Sleep EEG characteristics associated with total sleep time misperception in young adults

Abstract Backgroud: Power spectral analysis (PSA) is one of the most commonly-used EEG markers of cortical hyperarousal which help to understand subjective-objective sleep discrepancy (SOD). Age is associated with decreased sleep EEG activity. Currently, PSA of young adults are limited. Thus, this study aimed to examine the correlation of spectral EEG power with total sleep time misperception in young patients. Methods : Forty-seven young adults were recruited and underwent a polysomnography recording in a sleep laboratory. The clinical records and self-report questionnaires of all patients were collected, who were categorized into the GS (n=10), insomnias with a low mismatch (IWLM, n=19) and participants with a high mismatch (IWHM, n=18) subgroups. Power spectral analysis was performed during the first 6 hours of sleep. Results : The IWLM group showed increased absolute beta power in central-frontal area and relative beta power in frontal areas compared to the GS group. In addition, IWHM patients exhibited higher absolute and relative beta power in the central area compared to the GS group. The absolute and relative beta/delta ratios in frontal area in the IWHM and IWLM groups were higher than those in the GS group. The IWHM group also showed higher absolute and relative beta/delta ratios in the central area compared with the GS group. No significant difference in the above parameters was observed between the IWHM and IWLM groups. Moreover, the SOD of TST was negatively correlated with the relative delta power (r=0.289, p=0.049), beta power (r=0.373, p=0.010), beta/delta ratio(r= 0.314, p=0.032), and the absolute beta/delta ratio (r=0.314, p=0.032) in central area. Conclusions: Young IWHM and IWLM patients showed increased beta EEG power compared to GS, suggesting that there exists increased cortical activity in these patients. Also, the beta/delta ratio was negatively correlated with the SOD in patients with IWHM and IWLM.

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All-night EEG power spectral analysis of the cyclic alternating pattern components in young adult subjects

Clinical Neurophysiology ◽

10.1016/j.clinph.2005.06.022 ◽

2005 ◽

Vol 116 (10) ◽

pp. 2429-2440 ◽

Cited By ~ 37

Author(s):

Raffaele Ferri ◽

Oliviero Bruni ◽

Silvia Miano ◽

Giuseppe Plazzi ◽

Mario G. Terzano

Keyword(s):

Spectral Analysis ◽

Young Adult ◽

Power Spectral Analysis ◽

Cyclic Alternating Pattern ◽

Power Spectral ◽

Eeg Power

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Assessing traumatic brain injuries using EEG power spectral analysis and instantaneous phase

2012 38th Annual Northeast Bioengineering Conference (NEBEC) ◽

10.1109/nebc.2012.6206935 ◽

2012 ◽

Cited By ~ 1

Author(s):

A. Napoli ◽

K. Darvish ◽

I. Obeid

Keyword(s):

Spectral Analysis ◽

Brain Injuries ◽

Power Spectral Analysis ◽

Traumatic Brain Injuries ◽

Instantaneous Phase ◽

Power Spectral ◽

Eeg Power

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Parametric cortical representations of complexity and preference for artistic and computer-generated fractal patterns revealed by single-trial EEG power spectral analysis

10.31234/osf.io/g3s7r ◽

2021 ◽

Author(s):

Eric Rawls ◽

Rebecca A. White ◽

Stephanie Kane ◽

Carl E. Stevens ◽

Darya Zabelina

Keyword(s):

Spectral Analysis ◽

Fractal Dimension ◽

Power Spectral Analysis ◽

Alpha Band ◽

Single Trial ◽

Power Spectral ◽

Subjective Preference ◽

Fractal Patterns ◽

Fractal Images ◽

Eeg Power

Fractals are self-similar patterns that repeat at different scales, the complexity of which are expressed as a fractional Euclidean dimension D between 0 (a point) and 2 (a filled plane). The drip paintings of American painter Jackson Pollock (JP) are fractal in nature, and Pollock’s most illustrious works are of the high-D (~1.7) category. This would imply that people prefer more complex fractal patterns, but some research has instead suggested people prefer lower-D fractals. Furthermore, research has suggested that parietal and frontal brain activity tracks the complexity of fractal patterns, but previous research has artificially binned fractals depending on fractal dimension, rather than treating fractal dimension as a parametrically varying value. We used white layers extracted from JP artwork as stimuli, and constructed statistically matched 2-dimensional random Cantor sets as control stimuli. We recorded the electroencephalogram (EEG) while participants viewed the JP and matched random Cantor fractal patterns. Participants then rated their subjective preference for each pattern. We used a single-trial analysis to construct within-subject models relating subjective preference to fractal dimension D, as well as relating D and subjective preference to single-trial EEG power spectra. Results indicated that participants preferred higher-D images for both JP and Cantor stimuli. Power spectral analysis showed that, for artistic fractal images, parietal alpha and beta power parametrically tracked complexity of fractal patterns, while for matched mathematical fractals, parietal power tracked complexity of patterns over a range of frequencies, but most prominently in alpha band. Furthermore, parietal alpha power parametrically tracked aesthetic preference for both artistic and matched Cantor patterns. Overall, our results suggest that perception of complexity for artistic and computer-generated fractal images is reflected in parietal-occipital alpha and beta activity, and neural substrates of preference for complex stimuli are reflected in parietal alpha band activity.

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Longitudinal Sleep EEG Power Spectral Analysis Studies in Adolescents with Minor Head Injury

Journal of Neurotrauma ◽

10.1089/neu.1997.14.549 ◽

1997 ◽

Vol 14 (8) ◽

pp. 549-559 ◽

Cited By ~ 28

Author(s):

L.C. PARSONS ◽

L.J. CROSBY ◽

M. PERLIS ◽

T. BRITT ◽

P. JONES

Keyword(s):

Spectral Analysis ◽

Head Injury ◽

Power Spectral Analysis ◽

Sleep Eeg ◽

Minor Head Injury ◽

Power Spectral ◽

Eeg Power

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Assessing traumatic brain injuries using EEG power spectral analysis and instantaneous phase

2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society ◽

10.1109/embc.2012.6347014 ◽

2012 ◽

Cited By ~ 2

Author(s):

A. Napoli ◽

M. Barbe ◽

K. Darvish ◽

I. Obeid

Keyword(s):

Spectral Analysis ◽

Brain Injuries ◽

Power Spectral Analysis ◽

Traumatic Brain Injuries ◽

Instantaneous Phase ◽

Power Spectral ◽

Eeg Power

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EEG Power Spectral Analysis of Abnormal Cortical Activations During REM/NREM Sleep in Obstructive Sleep Apnea

Frontiers in Neurology ◽

10.3389/fneur.2021.643855 ◽

2021 ◽

Vol 12 ◽

Author(s):

Shuling Liu ◽

Jiucheng Shen ◽

Yezhou Li ◽

Jing Wang ◽

Jianhua Wang ◽

...

Keyword(s):

Obstructive Sleep Apnea ◽

Spectral Analysis ◽

Power Spectral Analysis ◽

Nrem Sleep ◽

The Other ◽

Frequency Bands ◽

Delta Band ◽

Power Spectral ◽

Obstructive Sleep ◽

Eeg Power

Objective: To characterize electroencephalogram (EEG) power in different frequency bands during rapid eye movement (REM) sleep and non-rapid eye movement (NREM) sleep in patients with obstructive sleep apnea (OSA).Methods: Retrospective data on 151 patients were collected and divided into three groups: primary snoring group (AHI < 5/h), mild-moderate OSA group (6 ≤ AHI < 30/h), and severe OSA group (AHI ≥ 30/h). EEG recordings in the frontal, central, and occipital regions were extracted from both REM and NREM sleep, to compute the normalized spectral power densities in the delta, theta, alpha, sigma, beta, and gamma frequency bands, using Fast Fourier Transform. Correlations between the computed EEG power and PSG parameters were analyzed.Results: In NREM sleep, elevated normalized power spectral density (PSD) in the delta band was observed in the severe OSA group compared to the other two groups. In contrast, the PSD of the other frequency bands showed a corresponding decrease in the severe OSA group. In REM sleep, similar changes were observed in the frontal region. Delta band PSD was positively correlated with Apnea Hypopnea Index (AHI) (r = 0.33), longest time of apnea, oxygen desaturation index (ODI) (r = 0.34), percent sleep time below 90% SaO2 (T90%) (r = 0.30), Arousal Index (ArI) (r = 0.29), and negatively correlated with N3%, minimum oxygen saturation (minSaO2).Conclusion: Our findings provide neurophysiological evidence for pathological cortical activation during REM/NREM sleep, which may be associated with the arousals and cognitive impairments in OSA. The technique of power spectral analysis could prove a potentially useful tool in complementing traditional PSG parameters in assessing disease burden to guide therapeutic decisions.

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All-night EEG power spectral analysis of the cyclic alternating pattern at different ages

Clinical Neurophysiology ◽

10.1016/j.clinph.2008.11.001 ◽

2009 ◽

Vol 120 (2) ◽

pp. 248-256 ◽

Cited By ~ 8

Author(s):

Oliviero Bruni ◽

Luana Novelli ◽

Elena Finotti ◽

Anna Luchetti ◽

Giordana Uggeri ◽

...

Keyword(s):

Spectral Analysis ◽

Power Spectral Analysis ◽

Cyclic Alternating Pattern ◽

Power Spectral ◽

Different Ages ◽

Eeg Power

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Sleep and EEG Power Spectral Analysis in Three Transgenic Mouse Models of Alzheimer’s Disease: APP/PS1, 3xTgAD, and Tg2576

Journal of Alzheimer s Disease ◽

10.3233/jad-180260 ◽

2018 ◽

Vol 64 (4) ◽

pp. 1325-1336 ◽

Cited By ~ 11

Author(s):

Brianne A. Kent ◽

Stephen M. Strittmatter ◽

Haakon B. Nygaard

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Spectral Analysis ◽

Transgenic Mouse ◽

Mouse Models ◽

Power Spectral Analysis ◽

Transgenic Mouse Models ◽

Power Spectral ◽

Eeg Power

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The Eeg in Antisocial Behaviour: A Study of Borstal Boys

Bulletin of the Royal College of Psychiatrists ◽

10.1192/pb.1.5.7-a ◽

1977 ◽

Vol 1 (5) ◽

pp. 7-8

Author(s):

G. W. Fenton ◽

P. B. C. Fenwick ◽

J. Dollimore ◽

R. Foggitt ◽

R. Nichol

Keyword(s):

Spectral Analysis ◽

Control Sample ◽

Power Spectral Analysis ◽

Structured Interview ◽

Pass Filter ◽

Low Pass Filter ◽

Duration Of Stay ◽

Eyes Closed ◽

Power Spectral ◽

Eeg Power

A sample of borstal boys was selected (56). All had an assessment of mental state and ratings of sociopathy and aggressiveness performed, using structured interview techniques. A group of RAMC apprentices matched for age, sex and social class, was also examined (56). Eight-channel bipolar scalp EEG recordings were taken, 4 channels (T4–T6, P4–O2, T3–T5, P3–O1) being recorded on analogue tape. The tape-recorded signals were filtered off line through a low pass filter, multiplexed and digitized on to magnetic tape. Power spectral analysis was carried out on this data, using the University of London CDC 60 600 computer. Three 30-second epochs were analysed: eyes closed, eyes open, and eyes closed. No significant EEG differences were found between the borstal boys and the control sample. Neither visual inspection nor power spectral analysis revealed any EEG differences between the borstal boys and controls. Correlation coefficients between the power at each frequency from all four channels, the violence and sociopathy ratings and the time spent in institutional care in months for each boy were computed. These showed that violence contributes not more than 1 per cent and sociopathy not more than 5 per cent to the variance of the EEG power. Duration of stay in the institution accounted for as much as 20 per cent of the variance of the EEG power with significant correlations at 7 Hz (positive) and 11 Hz (negative). Duration of stay is thus a variable that must be controlled for during the investigation of subjects in penal institutions and long-stay hospitals.

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