s):  
Artificial Intelligence ◽  
Embodied Cognition ◽  
Cognitive Processes ◽  
Process Model ◽  
Extended Cognition ◽  
Dual Process ◽  
Personalized Recommendation ◽  
Normative Values ◽  
And Performance ◽  
Concise Guide

The recent proliferation of artificial intelligence (AI) gives rise to questions on how users interact with AI services and how algorithms embody the values of users. Despite the surging popularity of AI, how users evaluate algorithms, how people perceive algorithmic decisions, and how they relate to algorithmic functions remain largely unexplored. Invoking the idea of embodied cognition, we characterize core constructs of algorithms that drive the value of embodiment and conceptualizes these factors in reference to trust by examining how they influence the user experience of personalized recommendation algorithms. The findings elucidate the embodied cognitive processes involved in reasoning algorithmic characteristics – fairness, accountability, transparency, and explainability – with regard to their fundamental linkages with trust and ensuing behaviors. Users use a dual-process model, whereby a sense of trust built on a combination of normative values and performance-related qualities of algorithms. Embodied algorithmic characteristics are significantly linked to trust and performance expectancy. Heuristic and systematic processes through embodied cognition provide a concise guide to its conceptualization of AI experiences and interaction. The identified user cognitive processes provide information on a user’s cognitive functioning and patterns of behavior as well as a basis for subsequent metacognitive processes.

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 Shining a Light on the Mechanisms of Sleep for Memory Consolidation

2021 ◽  
Author(s):  
Michelle A. Frazer ◽  
Yesenia Cabrera ◽  
Rockelle S. Guthrie ◽  
Gina R. Poe
Keyword(s):  
Rem Sleep ◽  
Neural Activity ◽  
Memory Consolidation ◽  
Strong Support ◽  
Nrem Sleep ◽  
Future Research ◽  
Sleep Spindles ◽  
Slow Oscillations ◽  
Theta Waves ◽  
Learning Tasks

Abstract Purpose of review This paper reviews all optogenetic studies that directly test various sleep states, traits, and circuit-level activity profiles for the consolidation of different learning tasks. Recent findings Inhibiting or exciting neurons involved either in the production of sleep states or in the encoding and consolidation of memories reveals sleep states and traits that are essential for memory. REM sleep, NREM sleep, and the N2 transition to REM (characterized by sleep spindles) are integral to memory consolidation. Neural activity during sharp-wave ripples, slow oscillations, theta waves, and spindles are the mediators of this process. Summary These studies lend strong support to the hypothesis that sleep is essential to the consolidation of memories from the hippocampus and the consolidation of motor learning which does not necessarily involve the hippocampus. Future research can further probe the types of memory dependent on sleep-related traits and on the neurotransmitters and neuromodulators required.

scholarly journals The relationship between fasting-induced torpor, sleep and waking in laboratory mice

SLEEP ◽  
2021 ◽  
Author(s):  
Yi-Ge Huang ◽  
Sarah J Flaherty ◽  
Carina A Pothecary ◽  
Russell G Foster ◽  
Stuart N Peirson ◽  
...  
Keyword(s):  
Body Temperature ◽  
Rem Sleep ◽  
Brain Activity ◽  
Mammalian Species ◽  
Nrem Sleep ◽  
Laboratory Mice ◽  
State Classification ◽  
Metabolic Suppression ◽  
The Relationship ◽  
Electroencephalogram Eeg

Abstract Study objectives Torpor is a regulated and reversible state of metabolic suppression used by many mammalian species to conserve energy. Whereas the relationship between torpor and sleep has been well-studied in seasonal hibernators, less is known about the effects of fasting-induced torpor on states of vigilance and brain activity in laboratory mice. Methods Continuous monitoring of electroencephalogram (EEG), electromyogram (EMG) and surface body temperature was undertaken in adult, male C57BL/6 mice over consecutive days of scheduled restricted feeding. Results All animals showed bouts of hypothermia that became progressively deeper and longer as fasting progressed. EEG and EMG were markedly affected by hypothermia, although the typical electrophysiological signatures of NREM sleep, REM sleep and wakefulness enabled us to perform vigilance-state classification in all cases. Consistent with previous studies, hypothermic bouts were initiated from a state indistinguishable from NREM sleep, with EEG power decreasing gradually in parallel with decreasing surface body temperature. During deep hypothermia, REM sleep was largely abolished, and we observed shivering-associated intense bursts of muscle activity. Conclusions Our study highlights important similarities between EEG signatures of fasting-induced torpor in mice, daily torpor in Djungarian hamsters and hibernation in seasonally-hibernating species. Future studies are necessary to clarify the effects on fasting-induced torpor on subsequent sleep.

scholarly journals Development of training method for vessel traffic service based on cognitive process

2021 ◽  
Author(s):  
Binbing Song ◽  
Hiroko Itoh ◽  
Yasumi Kawamura
Keyword(s):  
Cognitive Processes ◽  
Cognitive Process ◽  
Process Model ◽  
Situational Awareness ◽  
International Association ◽  
Tokyo Bay ◽  
Training Methods ◽  
Training Method ◽  
Oral Transmission ◽  
Maritime Traffic

AbstractVessel traffic service (VTS) is important to protect the safety of maritime traffic. Along with the expansion of monitoring area per VTS operator in Tokyo Bay, Japan, inexperienced operators must acquire the ability to quickly and accurately detect conditions that requires attention (CRAs) from a monitoring screen. In our previous study (Song B, Itoh H, Kawamura Y, Fukuto J (2018) Analysis of Cognitive Processes of Operators of Vessel Traffic Service. In: Proceedings of the 2018 International Association of Institutes of Navigation. IAIN 2018, pp 529–534, Song et al., J Jpn Inst Navig 140:48–54, 2019), we established a task analysis method based on the assumption that the cognitive process model consists of three stages: “situational awareness”, “situation judgment”, and “decision making”. A simulation experiment was conducted for VTS operators with different levels of ability and their cognitive processes were compared based on the observation of eye movements. The results showed that the inexperienced operators’ abilities to predict situation changes were lower. And it was considered that oral transmission of the knowledge is difficult, thus new training methods are needed to help the inexperienced operators to understand the prediction methods of experienced operators. In this study, based on the cognitive process of an experienced operator, we analyzed the prediction procedures of situation changes and developed an educational tool called vessel traffic routine (VTR). The training method learning VTR aims to quickly improve inexperienced VTS operators’ abilities to predict situation changes. A simulation verification experiment of the VTR effect was conducted for four inexperienced operators, who were divided into two groups with and without prior explanation of VTR. By evaluating the cognitive processes of inexperienced operators, it was confirmed that those given prior explanations of VTR were better at detecting CRAs.

Heterogeneous activity level of jaw-closing and -opening muscles and its association with arousal levels during sleep in the guinea pig

2010 ◽  
Vol 298 (1) ◽  
pp. R34-R42 ◽  
Author(s):  
Takafumi Kato ◽  
Yuji Masuda ◽  
Hayato Kanayama ◽  
Norimasa Nakamura ◽  
Atsushi Yoshida ◽  
...  
Keyword(s):  
Heart Rate ◽  
Eye Movement ◽  
Rem Sleep ◽  
Muscle Activity ◽  
Guinea Pigs ◽  
Nrem Sleep ◽  
Activity Level ◽  
Jaw Muscles ◽  
High Activity Level ◽  
Motor Activities

Exaggerated jaw motor activities during sleep are associated with muscle symptoms in the jaw-closing rather than the jaw-opening muscles. The intrinsic activity of antagonistic jaw muscles during sleep remains unknown. This study aims to assess the balance of muscle activity between masseter (MA) and digastric (DG) muscles during sleep in guinea pigs. Electroencephalogram (EEG), electroocculogram, and electromyograms (EMGs) of dorsal neck, MA, and DG muscles were recorded with video during sleep-wake cycles. These variables were quantified for each 10-s epoch. The magnitude of muscle activity during sleep in relation to mean EMG activity of total wakefulness was up to three times higher for MA muscle than for DG muscle for nonrapid eye movement (NREM) and rapid-eye-movement (REM) sleep. Although the activity level of the two jaw muscles fluctuated during sleep, the ratio of activity level for each epoch was not proportional. Epochs with a high activity level for each muscle were associated with a decrease in δEEG power and/or an increase in heart rate in NREM sleep. However, this association with heart rate and activity levels was not observed in REM sleep. These results suggest that in guinea pigs, the magnitude of muscle activity for antagonistic jaw muscles is heterogeneously modulated during sleep, characterized by a high activity level in the jaw-closing muscle. Fluctuations in the activity are influenced by transient arousal levels in NREM sleep but, in REM sleep, the distinct controls may contribute to the fluctuation. The above intrinsic characteristics could underlie the exaggeration of jaw motor activities during sleep (e.g., sleep bruxism).

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)

Sleep Disorders

2015 ◽  
Author(s):  
Sudhansu Chokroverty
Keyword(s):  
Sleep Apnea ◽  
Sleep Disorders ◽  
Eye Movement ◽  
Rem Sleep ◽  
Sleep Apnea Syndrome ◽  
Nrem Sleep ◽  
Rapid Eye Movement ◽  
Circadian Rhythm Sleep Disorders ◽  
Apnea Syndrome ◽  
Sleep Mechanism

Recent research has generated an enormous fund of knowledge about the neurobiology of sleep and wakefulness. Sleeping and waking brain circuits can now be studied by sophisticated neuroimaging techniques that map different areas of the brain during different sleep states and stages. Although the exact biologic functions of sleep are not known, sleep is essential, and sleep deprivation leads to impaired attention and decreased performance. Sleep is also believed to have restorative, conservative, adaptive, thermoregulatory, and consolidative functions. This review discusses the physiology of sleep, including its two independent states, rapid eye movement (REM) and non–rapid eye movement (NREM) sleep, as well as functional neuroanatomy, physiologic changes during sleep, and circadian rhythms. The classification and diagnosis of sleep disorders are discussed generally. The diagnosis and treatment of the following disorders are described: obstructive sleep apnea syndrome, narcolepsy-cataplexy sydrome, idiopathic hypersomnia, restless legs syndrome (RLS) and periodic limb movements in sleep, circadian rhythm sleep disorders, insomnias, nocturnal frontal lobe epilepsy, and parasomnias. Sleep-related movement disorders and the relationship between sleep and psychiatric disorders are also discussed. Tables describe behavioral and physiologic characteristics of states of awareness, the international classification of sleep disorders, common sleep complaints, comorbid insomnia disorders, causes of excessive daytime somnolence, laboratory tests to assess sleep disorders, essential diagnostic criteria for RLS and Willis-Ekbom disease, and drug therapy for insomnia. Figures include polysomnographic recording showing wakefulness in an adult; stage 1, 2, and 3 NREM sleep in an adult; REM sleep in an adult; a patient with sleep apnea syndrome; a patient with Cheyne-Stokes breathing; a patient with RLS; and a patient with dream-enacting behavior; schematic sagittal section of the brainstem of the cat; schematic diagram of the McCarley-Hobson model of REM sleep mechanism; the Lu-Saper “flip-flop” model; the Luppi model to explain REM sleep mechanism; and a wrist actigraph from a man with bipolar disorder. This review contains 14 highly rendered figures, 8 tables, 115 references, and 5 MCQs.

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