Characterization of sleep spindles using higher order statistics and spectra

Cataloged from PDF version of article.This work characterizes the dynamics of sleep spindles, observed in electroencephalogram (EEG) recorded from humans during sleep, using both time and frequency domain methods which depend on higher order statistics and spectra. The time domain method combines the use of second- and third-order correlations to reveal information on the stationarity of periodic spindle rhythms to detect transitions between multiple activities. The frequency domain method, based on normalized spectrum and bispectrum, describes frequency interactions associated with nonlinearities occuring in the observed EEG

The spatiotemporal pattern of the human electroencephalogram at sleep onset after a period of prolonged wakefulness

During the sleep onset (SO) process, the human electroencephalogram (EEG) is characterized by an orchestrated pattern of spatiotemporal changes. Sleep deprivation (SD) strongly affects both wake and sleep EEG, but a description of the topographical EEG power spectra and oscillatory activity during the wake-sleep transition after a period of prolonged wakefulness is still missing. The increased homeostatic sleep pressure should induce an earlier onset of sleep-related EEG oscillations. The aim of the present study was to assess the spatiotemporal EEG pattern at SO following SD. A dataset of a previous study was analyzed. We assessed the spatiotemporal EEG changes (19 cortical derivations) during the SO (5 min before vs. 5 min after the first epoch of Stage 2) of a recovery night after 40 h of SD in 39 healthy subjects, analyzing the EEG power spectra (fast Fourier transform) and the oscillatory activity [better oscillation (BOSC) detection method]. The spatiotemporal pattern of the EEG power spectra mostly confirmed the changes previously observed during the wake-sleep transition at baseline. The comparison between baseline and recovery showed a wide increase of the post- vs. pre-SO ratio during the recovery night in the frequency bins 10 Hz. We found a predominant alpha oscillatory rhythm in the pre-SO period, while after SO the theta oscillatory activity was prevalent. The oscillatory peaks showed a generalized increase in all frequency bands from delta to sigma with different predominance, while beta activity increased only in the fronto-central midline derivations. Overall, the analysis of the EEG power replicated the topographical pattern observed during a baseline night of sleep but with a stronger intensity of the SO-induced changes in the frequencies 10 Hz, and the detection of the rhythmic activity showed the rise of several oscillations at SO after SD that was not observed during the wake-sleep transition at baseline (e.g., alpha and frontal theta in correspondence of their frequency peaks). Beyond confirming the local nature of the EEG pattern at SO, our results show that SD has an impact on the spatiotemporal modulation of cortical activity during the falling-asleep process, inducing the earlier emergence of sleep-related EEG oscillations

Computerized scoring of sleep stage data

Sleep is a non-uniform biological state which has been subdivided into different stages. The basic criteria behind staging are the amplitude and frequency variations of sleep data. The sleep analysis is carried out by considering the characteristic variation of all three EEG, EOG and EMG signals. The polygraphic recording of nocturnal sleep is a method of research widely used in neurophysiology laboratories, both for the clinical study of sleep and for the evaluation of the therapeutic effectiveness of drugs acting on sleep. The analysis of this method is carried out by an expert individual whose depth of knowledge regarding the normal pattern of waveforms and the set of criteria used for staging reflects on the outcome of the analysis. With this approach there are always discrepancies among the individual \u27scorers with respect to the method applied and as well as criteria considered. Visual analysis of the EEG remains necessary and appropriate, but it is time consuming and lacks quantification. The alternative would be to develop an Computerized System for scoring the sleep stage data. Over these years automatic scoring of sleep stage data has promised increased understanding of pathological as well as normal sleep patterns. Computerized systems also act as an essential tool in describing the sleep process and to reflect the dynamic organization of human sleep. The objective of the present work is to develop a Computerized System with an efficient algorithm to score the sleep stage data based on multiple set of criteria. The outcome of this study is then compared with the Visual Scoring data to find out the percentage of agreement between the human scorer and the computer algorithm

Infraslow oscillations in human sleep spindle activity

Background: It has previously been reported that EEG sigma (10-15 Hz) activity during sleep exhibits infraslow oscillations (ISO) with a period of 50 seconds. However, a detailed analysis of the ISO of individually identified sleep spindles is not available. New Method: We investigated basic properties of ISO during baseline sleep of 34 healthy young human participants using a new and established methods. The analyses focused on fast sleep spindle and sigma activity (13-15 Hz) in NREM stage 2 and slow wave sleep (SWS). To describe ISO in sigma activity we analysed power of power of the EEG signal. For the study of ISO in sleep spindle activity we applied a new method in which the EEG signal was reduced to a spindle on/off binary square signal. Its spectral properties were contrasted to that of a square signal wherein the same spindles and also the inter spindle intervals were permutated randomly. This approach was validated using surrogate data with imposed ISO modulation. Results: We confirm the existence of ISO in sigma activity albeit with a frequency below the previously reported 0.02 Hz. These ISO are most prominent in the high sigma band and over the centro-parieto-occipital regions. A similar modulation is present in spindle activity. ISO in sleep spindles are most prominent in the centro-parieto-occipital regions, left hemisphere and second half of the night independent of the number of spindles. Conclusions: The comparison of spectral properties of binary event signals and permutated event signals is effective in detecting slow oscillatory phenomena

Heterogeneous profiles of coupled sleep oscillations in human hippocampus

Cross-frequency coupling of sleep oscillations is thought to mediate memory consolidation. While the hippocampus is deemed central to this process, detailed knowledge of which oscillatory rhythms interact in the sleeping human hippocampus is lacking. Combining intracranial hippocampal and non-invasive electroencephalography from twelve neurosurgical patients, we characterized spectral power and coupling during non-rapid eye movement (NREM) and rapid eye movement (REM) sleep. Hippocampal coupling was extensive, with the majority of channels expressing spectral interactions. NREM consistently showed delta–ripple coupling, but ripples were also modulated by slow oscillations (SOs) and sleep spindles. SO–delta and SO–theta coupling, as well as interactions between delta/theta and spindle/beta frequencies also occurred. During REM, limited interactions between delta/theta and beta frequencies emerged. Moreover, oscillatory organization differed substantially between i) hippocampus and scalp, ii) sites along the anterior-posterior hippocampal axis, and iii) individuals. Overall, these results extend and refine our understanding of hippocampal sleep oscillations

Oscillatory patterns in the electroencephalogram at sleep onset

Falling asleep is a gradually unfolding process. We investigated the role of various oscillatory activities including sleep spindles and alpha and delta oscillations at sleep onset (SO) by automatically detecting oscillatory events. We used two datasets of healthy young males, eight with four baseline recordings, and eight with a baseline and recovery sleep after 40 h of sustained wakefulness. We analyzed the 2-min interval before SO (stage 2) and the five consecutive 2-min intervals after SO. The incidence of delta/theta events reached its maximum in the first 2-min episode after SO, while the frequency of them was continuously decreasing from stage 1 onwards, continuing over SO and further into deeper sleep. Interestingly, this decrease of the frequencies of the oscillations were not affected by increased sleep pressure, in contrast to the incidence which increased. We observed an increasing number of alpha events after SO, predominantly frontally, with their prevalence varying strongly across individuals. Sleep spindles started to occur after SO, with first an increasing then a decreasing incidence and a continuous decrease in their frequency. Again, the frequency of the spindles was not altered after sleep deprivation. Oscillatory events revealed derivation dependent aspects. However, these regional aspects were not specific of the process of SO but rather reflect a general sleep related phenomenon. No individual traits of SO features (incidence and frequency of oscillations) and their dynamics were observed. Delta/theta events are important features for the analysis of SO in addition to slow waves

Cortical and subcortical speech-evoked responses in young and older adults: Effects of background noise, arousal states, and neural excitability

This thesis investigated how the brain processes speech signals in human adults across a wide age-range in the sensory auditory systems using electroencephalography (EEG). Two types of speech-evoked phase-locked responses were focused on: (i) cortical responses (theta-band phase-locked responses) that reflect processing of low-frequency slowly-varying envelopes of speech; (ii) subcortical/peripheral responses (frequency-following responses; FFRs) that reflect encoding of speech periodicity and temporal fine structure information. The aims are to elucidate how these neural activities are affected by different internal (aging, hearing loss, level of arousal and neural excitability) and external (background noise) factors during our daily life through three studies. Study 1 investigated theta-band phase-locking and FFRs in noisy environments in young and older adults. It investigated how aging and hearing loss affect these activities under quiet and noisy environments, and how these activities are associated with speech-in-noise perception. The results showed that ageing and hearing loss affect speech-evoked phase-locked responses through different mechanisms, and the effects of aging on cortical and subcortical activities take different roles in speech-in-noise perception. Study 2 investigated how level of arousal, or consciousness, affects phase-locked responses in young and older adults. The results showed that both theta-band phase-locking and FFRs decreases following decreases in the level of arousal. It was further found that neuro-regulatory role of sleep spindles on theta-band phase-locking is distinct between young and older adults, indicating that the mechanisms of neuro-regulation for phase-locked responses in different arousal states are age-dependent. Study 3 established a causal relationship between the auditory cortical excitability and FFRs using combined transcranial direct current stimulation (tDCS) and EEG. FFRs were measured before and after tDCS was applied over the auditory cortices. The results showed that changes in neural excitability of the right auditory cortex can alter FFR magnitudes along the contralateral pathway. This shows important theoretical and clinical implications that causally link functions of auditory cortex with neural encoding of speech periodicity. Taken together, findings of this thesis will advance our understanding of how speech signals are processed via neural phase-locking in our everyday life across the lifespan