Local and Widespread Slow Waves in Stable NREM Sleep: Evidence for Distinct Regulation Mechanisms

Previous work showed that two types of slow waves are temporally dissociated during the transition to sleep: widespread, large and steep slow waves predominate early in the falling asleep period (type I), while smaller, more circumscribed slow waves become more prevalent later (type II). Here, we studied the possible occurrence of these two types of slow waves in stable non-REM (NREM) sleep and explored potential differences in their regulation. A heuristic approach based on slow wave synchronization efficiency was developed and applied to high-density electroencephalographic (EEG) recordings collected during consolidated NREM sleep to identify the potential type I and type II slow waves. Slow waves with characteristics compatible with those previously described for type I and type II were identified in stable NREM sleep. Importantly, these slow waves underwent opposite changes across the night, with only type II slow waves displaying a clear homeostatic regulation. In addition, we showed that the occurrence of type I slow waves was often followed by larger type II slow waves, whereas the occurrence of type II slow waves was usually followed by smaller type I waves. Finally, type II slow waves were associated with a relative increase in spindle activity, while type I slow waves triggered periods of high-frequency activity. Our results provide evidence for the existence of two distinct slow wave synchronization processes that underlie two different types of slow waves. These slow waves may have different functional roles and mark partially distinct “micro-states” of the sleeping brain.

Sleep spindles, K-complexes, limb movements and sleep stage proportions may be biomarkers for amnestic mild cognitive impairment and Alzheimer's disease

PURPOSE

Sleep disturbances are common in Alzheimer's disease (AD) and mild cognitive impairment (MCI) patients. Non-rapid eye movement stage 3 (N3), rapid eye movement stage (REM), spindle density, and K-complex (KC) density are decreased in MCI and AD patients. Periodic limb movements in sleep (PLMS) are increased in other neurodegenerative diseases. We aimed to distinguish amnestic mild cognitive impairment (aMCI) patients from the overall population of MCI patients by comparing the N3 and REM proportions, the morphological characteristics of spindles and KCs and the periodic limb movement index (PLMI) among control, aMCI and AD subjects.

METHODS

In 92 subjects (30 controls, 32 aMCI and 30 AD), sleep stages, spindles, KCs and PLMS were recorded during the second of two nights of polysomnography (PSG). We compared the above parameters among the three groups.

RESULTS

AD and aMCI subjects had lower proportions of N3 and REM, poorer spindle and KC activities and more frequent PLMS than controls. These alterations were associated with decreased Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) scores. We determined cut-off values for distinguishing aMCI and AD using logistic regression and receiver operating characteristic (ROC) analyses.

CONCLUSIONS

AD and aMCI patients have abnormal sleep stage proportions, spindles, KCs and PLMS. The combination of the above alterations may distinguish aMCI and AD patients from controls with high specificity and sensitivity.

Sleep spindle and K-complex detection using tunable Q-factor wavelet transform and morphological component analysis

A novel framework for joint detection of sleep spindles and K-complex events, two hallmarks of sleep stage S2, is proposed. Sleep electroencephalography (EEG) signals are split into oscillatory (spindles) and transient (K-complex) components. This decomposition is conveniently achieved by applying morphological component analysis (MCA) to a sparse representation of EEG segments obtained by the recently introduced discrete tunable Q-factor wavelet transform (TQWT). Tuning the Q-factor provides a convenient and elegant tool to naturally decompose the signal into an oscillatory and a transient component. The actual detection step relies on thresholding (i) the transient component to reveal K-complexes and (ii) the time-frequency representation of the oscillatory component to identify sleep spindles. Optimal thresholds are derived from ROC-like curves (sensitivity vs. FDR) on training sets and the performance of the method is assessed on test data sets. We assessed the performance of our method using full-night sleep EEG data we collected from 14 participants. In comparison to visual scoring (Expert 1), the proposed method detected spindles with a sensitivity of 83.18% and false discovery rate (FDR) of 39%, while K-complexes were detected with a sensitivity of 81.57% and an FDR of 29.54%. Similar performances were obtained when using a second expert as benchmark. In addition, when the TQWT and MCA steps were excluded from the pipeline the detection sensitivities dropped down to 70% for spindles and to 76.97% for K-complexes, while the FDR rose up to 43.62 and 49.09%, respectively. Finally, we also evaluated the performance of the proposed method on a set of publicly available sleep EEG recordings. Overall, the results we obtained suggest that the TQWT-MCA method may be a valuable alternative to existing spindle and K-complex detection methods. Paths for improvements and further validations with large-scale standard open-access benchmarking data sets are discussed.

K-Complexes: Interaction between the Central and Autonomic Nervous Systems during Sleep

STUDY OBJECTIVES

To investigate the relationship between K-complexes (KCs) and cardiac functioning.

METHODS

Forty healthy adolescents aged 16-22 y (19 females) participated in the study. Heart rate (HR) fluctuations associated with spontaneous and evoked KCs were investigated on two nights, one with (event-related potential night) and one without auditory tones presented across the night.

RESULTS

There was a clear biphasic cardiac response to evoked and spontaneous KCs, with an initial acceleration in HR followed by a deceleration (P < 0.001). HR acceleration occurred immediately to KCs in response to tones presented in the first third of the interbeat interval, but was delayed a beat when the tone occurred later in the cardiac cycle (P < 0.05). Sex differences were also evident. Pretone baseline HR was higher, and the magnitude of the HR response was blunted and delayed, in female compared to male adolescents (P < 0.001). Also, pretone baseline HR was lower when a tone elicited a KC compared to when it did not (P < 0.001), suggesting that KCs are possibly more likely to be elicited by external stimuli in states of reduced cardiac activation.

CONCLUSIONS

The strict dependency observed between KCs and cardiac control indicates a potential role of KCs in modulating the cardiovascular system during sleep. Sex differences in the KC-cardiac response indicate the sensitivity of this measure in capturing sex differences in cardiac regulatory physiology.

Slow-wave activity surrounding stage N2 K-complexes and daytime function measured by psychomotor vigilance test in obstructive sleep apnea

STUDY OBJECTIVE

To better understand the inter-individual differences in neurobehavioral impairment in obstructive sleep apnea (OSA) and its treatment with continuous positive airway pressure (CPAP), we examined how changes in sleep electroencephalography (EEG) slow waves were associated with next-day psychomotor vigilance test (PVT) performance.

METHODS

Data from 28 OSA subjects (Apnea-Hypopnea Index with 3% desaturation and/or with an associated arousal [AHI3A] > 15/hour; AHI3A = sum of all apneas and hypopneas with 3% O2 desaturation and/or an EEG arousal, divided by total sleep time [TST]), who underwent three full in-lab nocturnal polysomnographies (NPSGs: chronic OSA, CPAP-treated OSA, and acute OSA), and 19 healthy sleepers were assessed. Four 20-minute PVTs were performed after each NPSG along with subjective and objective assessment of sleepiness. Three EEG metrics were calculated: K-complex (KC) Density (#/minute of N2 sleep), change in slow-wave activity in 1-second envelopes surrounding KCs (ΔSWAK), and relative frontal slow-wave activity during non-rapid eye movement (NREM) (%SWA).

RESULTS

CPAP treatment of OSA resulted in a decrease in KC Density (chronic: 3.9 ± 2.2 vs. treated: 2.7 ± 1.1; p < 0.01; mean ± SD) and an increase in ΔSWAK (chronic: 2.6 ± 2.3 vs. treated: 4.1 ± 2.4; p < 0.01) and %SWA (chronic: 20.9 ± 8.8 vs. treated: 26.6 ± 8.6; p < 0.001). Cross-sectionally, lower ΔSWAK values were associated with higher PVT Lapses (chronic: rho = -0.55, p < 0.01; acute: rho = -0.46, p = 0.03). Longitudinally, improvement in PVT Lapses with CPAP was associated with an increase in ΔSWAK (chronic to treated: rho = -0.48, p = 0.02; acute to treated: rho = -0.5, p = 0.03). In contrast, OSA severity or global sleep quality metrics such as arousal index, NREM, REM, or TST were inconsistently associated with PVT Lapses.

CONCLUSION

Changes in EEG slow waves, in particular ∆SWAK, explain inter-individual differences in PVT performance better than conventional NPSG metrics, suggesting that ΔSWAK is a night-time correlate of next-day vigilance in OSA.

Preferential processing of emotionally and self-relevant stimuli persists in unconscious N2 sleep

Information processing has been suggested to depend on the current state of the brain as well as stimulus characteristics (e.g. salience). We compared processing of salient stimuli (subject's own names [SONs] and angry voice [AV] stimuli) to processing of unfamiliar names (UNs) and neutral voice (NV) stimuli across different vigilance stages (i.e. wakefulness as well as sleep stages N1 and N2) by means of event-related oscillatory responses during wakefulness and a subsequent afternoon nap. Our findings suggest that emotional prosody and self-relevance drew more attentional resources during wakefulness with specifically AV stimuli being processed more strongly. During N1, SONs were more arousing than UNs irrespective of prosody. Moreover, emotional and self-relevant stimuli evoked stronger responses also during N2 sleep suggesting a 'sentinel processing mode' of the brain during this state of naturally occurring unconsciousness. Finally, this initial preferential processing of salient stimuli during N2 sleep seems to be followed by an inhibitory sleep-protecting process, which is reflected by a K-complex-like response.

The role of the spontaneous and evoked k-complex in good-sleeper controls and in individuals with insomnia

STUDY OBJECTIVES

Spontaneous and evoked K-complexes are believed to reflect a mechanism of sleep protection, yet their functional role remains a subject of debate. Studying the K-complex in primary insomnia, for which sleep protection appears to be of central importance, may provide further insight on its role. The purpose of the present study was to determine the role of spontaneous and evoked K-complexes in good sleepers and to investigate its role in primary insomnia.

PARTICIPANTS

Twelve individuals with primary insomnia (mean age = 45.4 years) and 12 good-sleeper controls (mean age = 44.3 years).

METHODS AND PROCEDURE

Participants underwent 4 consecutive nights of polysomnographic recordings. Spontaneous K-complexes (SKC) were analyzed during continuous stage 2 sleep on the third night, whereas evoked K-complexes (EKC) were elicited by auditory stimuli on the fourth night. Relative spectral power was measured on 1-second electroencephalographic segments prior to and following SKC, EKC, and trials in which auditory stimuli did not elicit a K-complex (EKC-). K-complex amplitudes were also measured.

RESULTS

Measures of relative spectral power showed significant changes following EKC (increase in activity in the delta frequency band and decrease in activity in the theta, sigma, beta, and gamma frequency bands) and SKC (increase in activity in delta frequency band and decrease in activity in theta, alpha, sigma, and beta frequency bands) for good sleepers, whereas there was no such marked change in electroencephalographic activity surrounding EKC-. A similar pattern of electroencephalographic activity was also observed for the insomnia group on trials of each different K-complex. Auditory stimuli elicited the same proportion of EKC for both groups, whereas SKC density was higher for the insomnia group (1.52 SKC/min) than for good sleepers (1.06 SKC/minute)

CONCLUSION

These results suggest that the SKC and the EKC both promote deeper sleep, further supporting a sleep-protection role.

An intra-K-complex oscillation with independent and labile frequency and topography in NREM sleep

NREM sleep is characterized by K-complexes (KCs), over the negative phase of which we identified brief activity in the theta range. We recorded high resolution EEG of whole-night sleep from seven healthy volunteers and visually identified 2nd and 3rd stage NREM spontaneous KCs. We identified three major categories: (1) KCs without intra-KC-activity (iKCa), (2) KCs with non-oscillatory iKCa, and (3) KCs with oscillatory iKCa. The latter group of KCs with intra-KC-oscillation (iKCo), was clustered according to the duration of the iKCo. iKCa was observed in most KCs (1150/1522, 75%). iKCos with 2, 3, and 4 waves were observed in 52% (786/1522) of KCs in respective rates of 49% (386/786), 44%, and 7%. Successive waves of iKCos showed on average a shift of their maximal amplitude in the anterio-posterior axis, while the average amplitude of the slow KC showed no spatial shift in time. The iKCo spatial shift was accompanied by transient increases in instantaneous frequency from the theta band toward the alpha band, followed by decreases to upper theta. The study shows that the KC is most often concurrently accompanied by an independent brief iKCo exhibiting topographical relocation of amplitude maxima with every consecutive peak and transient increases in frequency. The iKCo features are potentially reflecting arousing processes taking place during the KC.

Spontaneous K-Complexes may be biomarkers of the progression of amnestic mild cognitive impairment

OBJECTIVE

Spontaneous K-complexes (SKCs), a hallmark of stage 2 sleep, have been reported to decrease in density in Alzheimer's disease (AD) patients. However, few former studies have explored the alterations in SKC characteristics in the pre-clinical phase of AD-amnestic mild cognitive impairment (aMCI). The aim of our prospective cohort study was to investigate the changing trend in SKC characteristics during the progression of aMCI.

METHODS

SKC density, amplitude and duration were measured in aMCI subjects and normal controls (NC) at two-year follow-up assessments by polysomnography (PSG). In sum, 22 NCs, 25 stable aMCI (sMCI) subjects and 20 progressive aMCI (pMCI) subjects finished the four follow-up PSG assessments, and their data were used for analysis.

RESULTS

SKC density and amplitude, but not duration, decreased during the follow-up assessments in both NCs and aMCI subjects, but the rate of decrease of these parameters was greater in aMCI subjects. With the progression of aMCI, significant differences in SKC density and amplitude among the three groups were observed, whereas SKC density showed no difference at the early stage of aMCI. The receiver operating characteristic (ROC) curve results demonstrated that SKC density and amplitude could distinguish aMCI subjects from NCs with high specificity and sensitivity.

CONCLUSION

Our results suggest that SKCs decrease with ageing and the progression of aMCI, and SKC characteristics may be potential biomarkers for diagnosing aMCI.

The heritability of the human K-complex: a twin study

Sleep electroencephalogram (EEG) has a trait-like nature. Several findings highlighted the heritability of spectral power in specific frequency ranges and sleep spindles during nonrapid eye movement (NREM) sleep. However, a genetic influence on the K-complex (KC), one of the electrophysiological hallmarks of NREM sleep, has never been assessed. Here, we investigated the heritability of the KC detected during NREM stage 2 comparing 10 monozygotic (MZ) and 10 dizygotic (DZ) twin pairs. Genetic variance analysis (GVA) and intraclass correlation coefficients (ICCs) were performed to assess the genetic effect and within-pair similarity for KC density, amplitude, and for the area under the curve (AUC) of the KC average waveform at Fz, Cz, and Pz scalp locations. Moreover, cluster analysis was performed on the KC average waveform profile. We observed a significant genetic effect on KC AUC at Cz and Pz, and on amplitude at Pz. Within-pair similarity (ICCs) was always significant for MZ twins except for KC density at Fz, whereas DZ twins always exhibited ICCs below the significance threshold, with the exception of density at Pz. The largest differences in within-pair similarity between MZ and DZ groups were observed again for AUC at Cz and Pz. MZ pairs accurately clustered for the KC average waveform with a higher frequency (successful clustering rate for MZ pairs: Fz = 60%; Cz = 80%; Pz = 90%) compared with DZ pairs (successful clustering rate for DZ pairs: Fz = 10%; Cz = 10%; Pz = none). Our results suggest the existence of a genetic influence on the human KC, particularly related to its morphology and maximally observable in central and parietal locations.

Partial recovery of alcohol dependence-related deficits in sleep evoked potentials following 12 months of abstinence

Stimuli presented during sleep can produce an evoked EEG delta wave referred to as a K-complex. These responses occur when large numbers of cortical cells burst fire in a synchronized manner. Large amplitude synchronized scalp responses require that the CNS contain large numbers of healthy neurons that are interconnected with highly functional white matter pathways. The P2, N550, and P900 components of the evoked K-complex are sensitive measures of normal healthy brain aging, showing a decrease in amplitude with age. N550 and P900 amplitudes are also reduced in recently detoxified alcoholics, most dramatically over frontal scalp regions. The present study tested the hypothesis that the amplitude of K-complex related evoked potential components would increase with prolonged abstinence. Fifteen alcoholics (12 men) were studied twice, separated by a 12 month period, during which time they were followed with monthly phone calls. Subjects were aged between 38 and 60 years at their first study. They had on average a 29.3 ± 6.7 year drinking history and had been abstinent for between 54 and 405 days at initial testing. Evoked K-complexes were identified in the EEG and averaged to enable measurement of the P2, N550 and P900 peaks. Data were collected from seven scalp sites (FP1, FP2, Fz, FCz, Cz, CPz, and Pz). N550 and P900 amplitudes were significantly higher after 12 months of abstinence and an improvement of at least 5 μV occurred in 12 of the 15 subjects. N550 and P900 also showed highly significant site by night interactions with the largest increases occurring over prefrontal and frontal sites. The data indicate that the sleep evoked response may provide a sensitive marker of brain recovery with abstinence from alcohol.

Beyond K-complex binary scoring during sleep: probabilistic classification using deep learning

STUDY OBJECTIVES

K-complexes (KCs) are a recognized electroencephalography marker of sensory processing and a defining feature of sleep stage 2. KC frequency and morphology may also be reflective of sleep quality, aging, and a range of sleep and sensory processing deficits. However, manual scoring of K-complexes is impractical, time-consuming, and thus costly and currently not well-standardized. Although automated KC detection methods have been developed, performance and uptake remain limited.

METHODS

The proposed algorithm is based on a deep neural network and Gaussian process, which gives the input waveform a probability of being a KC ranging from 0% to 100%. The algorithm was trained on half a million synthetic KCs derived from manually scored sleep stage 2 KCs from the Montreal Archive of Sleep Study containing 19 healthy young participants. Algorithm performance was subsequently assessed on 700 independent recordings from the Cleveland Family Study using sleep stages 2 and 3 data.

RESULTS

The developed algorithm showed an F1 score (a measure of binary classification accuracy) of 0.78 and thus outperforms currently available KC scoring algorithms with F1 = 0.2-0.6. The probabilistic approach also captured expected variability in KC shape and amplitude within individuals and across age groups.

CONCLUSIONS

An automated probabilistic KC classification is well suited and effective for systematic KC detection for a more in-depth exploration of potential relationships between KCs during sleep and clinical outcomes such as health impacts and daytime symptomatology.

K-complexes are a sensitive marker of noise-related sensory processing during sleep: A pilot study

STUDY OBJECTIVES

The primary aim of this study was to examine dose-response relationships between sound pressure levels (SPLs) and K-complex occurrence probability for wind farm and road traffic noise. A secondary aim was to compare K-complex dose-responses to manually scored EEG arousals and awakenings.

METHODS

Twenty-five participants underwent polysomnography recordings and noise exposure during sleep in a laboratory. Wind farm and road traffic noise recordings of 20-sec duration were played in random order at 6 SPLs between 33 - 48 dBA during established N2 or deeper sleep. Noise periods were separated with periods of 23 dBA background noise. K-complexes were scored using a validated algorithm. K-complex occurrence probability was compared between noise types controlling for noise SPL, subjective noise sensitivity and measured hearing acuity.

RESULTS

Noise-induced K-complexes were observed in N2 sleep at SPLs as low as 33 dBA (Odds ratio, 33dBA vs 23 dBA, mean (95% confidence interval); 1.75 (1.16, 2.66)) and increased with SPL. EEG arousals and awakenings were only associated with noise above 39 dBA in N2 sleep. K-complexes were 2 times more likely to occur in response to noise than EEG arousals or awakenings. Subjective noise sensitivity and hearing acuity were associated with K-complex occurrence, but not arousal or awakening. Noise type did not detectably influence K-complexes, EEG arousals or awakening responses.

CONCLUSION

These findings support that K-complexes are a sensitive marker of sensory processing of environmental noise during sleep and that increased hearing acuity and decreased self-reported noise sensitivity increase K-complex probability.

Association between Loss of Sleep-specific Waves and Age, Sleep Efficiency, Body Mass Index, and Apnea-Hypopnea Index in Human N3 Sleep

Sleep spindles (SS) and K-complexes (KC) play important roles in human sleep. It has been reported that age, body mass index (BMI), and apnea-hypopnea index (AHI) may influence the number of SS or KC in non-rapid-eye-movement (NREM) 2 (N2) sleep. In this study, we investigated whether the loss of SS or KC is associated with the above factors in NREM 3 (N3) sleep. A total of 152 cases were enrolled from 2013 to 2017. The correlations between the number of SS or KC in N3 sleep and participants’ characteristics were analyzed using Spearman rank correlation. Chi-squared test was used to assess the effects of age, sleep efficiency, and BMI on the loss of N3 sleep, N3 spindle and N3 KC. Our results showed that there were negative correlations between the number of SS in N3 sleep with age, BMI, and AHI (P < 0.001), and similar trends were found for KC as well. The loss of SS and KC in N3 sleep was related with age, BMI, and AHI (P < 0.01), as was the loss of N3 sleep (P < 0.01). However, sleep efficiency was not related with the loss of N3 sleep, SS and KC in N3 sleep (P > 0.05). The present study supports that age, BMI, and AHI are all influencing factors of SS and KC loss in human N3 sleep, but sleep efficiency was not an influencing factor in the loss of N3 sleep and the loss of SS and KC in N3 sleep.

Meet Spinky: An Open-Source Spindle and K-Complex Detection Toolbox Validated on the Open-Access Montreal Archive of Sleep Studies (MASS)

Sleep spindles and K-complexes are among the most prominent micro-events observed in electroencephalographic (EEG) recordings during sleep. These EEG microstructures are thought to be hallmarks of sleep-related cognitive processes. Although tedious and time-consuming, their identification and quantification is important for sleep studies in both healthy subjects and patients with sleep disorders. Therefore, procedures for automatic detection of spindles and K-complexes could provide valuable assistance to researchers and clinicians in the field. Recently, we proposed a framework for joint spindle and K-complex detection (Lajnef et al., 2015a) based on a Tunable Q-factor Wavelet Transform (TQWT; Selesnick, 2011a) and morphological component analysis (MCA). Using a wide range of performance metrics, the present article provides critical validation and benchmarking of the proposed approach by applying it to open-access EEG data from the Montreal Archive of Sleep Studies (MASS; O'Reilly et al., 2014). Importantly, the obtained scores were compared to alternative methods that were previously tested on the same database. With respect to spindle detection, our method achieved higher performance than most of the alternative methods. This was corroborated with statistic tests that took into account both sensitivity and precision (i.e., Matthew's coefficient of correlation (MCC), F1, Cohen κ). Our proposed method has been made available to the community via an open-source tool named Spinky (for spindle and K-complex detection). Thanks to a GUI implementation and access to Matlab and Python resources, Spinky is expected to contribute to an open-science approach that will enhance replicability and reliable comparisons of classifier performances for the detection of sleep EEG microstructure in both healthy and patient populations.

Local Gamma Activity During Non-REM Sleep in the Context of Sensory Evoked K-Complexes

K-complexes (KCs) and Sleep Slow Oscillations (SSOs) are the EEG expression of neuronal bistability during deeper stages Non-REM sleep. They are characterized by a deep negative deflection lasting about half-a-second, sustained, at the cortical level, by a widespread and synchronized neuronal hyperpolarization (i.e., electrical silence). The phase of hyperpolarization is followed by a period of intense and synchronized neuronal firing (i.e., depolarization phase) resulting at the EEG level, in a large positive deflection (lasting about 0.5 s) and a concurrent high frequency activity (i.e., spindles). Both KCs and SSOs rather than being “local” phenomena, propagate over large sections of the cortex. These features suggest that bistability is a large-scale network phenomenon, possibly driven by a propagating excitatory activity and involving wide populations of synchronized neurons. We have recently shown that KCs and SSOs include a positive bump preceding the negative peak and that for sensory-evoked KCs this bump coincides with the P200 wave. We demonstrated that the P200 has a sensory-modality specific localization, as it is firstly elicited in the primary sensory areas related to the stimulus, which in turn receive projections from the thalamic core. We observed that the P200 acts as a propagating excitatory activity and hypothesized that it could play a key role in inducing the opening of K+ channels, and hence the cortical hyperpolarization. Here we demonstrate that the P200 is sustained by a high-frequency excitation bringing further support to its role in triggering bistability. We show that the P200 has a higher power density in gamma band as compared to the P900 coherently for all sensory modalities, and we confirm that the latter wave is crowned by higher activity in sigma-beta bands. Finally, we characterize the P200 gamma activity at the cortical level in terms of spatial localization and temporal dynamics, demonstrating that it emerges in sensory stimulus-specific primary areas and travels over the cortical mantle spreading toward fronto-central associative areas and fading concurrently with the N550 onset.

The role of the sleep K-complex on the conversion from mild cognitive impairment to Alzheimer's disease

The present literature points to an alteration of the human K-complex during non-rapid eye movement sleep in Alzheimer's disease. Nevertheless, the few findings on the K-complex changes in mild cognitive impairment and their possible predictive role on the Alzheimer's disease conversion show mixed findings, lack of replication, and a main interest for the frontal region. The aim of the present study was to assess K-complex measures in amnesic mild cognitive impairment subsequently converted in Alzheimer's disease over different cortical regions, comparing them with healthy controls and stable amnesic mild cognitive impairment. We assessed baseline K-complex density, amplitude, area under the curve and overnight changes in frontal, central and parietal midline derivations of 12 amnesic mild cognitive impairment subsequently converted in Alzheimer's disease, 12 stable amnesic mild cognitive impairment and 12 healthy controls. We also assessed delta electroencephalogram power, to determine if K-complex alterations in amnesic mild cognitive impairment occur with modification of the electroencephalogram power in the frequency range of the slow-wave activity. We found a reduced parietal K-complex density in amnesic mild cognitive impairment subsequently converted in Alzheimer's disease compared with stable amnesic mild cognitive impairment and healthy controls, without changes in K-complex morphology and overnight modulation. Both amnesic mild cognitive impairment groups showed decreased slow-wave sleep percentage compared with healthy controls. No differences between groups were observed in slow-wave activity power. Our findings suggest that K-complex alterations in mild cognitive impairment may be observed earlier in parietal regions, likely mirroring the topographical progression of Alzheimer's disease-related brain pathology, and express a frontal predominance only in a full-blown phase of Alzheimer's disease. Consistently with previous results, such K-complex modification occurs in the absence of significant electroencephalogram power changes in the slow oscillations range.

Evoked K-complexes and altered interaction between the central and autonomic nervous systems during sleep in alcohol use disorder

There is evidence for impairment in both central nervous system (CNS) and autonomic nervous system (ANS) function with prolonged alcohol use. While these impairments persist into abstinence, partial recovery of function has been demonstrated in both systems during sleep. To investigate potential ANS dysfunction associated with cortical CNS responses (impairment in CNS-ANS coupling), we assessed phasic heart rate (HR) fluctuation associated with tones that did and those that did not elicit a K-complex (KC) during stable N2 non-rapid eye movement (NREM) sleep in a group of 16 recently abstinent alcohol use disorder (AUD) patients (41.6 ± 8.5 years) and a group of 13 sex- and age-matched control participants (46.6 ± 9.3 years). Electroencephalogram (EEG) and electrocardiogram (ECG) data were recorded throughout the night. Alcohol consumption questionnaires were also administered to the AUD patients. AUD patients had elevated HR compared to controls at baseline prior to tone presentation. The HR fluctuation associated with KCs elicited by tone presentation was significantly smaller in amplitude, and tended to be delayed in time, in the AUD group compared with the control group, and the subsequent deceleration was also smaller in AUD patients. In both groups, the increase in HR was larger and occurred earlier when KCs were produced than when they were not, and there was no difference in the magnitude of the KC effect between groups. Phasic HR changes associated with KCs elicited by tones are impaired in AUD participants, reflecting ANS dysfunction possibly caused by an alteration of cardiac vagal trafficking. However, only the timing of the HR response was found to relate to estimated lifetime alcohol consumption in AUD. The clinical meaning and implications of these novel findings need to be determined.

Disruption of sleep macro- and microstructure in Alzheimer's disease: overlaps between neuropsychology, neurophysiology, and neuroimaging

Alzheimer's disease (AD) is the leading cause of dementia, often associated with impaired sleep quality and disorganized sleep structure. This study aimed to characterize changes in sleep macrostructure and K-complex density in AD, in relation to neuropsychological performance and brain structural changes. We enrolled 30 AD and 30 healthy control participants, conducting neuropsychological exams, brain MRI, and one-night polysomnography. AD patients had significantly reduced total sleep time (TST), sleep efficiency, and relative durations of non-rapid eye movement (NREM) stages 2 (S2), 3 (S3), and rapid eye movement (REM) sleep (p < 0.01). K-complex (KC) density during the entire sleep period and S2 (p < 0.001) was significantly decreased in AD. We found strong correlations between global cognitive performance and relative S3 (p < 0.001; r = 0.86) and REM durations (p < 0.001; r = 0.87). TST and NREM stage 1 (S1) durations showed a moderate negative correlation with amygdaloid and hippocampal volumes (p < 0.02; r = 0.51-0.55), while S3 and REM sleep had a moderate positive correlation with cingulate cortex volume (p < 0.02; r = 0.45-0.61). KC density strongly correlated with global cognitive function (p < 0.001; r = 0.66) and the thickness of the anterior cingulate cortex (p < 0.05; r = 0.45-0.47). Our results indicate significant sleep organization changes in AD, paralleling cognitive decline. Decreased slow wave sleep and KCs are strongly associated with cingulate cortex atrophy. Since sleep changes are prominent in early AD, they may serve as prognostic markers or therapeutic targets.

Images: Benign myoclonus of sleep associated with K-complexes on electroencephalography

In this brief case report on paroxysmal sleep-related movements, we describe an adolescent patient's presentation of brief jerking movements during sleep and the accompanying differential diagnosis. In examining the patient's overnight electroencephalogram we use hallmark sleep architecture to provide reassurance to the patient and her family.

CITATION

Silverman A, Miglis MG, Gallentine W. Images: Benign myoclonus of sleep associated with K-complexes on electroencephalography. J Clin Sleep Med. 2024;20(1):183-184.

Synthesis, characterization, and electrocatalytic behaviour of hydrothermally grown nanostructured La2 O3 and La2 O3 /K-complex

Rare earth metals play a conspicuous role in magnetic resonance imaging (MRI) for detecting cancerous cells. The alkali metal potassium is a neurotransmitter in the sodium-potassium pump in biomedical sciences. This unique property of rare earth metals and potassium drew our attention to carry forward this study. Therefore, in this work, previously synthesized potassium (K) complexes formed by the reflux of 4-N,N-dimethylaminobenzoic acid (DBA) and potassium hydroxide in methanol, and named [(μ2-4-N,N-dimethylaminobenzoate-κO)(μ2-4-N,N-dimethylaminobenzoic acid-κO)(4-N,N-dimethylaminobenzoic acid-κO) potassium(I) coordination polymer)] were treated hydrothermally with La2 O3 nanomaterials to obtain a nanohybrid La2 O3 /K-complex. After that, the K-complex was analyzed using single-crystal X-ray diffraction and 1 H and 13 C NMR spectroscopy. In addition, the structural and morphological properties of the as-prepared nanostructured La2 O3 /K-complex were also characterized, which involved an investigation using X-ray diffraction (XRD)spectroscopy, Fourier transform infrared (FTIR) spectroscopy, atomic force spectroscopy (AFM), transmission electron microscopy (TEM), and energy dispersive X-ray (EDX) analysis. After this, the electrochemical redox behaviour of the synthesized nanohybrid material was studied using cyclic voltammetry (CV) and differential pulse voltammetry (DPV). Therefore, the results from these studies revealed that the as-prepared material was a La2 O3 /K-complex that has a promising future role in sensing various analytes, as it showed effective electrocatalytic behaviour.

Acoustically evoked K-complexes together with sleep spindles boost verbal declarative memory consolidation in healthy adults

Over the past decade, phase-targeted auditory stimulation (PTAS), a neuromodulation approach which presents auditory stimuli locked to the ongoing phase of slow waves during sleep, has shown potential to enhance specific aspects of sleep functions. However, the complexity of PTAS responses complicates the establishment of causality between specific electroencephalographic events and observed benefits. Here, we used down-PTAS during sleep to specifically evoke the early, K-complex (KC)-like response following PTAS without leading to a sustained increase in slow-wave activity throughout the stimulation window. Over the course of two nights, one with down-PTAS, the other without, high-density electroencephalography (hd-EEG) was recorded from 14 young healthy adults. The early response exhibited striking similarities to evoked KCs and was associated with improved verbal memory consolidation via stimulus-evoked spindle events nested into the up-phase of ongoing 1 Hz waves in a central region. These findings suggest that the early, KC-like response is sufficient to boost memory, potentially by orchestrating aspects of the hippocampal-neocortical dialogue.

Structure of Spectral Composition and Synchronization in Human Sleep on the Whole Scalp: A Pilot Study

We used numerical methods to define the normative structure of the different stages of sleep and wake (W) in a pilot study of 19 participants without pathology (18-64 years old) using a double-banana bipolar montage. Artefact-free 120-240 s epoch lengths were visually identified and divided into 1 s windows with a 10% overlap. Differential channels were grouped into frontal, parieto-occipital, and temporal lobes. For every channel, the power spectrum (PS) was calculated via fast Fourier transform and used to compute the areas for the delta (0-4 Hz), theta (4-8 Hz), alpha (8-13 Hz), and beta (13-30 Hz) bands, which were log-transformed. Furthermore, Pearson's correlation coefficient and coherence by bands were computed. Differences in logPS and synchronization from the whole scalp were observed between the sexes for specific stages. However, these differences vanished when specific lobes were considered. Considering the location and stages, the logPS and synchronization vary highly and specifically in a complex manner. Furthermore, the average spectra for every channel and stage were very well defined, with phase-specific features (e.g., the sigma band during N2 and N3, or the occipital alpha component during wakefulness), although the slow alpha component (8.0-8.5 Hz) persisted during NREM and REM sleep. The average spectra were symmetric between hemispheres. The properties of K-complexes and the sigma band (mainly due to sleep spindles-SSs) were deeply analyzed during the NREM N2 stage. The properties of the sigma band are directly related to the density of SSs. The average frequency of SSs in the frontal lobe was lower than that in the occipital lobe. In approximately 30% of the participants, SSs showed bimodal components in the anterior regions. qEEG can be easily and reliably used to study sleep in healthy participants and patients.

Sleep electroencephalography biomarkers of cognition in obstructive sleep apnea

Obstructive sleep apnea has been associated with cognitive impairment and may be linked to disorders of cognitive function. These associations may be a result of intermittent hypoxaemia, sleep fragmentation and changes in sleep microstructure in obstructive sleep apnea. Current clinical metrics of obstructive sleep apnea, such as the apnea-hypopnea index, are poor predictors of cognitive outcomes in obstructive sleep apnea. Sleep microstructure features, which can be identified on sleep electroencephalography of traditional overnight polysomnography, are increasingly being characterized in obstructive sleep apnea and may better predict cognitive outcomes. Here, we summarize the literature on several major sleep electroencephalography features (slow-wave activity, sleep spindles, K-complexes, cyclic alternating patterns, rapid eye movement sleep quantitative electroencephalography, odds ratio product) identified in obstructive sleep apnea. We will review the associations between these sleep electroencephalography features and cognition in obstructive sleep apnea, and examine how treatment of obstructive sleep apnea affects these associations. Lastly, evolving technologies in sleep electroencephalography analyses will also be discussed (e.g. high-density electroencephalography, machine learning) as potential predictors of cognitive function in obstructive sleep apnea.