EEG Signal Diversity Varies With Sleep Stage and Aspects of Dream Experience

Several theories link consciousness to complex cortical dynamics, as suggested by comparison of brain signal diversity between conscious states and states where consciousness is lost or reduced. In particular, Lempel-Ziv complexity, amplitude coalition entropy and synchrony coalition entropy distinguish wakefulness and REM sleep from deep sleep and anesthesia, and are elevated in psychedelic states, reported to increase the range and vividness of conscious contents. Some studies have even found correlations between complexity measures and facets of self-reported experience. As suggested by integrated information theory and the entropic brain hypothesis, measures of differentiation and signal diversity may therefore be measurable correlates of consciousness and phenomenological richness. Inspired by these ideas, we tested three hypotheses about EEG signal diversity related to sleep and dreaming. First, diversity should decrease with successively deeper stages of non-REM sleep. Second, signal diversity within the same sleep stage should be higher for periods of dreaming vs. non-dreaming. Third, specific aspects of dream contents should correlate with signal diversity in corresponding cortical regions. We employed a repeated awakening paradigm in sleep deprived healthy volunteers, with immediate dream report and rating of dream content along a thought-perceptual axis, from exclusively thought-like to exclusively perceptual. Generalized linear mixed models were used to assess how signal diversity varied with sleep stage, dreaming and thought-perceptual rating. Signal diversity decreased with sleep depth, but was not significantly different between dreaming and non-dreaming, even though there was a significant positive correlation between Lempel-Ziv complexity of EEG recorded over the posterior cortex and thought-perceptual ratings of dream contents.

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Complexity Measures of Brain Electrophysiological Activity

Journal of Psychophysiology ◽

10.1027/0269-8803/a000024 ◽

2010 ◽

Vol 24 (2) ◽

pp. 131-135 ◽

Cited By ~ 5

Author(s):

Włodzimierz Klonowski ◽

Pawel Stepien ◽

Robert Stepien

Keyword(s):

Brain Activity ◽

Deterministic Chaos ◽

Epileptic Seizures ◽

Eeg Signal ◽

Eeg Signals ◽

Complexity Measures ◽

Electrophysiological Activity ◽

Signal Complexity ◽

Physiological Sleep ◽

The Brain

Over 20 years ago, Watt and Hameroff (1987 ) suggested that consciousness may be described as a manifestation of deterministic chaos in the brain/mind. To analyze EEG-signal complexity, we used Higuchi’s fractal dimension in time domain and symbolic analysis methods. Our results of analysis of EEG-signals under anesthesia, during physiological sleep, and during epileptic seizures lead to a conclusion similar to that of Watt and Hameroff: Brain activity, measured by complexity of the EEG-signal, diminishes (becomes less chaotic) when consciousness is being “switched off”. So, consciousness may be described as a manifestation of deterministic chaos in the brain/mind.

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Informativeness of Auditory Stimuli Does Not Affect EEG Signal Diversity

Frontiers in Psychology ◽

10.3389/fpsyg.2018.01820 ◽

2018 ◽

Vol 9 ◽

Author(s):

Michał Bola ◽

Paweł Orłowski ◽

Karolina Baranowska ◽

Michael Schartner ◽

Artur Marchewka

Keyword(s):

Auditory Stimuli ◽

Eeg Signal ◽

Signal Diversity

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Classification of Sleep Stages Using Multi-wavelet Time Frequency Entropy and LDA

Methods of Information in Medicine ◽

10.3414/me09-01-0054 ◽

2010 ◽

Vol 49 (03) ◽

pp. 230-237 ◽

Cited By ~ 44

Author(s):

K. Lweesy ◽

N. Khasawneh ◽

M. Fraiwan ◽

H. Wenz ◽

H. Dickhaus ◽

...

Keyword(s):

Feature Extraction ◽

Wavelet Transform ◽

Discriminant Analysis ◽

Sleep Stage ◽

Continuous Wavelet ◽

Eeg Signal ◽

Linear Discriminant ◽

Time Frequency ◽

Mother Wavelets ◽

Sleep Stage Scoring

Summary Background: The process of automatic sleep stage scoring consists of two major parts: feature extraction and classification. Features are normally extracted from the polysomno-graphic recordings, mainly electroencephalograph (EEG) signals. The EEG is considered a non-stationary signal which increases the complexity of the detection of different waves in it. Objectives: This work presents a new technique for automatic sleep stage scoring based on employing continuous wavelet transform (CWT) and linear discriminant analysis (LDA) using different mother wavelets to detect different waves embedded in the EEG signal. Methods: The use of different mother wave-lets increases the ability to detect waves in the EEG signal. The extracted features were formed based on CWT time frequency entropy using three mother wavelets, and the classification was performed using the linear discriminant analysis. Thirty-two data sets from the MIT-BIH database were used to evaluate the performance of the proposed method. Results: Features of a single EEG signal were extracted successfully based on the time frequency entropy using the continuous wavelet transform with three mother wavelets. The proposed method has shown to outperform the classification based on a CWT using a single mother wavelet. The accuracy was found to be 0.84, while the kappa coefficient was 0.78. Conclusions: This work has shown that wavelet time frequency entropy provides a powerful tool for feature extraction for the non-stationary EEG signal; the accuracy of the classification procedure improved when using multiple wavelets compared to the use of single wavelet time frequency entropy.

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Distributed context-dependent choice information in mouse dorsal-parietal cortex

10.21203/rs.3.rs-288103/v1 ◽

2021 ◽

Author(s):

Javier Orlandi ◽

Mohammad Adbolrahmani ◽

Ryo Aoki ◽

Dmitry Lyamzin ◽

Andrea Benucci

Keyword(s):

Decision Making ◽

Decision Variable ◽

Visual Stream ◽

Posterior Cortex ◽

Neural Data ◽

Context Dependent ◽

Cortical Regions ◽

Low Dimensional ◽

Independent Decision ◽

The Brain

Abstract Choice information appears in the brain as distributed signals with top-down and bottom-up components that together support decision-making computations. In sensory and associative cortical regions, the presence of choice signals, their strength, and area specificity are known to be elusive and changeable, limiting a cohesive understanding of their computational significance. In this study, examining the mesoscale activity in mouse posterior cortex during a complex visual discrimination task, we found that broadly distributed choice signals defined a decision variable in a low-dimensional embedding space of multi-area activations, particularly along the ventral visual stream. The subspace they defined was near-orthogonal to concurrently represented sensory and motor-related activations, and it was modulated by task difficulty and contextually by the animals’ attention state. To mechanistically relate choice representations to decision-making computations, we trained recurrent neural networks with the animals’ choices and found an equivalent decision variable whose context-dependent dynamics agreed with that of the neural data. In conclusion, our results demonstrated an independent decision variable broadly represented in the posterior cortex, controlled by task features and cognitive demands. Its dynamics reflected decision computations, possibly linked to context-dependent feedback signals used for probabilistic-inference computations in variable animal-environment interactions.

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Increased signal diversity/complexity of spontaneous EEG, but not evoked EEG responses, in ketamine-induced psychedelic state in humans

10.1101/508697 ◽

2019 ◽

Cited By ~ 2

Author(s):

Nadine Farnes ◽

Bjørn E. Juel ◽

André S. Nilsen ◽

Luis G. Romundstad ◽

Johan F. Storm

Keyword(s):

Brain Activity ◽

Altered States Of Consciousness ◽

Altered States ◽

Eeg Signal ◽

Eyes Closed ◽

Electrical Brain Activity ◽

States Of Consciousness ◽

Significant Difference ◽

Eyes Open ◽

Signal Diversity

AbstractObjectiveHow and to what extent electrical brain activity is affected in pharmacologically altered states of consciousness, where it is mainly the phenomenological content rather than the level of consciousness that is altered, is not well understood. An example is the moderately psychedelic state caused by low doses of ketamine. Therefore, we investigated whether and how measures of evoked and spontaneous electroencephalographic (EEG) signal diversity are altered by sub-anaesthetic levels of ketamine compared to normal wakefulness, and how these measures relate to subjective assessments of consciousness.MethodsHigh-density electroencephalography (EEG, 62 channels) was used to record spontaneous brain activity and responses evoked by transcranial magnetic stimulation (TMS) in 10 healthy volunteers before and after administration of sub-anaesthetic doses of ketamine in an open-label within-subject design. Evoked signal diversity was assessed using the perturbational complexity index (PCI), calculated from the global EEG responses to local TMS perturbations. Signal diversity of spontaneous EEG, with eyes open and eyes closed, was assessed by Lempel Ziv complexity (LZc), amplitude coalition entropy (ACE), and synchrony coalition entropy (SCE).ResultsAlthough no significant difference was found in the index of TMS-evoked complexity (PCI) between the sub-anaesthetic ketamine condition and normal wakefulness, all the three measures of spontaneous EEG signal diversity showed significantly increased values in the sub-anaesthetic ketamine condition. This increase in signal diversity also correlated with subjective assessment of altered states of consciousness. Moreover, spontaneous signal diversity was significantly higher when participants had eyes open compared to eyes closed, both during normal wakefulness and during influence of sub-anaesthetic ketamine doses.ConclusionThe results suggest that PCI and spontaneous signal diversity may be complementary and potentially measure different aspects of consciousness. Thus, our results seem compatible with PCI being indicative of the brain’s ability to sustain consciousness, as indicated by previous research, while it is possible that spontaneous EEG signal diversity may be indicative of the complexity of conscious content. The observed sensitivity of the latter measures to visual input seems to support such an interpretation. Thus, sub-anaesthetic ketamine may increase the complexity of both the conscious content (experience) and the brain activity underlying it, while the level, degree, or general capacity of consciousness remains largely unaffected.

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A Smart Arduino Alarm Clock Based on NREM and REM Sleep Stage Detection

Mobile Web and Intelligent Information Systems - Lecture Notes in Computer Science ◽

10.1007/978-3-319-44215-0_36 ◽

2016 ◽

pp. 431-442

Author(s):

Adam Drabek ◽

Ondrej Krejcar ◽

Kamil Kuca

Keyword(s):

Rem Sleep ◽

Sleep Stage ◽

Alarm Clock

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Sleep, Subcortical Stimulation and Kindling in the Cat

Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques ◽

10.1017/s031716710002059x ◽

1975 ◽

Vol 2 (4) ◽

pp. 447-455 ◽

Cited By ~ 32

Author(s):

T. Tanaka ◽

H. Lange ◽

R. Naquet

Keyword(s):

Rem Sleep ◽

Sleep Stage ◽

Low Frequency ◽

Mesencephalic Reticular Formation ◽

Seizure Threshold ◽

Sleep Stages ◽

Central Gray Matter ◽

Spike Discharge ◽

Amygdaloid Stimulation ◽

Stimulation Of

SUMMARY:A longitudinal study of the effects of sleep on amygdaloid kindling showed that kindling disrupted normal sleep patterns by reducing REM sleep and increasing awake time. Few interictal spike discharges were observed during the awake stage, while a marked increase in discharge was observed during the light and deep sleep stages. No discharges were observed during REM sleep. During the immediate post-stimulation period the nonstimulated amygdala showed a much higher rate of spike discharge. On the other hand, there was an increase in spike discharge in the stimulated amygdala during natural sleep without preceding amygdaloid stimulation. Amygdaloid stimulation at the generalized seizure threshold during each sleep stage resulted in a generalized convulsion.The influence of subcortical electrical stimulation on kindled amygdaloid convulsions was investigated in a second experiment. Stimulation of the centre median and the caudate nucleus was without effect on kindled convulsions, while stimulation of the mesencephalic reticular formation at high frequency (300 Hz) reduced the latency of onset of kindled generalized convulsions. Stimulation of the nucleus ventralis lateralis of the thalamus at low frequency (10 Hz) prolonged the convulsion latency, and at high current levels blocked the induced convulsion. Stimulation in the central gray matter at low frequency (10 Hz) also blocked kindled amygdaloid convulsions.

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REM sleep behavior disorder in children with type 1 Narcolepsy treated with Sodium Oxybate

Neurology ◽

10.1212/wnl.0000000000011157 ◽

2020 ◽

pp. 10.1212/WNL.0000000000011157

Author(s):

Elena Antelmi ◽

Marco Filardi ◽

Fabio Pizza ◽

Stefano Vandi ◽

Monica Moresco ◽

...

Keyword(s):

Rem Sleep ◽

Sleep Stage ◽

Rem Sleep Behavior Disorder ◽

Behavior Disorder ◽

Sodium Oxybate ◽

Direct Role ◽

Sleep Behavior ◽

Rem Sleep Without Atonia ◽

Nighttime Sleep

Objective:The aim was to study the effect of stable treatment with Sodium Oxybate (SO) on nocturnal REM sleep behavior disorder (RBD) and REM sleep without atonia (RSWA) that severely affected children with type 1 narcolepsy (NT1.Methods:Nineteen NT1 children and adolescents (nine females; mean age 12.5±2.7, mean disease duration: 3.4±1.6 years) underwent neurological investigations and video-polysomnography (v-PSG) at baseline and after three months of stable treatment with SO.v-PSG was independently analysed by two sleep experts, in order to rate RBD episodes. RSWA was automatically computed by means of the validated REM sleep atonia index (RAI).Results:Compared to baseline, RAI significantly improved (p< 0.05) and complex movements during REM sleep were remarkably reduced after stable treatment with SO. Compared to baseline, children also reported improvement in clinical complaints and showed a different nighttime sleep stage architecture.Conclusions:RBD and RSWA improved after treatment with SO, pointing to a direct role of the drug in modulating motor control during REM sleep.

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