Dependence of rhythmic activity and oddball effects in the rat cortex on the depth of sedation during dissociative anesthesia.

The reactions to novelty manifesting in mismatch negativity in the rat brain were studied. During dissociative anesthesia, mismatch negativity-like waves were recorded from the somatosensory cortex using an epidural 32-electrode array. Experimental animals: 7 wild-type Wistar rats and 3 transgenic rats. During high-dose anesthesia, deviant 1,500 Hz tones were presented randomly among many standard 1,000 Hz tones in the oddball paradigm. "Deviant minus standard_before_deviant" difference waves were calculated using both the classical method of Naatanen and method of cross-correlation of sub-averages. Both methods gave consistent results: an early phasic component of the N40 and later N100 to 200 (mismatch negativity itself) tonic component. The gamma and delta rhythms power and the frequency of down-states (suppressed activity periods) were assessed. In all rats, the amplitude of tonic component grew with increasing sedation depth. At the same time, a decrease in gamma power with a simultaneous increase in delta power and the frequency of down-states. The earlier phasic frontocentral component is associated with deviance detection, while the later tonic one over the auditory cortex reflects the orienting reaction. Under anesthesia, this slow mismatch negativity-like wave most likely reflects the tendency of the system to respond to any influences with delta waves, K-complexes and down-states, or produce them spontaneously.

Cross-Frequency Coupling as a Biomarker for Early Stroke Recovery.

BACKGROUND: The application of neuroimaging-based biomarkers in stroke has enriched our understanding of post-stroke recovery mechanisms, including alterations in functional connectivity based on synchronous oscillatory activity across various cortical regions. Phase-amplitude coupling, a type of cross-frequency coupling, may provide additional mechanistic insight. OBJECTIVE: To determine how the phase of prefrontal cortex delta (1-3 Hz) oscillatory activity mediates the amplitude of motor cortex beta (13-20 Hz) oscillations in individual's early post-stroke. METHODS: Participants admitted to an inpatient rehabilitation facility completed resting and task-based EEG recordings and motor assessments around the time of admission and discharge along with structural neuroimaging. Unimpaired controls completed EEG procedures during a single visit. Mixed-effects linear models were performed to assess within- and between-group differences in delta-beta prefrontomotor coupling. Associations between coupling and motor status and injury were also determined. RESULTS: Thirty individuals with stroke and 17 unimpaired controls participated. Coupling was greater during task versus rest conditions for all participants. Though coupling during affected extremity task performance decreased during hospitalization, coupling remained elevated at discharge compared to controls. Greater baseline coupling was associated with better motor status at admission and discharge and positively related to motor recovery. Coupling demonstrated both positive and negative associations with injury involving measures of lesion volume and overlap injury to anterior thalamic radiation, respectively. CONCLUSIONS: This work highlights the utility of prefrontomotor cross-frequency coupling as a potential motor status and recovery biomarker in stroke. The frequency- and region-specific neurocircuitry featured in this work may also facilitate novel treatment strategies in stroke.

Neurovascular Coupling Analysis Based on Multivariate Variational Gaussian Process Convergent Cross-Mapping.

Neurovascular coupling (NVC) provides important insights into the intricate activity of brain functioning and may aid in the early diagnosis of brain diseases. Emerging evidences have shown that NVC could be assessed by the coupling between electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS). However, this endeavor presents significant challenges due to the absence of standardized methodologies and reliable techniques for coupling analysis of these two modalities. In this study, we introduced a novel method, i.e., the collaborative multi-output variational Gaussian process convergent cross-mapping (CMVGP-CCM) approach to advance coupling analysis of EEG and fNIRS. To validate the robustness and reliability of the CMVGP-CCM method, we conducted extensive experiments using chaotic time series models with varying noise levels, sequence lengths, and causal driving strengths. In addition, we employed the CMVGP-CCM method to explore the NVC between EEG and fNIRS signals collected from 26 healthy participants using a working memory (WM) task. Results revealed a significant causal effect of EEG signals, particularly the delta, theta, and alpha frequency bands, on the fNIRS signals during WM. This influence was notably observed in the frontal lobe, and its strength exhibited a decline as cognitive demands increased. This study illuminates the complex connections between brain electrical activity and cerebral blood flow, offering new insights into the underlying NVC mechanisms of WM.

Sleep Delta power, age, and sex effects in treatment-resistant depression.

Electroencephalographic (EEG) deficits in slow wave activity or Delta power (0.5-4 Hz) indicate disturbed sleep homeostasis and are hallmarks of depression. Sleep homeostasis is linked to restorative sleep and potential antidepressant response via non-rapid eye movement (NREM) slow wave sleep (SWS) during which neurons undergo essential repair and rejuvenation. Decreased Low Delta power (0.5-2 Hz) was previously reported in individuals with depression. This study investigated power levels in the Low Delta (0.5-<2 Hz), High Delta (2-4 Hz), and Total Delta (0.5-4 Hz) bands and their association with age, sex, and disrupted sleep in treatment-resistant depression (TRD). Mann-Whitney U tests were used to compare the nightly progressions of Total Delta, Low Delta, and High Delta in 100 individuals with TRD and 24 healthy volunteers (HVs). Polysomnographic parameters were also examined, including Total Sleep Time (TST), Sleep Efficiency (SE), and Wake after Sleep Onset (WASO). Individuals with TRD had lower Delta power during the first NREM episode (NREM1) than HVs. The deficiency was observed in the Low Delta band versus High Delta. Females with TRD had higher Delta power than males during the first NREM1 episode, with the most noticeable sex difference observed in Low Delta. In individuals with TRD, Low Delta power correlated with WASO and SE, and High Delta correlated with WASO. Low Delta power deficits in NREM1 were observed in older males with TRD, but not females. These results provide compelling evidence for a link between age, sex, Low Delta power, sleep homeostasis, and non-restorative sleep in TRD.

A multiscale symbolic approach to decoding delta and ripple oscillation bands as biomarkers for epileptiform discharges.

We use a multiscale symbolic approach to study the complex dynamics of temporal lobe refractory epilepsy employing high-resolution intracranial electroencephalogram (iEEG). We consider the basal and preictal phases and meticulously analyze the dynamics across frequency bands, focusing on high-frequency oscillations up to 240 Hz. Our results reveal significant periodicities and critical time scales within neural dynamics across frequency bands. By bandpass filtering neural signals into delta, theta, alpha, beta, gamma, and ripple high-frequency bands (HFO), each associated with specific neural processes, we examine the distinct nonlinear dynamics. Our method introduces a reliable approach to pinpoint intrinsic time lag scales τ within frequency bands of the basal and preictal signals, which are crucial for the study of refractory epilepsy. Using metrics such as permutation entropy (H), Fisher information (F), and complexity (C), we explore nonlinear patterns within iEEG signals. We reveal the intrinsic τmax that maximize complexity within each frequency band, unveiling the nonlinear subtle patterns of the temporal structures within the basal and preictal signal. Examining the H×F and C×F values allows us to identify differences in the delta band and a band between 200 and 220 Hz (HFO 6) when comparing basal and preictal signals. Differences in Fisher information in the delta and HFO 6 bands before seizures highlight their role in capturing important system dynamics. This offers new perspectives on the intricate relationship between delta oscillations and HFO waves in patients with focal epilepsy, highlighting the importance of these patterns and their potential as biomarkers.

Spatiotemporal EEG dynamics of the sleep onset process in preadolescence.

BACKGROUND: During preadolescence the sleep electroencephalography undergoes massive qualitative and quantitative modifications. Despite these relevant age-related peculiarities, the specific EEG pattern of the wake-sleep transition in preadolescence has not been exhaustively described. METHODS: The aim of the present study is to characterize regional and temporal electrophysiological features of the sleep onset (SO) process in a group of 23 preadolescents (9-14 years) and to compare the topographical pattern of slow wave activity and delta/beta ratio of preadolescents with the EEG pattern of young adults. RESULTS: Results showed in preadolescence the same dynamics known for adults, but with peculiarities in the delta and beta activity, likely associated with developmental cerebral modifications: the delta power showed a widespread increase during the SO with central maxima, and the lower bins of the beta activity showed a power increase after SO. Compared to adults, preadolescents during the SO exhibited higher delta power only in the slowest bins of the band: before SO slow delta activity was higher in prefrontal, frontal and occipital areas in preadolescents, and, after SO the younger group had higher slow delta activity in occipital areas. In preadolescents delta/beta ratio was higher in more posterior areas both before and after the wake-sleep transition and, after SO, preadolescents showed also a lower delta/beta ratio in frontal areas, compared to adults. CONCLUSION: Results point to a general higher homeostatic drive for the developing areas, consistently with plastic-related maturational modifications, that physiologically occur during preadolescence.

Coincident development and synchronization of sleep-dependent delta in the cortex and medulla.

In early development, active sleep is the predominant sleep state before it is supplanted by quiet sleep. In rats, the developmental increase in quiet sleep is accompanied by the sudden emergence of the cortical delta rhythm (0.5-4 Hz) around postnatal day 12 (P12). We sought to explain the emergence of the cortical delta by assessing developmental changes in the activity of the parafacial zone (PZ), a medullary structure thought to regulate quiet sleep in adults. We recorded from the PZ in P10 and P12 rats and predicted an age-related increase in neural activity during increasing periods of delta-rich cortical activity. Instead, during quiet sleep, we discovered sleep-dependent rhythmic spiking activity-with intervening periods of total silence-phase locked to a local delta rhythm. Moreover, PZ and cortical delta were coherent at P12 but not at P10. PZ delta was also phase locked to respiration, suggesting sleep-dependent modulation of PZ activity by respiratory pacemakers in the ventral medulla. Disconnecting the main olfactory bulbs from the cortex did not diminish cortical delta, indicating that the influence of respiration on delta at this age is not mediated indirectly through nasal breathing. Finally, we observed an increase in parvalbumin-expressing terminals in the PZ across these ages, supporting a role for local GABAergic inhibition in the PZ's rhythmicity. The unexpected discovery of delta-rhythmic neural activity in the medulla-when cortical delta is also emerging-provides a new perspective on the brainstem's role in regulating sleep and promoting long-range functional connectivity in early development.

Extracting Stress-Related EEG Patterns From Pre-Sleep EEG for Forecasting Slow-Wave Sleep Deficiency.

Sleep is vital to our daily activity. Lack of proper sleep can impair functionality and overall health. While stress is known for its detrimental impact on sleep quality, the precise effect of pre-sleep stress on subsequent sleep structure remains unknown. This study introduced a novel approach to study the pre-sleep stress effect on sleep structure, specifically slow-wave sleep (SWS) deficiency. To achieve this, we selected forehead resting EEG immediately before and upon sleep onset to extract stress-related neurological markers through power spectra and entropy analysis. These markers include beta/delta correlation, alpha asymmetry, fuzzy entropy (FuzzEn) and spectral entropy (SpEn). Fifteen subjects were included in this study. Our results showed that subjects lacking SWS often exhibited signs of stress in EEG, such as an increased beta/delta correlation, higher alpha asymmetry, and increased FuzzEn in frontal EEG. Conversely, individuals with ample SWS displayed a weak beta/delta correlation and reduced FuzzEn. Finally, we employed several supervised learning models and found that the selected neurological markers can predict subsequent SWS deficiency. Our investigation demonstrated that the classifiers could effectively predict varying levels of slow-wave sleep (SWS) from pre-sleep EEG segments, achieving a mean balanced accuracy surpassing 0.75. The SMOTE-Tomek resampling method could improve the performance to 0.77. This study suggests that stress-related neurological markers derived from pre-sleep EEG can effectively predict SWS deficiency. Such information can be integrated with existing sleep-improving techniques to provide a personalized sleep forecasting and improvement solution.

Outcome measures of brainwave entrainment using delta wave stimulation in individuals with tinnitus having normal hearing sensitivity.

OBJECTIVE: The current study aimed to evaluate the efficacy of delta frequency binaural beats stimulation in treatment of individuals with tinnitus having normal hearing sensitivity. METHOD: Twenty-four individuals who reported bothersome tinnitus in the presence of clinically normal hearing were grouped into two (I and II). The group was provided with delta frequency binaural beats and II was provided with white noise stimulation (both of 20 min duration) for 30 days. Post 30 days, the re-assessment of tinnitus handicap, depression, anxiety, and quality of life parameters were performed and compared with that of pre-treatment scores. RESULTS: A considerable reduction of tinnitus handicap scores, depression and anxiety levels were observed for both the groups, except for the quality-of-life parameters. However, few of the participants showed limited or negligible improvement post-treatment. On comparison of reduction of scores observed across the groups, there was a higher reduction of scores observed for group I when compared to group II. CONCLUSION: The current study was an initial attempt to study the efficacy of binaural beats in treatment of individuals with tinnitus having normal hearing. Apart from a few individuals, the delta wave stimulation acted as a helpful tool in improving tinnitus borne distress symptoms in such patients with normal hearing. The results of the present study put forward the scope of adapting binaural beats stimulation for the treatment of individuals presenting with tinnitus having normal hearing sensitivity. This technique could be adopted into clinical practice after extensive research involving an extended treatment duration on a larger population.

Association of Disrupted Delta Wave Activity During Sleep With Long-Term Cardiovascular Disease and Mortality.

BACKGROUND: Delta wave activity is a prominent feature of deep sleep, which is significantly associated with sleep quality. OBJECTIVES: The authors hypothesized that delta wave activity disruption during sleep could predict long-term cardiovascular disease (CVD) and CVD mortality risk. METHODS: The authors used a comprehensive power spectral entropy-based method to assess delta wave activity during sleep based on overnight polysomnograms in 4,058 participants in the SHHS (Sleep Heart Health Study) and 2,193 participants in the MrOS (Osteoporotic Fractures in Men Study) Sleep study. RESULTS: During 11.0 ± 2.8 years of follow-up in SHHS, 729 participants had incident CVD and 192 participants died due to CVD. During 15.5 ± 4.4 years of follow-up in MrOS, 547 participants had incident CVD, and 391 died due to CVD. In multivariable Cox regression models, lower delta wave entropy during sleep was associated with higher risk of coronary heart disease (SHHS: HR: 1.46; 95% CI: 1.02-2.06; P = 0.03; MrOS: HR: 1.79; 95% CI: 1.17-2.73; P < 0.01), CVD (SHHS: HR: 1.60; 95% CI: 1.21-2.11; P < 0.01; MrOS: HR: 1.43; 95% CI: 1.00-2.05; P = 0.05), and CVD mortality (SHHS: HR: 1.94; 95% CI: 1.18-3.18; P < 0.01; MrOS: HR: 1.66; 95% CI: 1.12-2.47; P = 0.01) after adjusting for covariates. The Shapley Additive Explanations method indicates that low delta wave entropy was more predictive of coronary heart disease, CVD, and CVD mortality risks than conventional sleep parameters. CONCLUSIONS: The results suggest that delta wave activity disruption during sleep may be a useful metric to identify those at increased risk for CVD and CVD mortality.

Preoperative recovery sleep ameliorates postoperative cognitive dysfunction aggravated by sleep fragmentation in aged mice by enhancing EEG delta-wave activity and LFP theta oscillation in hippocampal CA1.

Sleep fragmentation (SF) is a common sleep problem experienced during the perioperative period by older adults, and is associated with postoperative cognitive dysfunction (POCD). Increasing evidence indicates that delta-wave activity during non-rapid eye movement (NREM) sleep is involved in sleep-dependent memory consolidation and that hippocampal theta oscillations are related to spatial exploratory memory. Recovery sleep (RS), a self-regulated state of sleep homeostasis, enhances delta-wave power and memory performance in sleep-deprived older mice. However, it remains unclear whether RS therapy has a positive effect on cognitive changes following SF in older mouse models. Therefore, this study aimed to explore whether preoperative RS can alleviate cognitive deficits in aged mice with SF. A model of preoperative 24-h SF combined with exploratory laparotomy-induced POCD was established in 18-month-old mice. Aged mice were treated with preoperative 6-h RS following SF and postoperative 6-h RS following surgery, respectively. The changes in hippocampus-dependent cognitive function were investigated using behavioral tests, electroencephalography (EEG), local field potential (LFP), magnetic resonance imaging, and neuromorphology. Mice that underwent 24-h SF combined with surgery exhibited severe spatial memory impairment; impaired cognitive performance could be alleviated by preoperative RS treatment. In addition, preoperative RS increased NREM sleep; enhanced EEG delta-wave activity and LFP theta oscillation in the hippocampal CA1; and improved hippocampal perfusion, microstructural integrity, and neuronal damage. Taken together, these results provide evidence that preoperative RS may ameliorate the severity of POCD aggravated by SF by enhancing delta slow-wave activity and hippocampal theta oscillation, and by ameliorating the reduction in regional cerebral blood flow and white matter microstructure integrity in the hippocampus.

Delta-band Activity Underlies Referential Meaning Representation during Pronoun Resolution.

Human language offers a variety of ways to create meaning, one of which is referring to entities, objects, or events in the world. One such meaning maker is understanding to whom or to what a pronoun in a discourse refers to. To understand a pronoun, the brain must access matching entities or concepts that have been encoded in memory from previous linguistic context. Models of language processing propose that internally stored linguistic concepts, accessed via exogenous cues such as phonological input of a word, are represented as (a)synchronous activities across a population of neurons active at specific frequency bands. Converging evidence suggests that delta band activity (1-3 Hz) is involved in temporal and representational integration during sentence processing. Moreover, recent advances in the neurobiology of memory suggest that recollection engages neural dynamics similar to those which occurred during memory encoding. Integrating from these two research lines, we here tested the hypothesis that neural dynamic patterns, especially in delta frequency range, underlying referential meaning representation, would be reinstated during pronoun resolution. By leveraging neural decoding techniques (i.e., representational similarity analysis) on a magnetoencephalogram data set acquired during a naturalistic story-listening task, we provide evidence that delta-band activity underlies referential meaning representation. Our findings suggest that, during spoken language comprehension, endogenous linguistic representations such as referential concepts may be proactively retrieved and represented via activation of their underlying dynamic neural patterns.

Distinct Cortical Networks Subserve Spatio-temporal Sampling in Vision through Different Oscillatory Rhythms.

Although visual input arrives continuously, sensory information is segmented into (quasi-)discrete events. Here, we investigated the neural correlates of spatiotemporal binding in humans with magnetoencephalography using two tasks where separate flashes were presented on each trial but were perceived, in a bistable way, as either a single or two separate events. The first task (two-flash fusion) involved judging one versus two flashes, whereas the second task (apparent motion: AM) involved judging coherent motion versus two stationary flashes. Results indicate two different functional networks underlying two unique aspects of temporal binding. In two-flash fusion trials, involving an integration window of ∼50 msec, evoked responses differed as a function of perceptual interpretation by ∼25 msec after stimuli offset. Multivariate decoding of subjective perception based on prestimulus oscillatory phase was significant for alpha-band activity in the right medial temporal (V5/MT) area, with the strength of prestimulus connectivity between early visual areas and V5/MT being predictive of performance. In contrast, the longer integration window (∼130 msec) for AM showed evoked field differences only ∼250 msec after stimuli offset. Phase decoding of the perceptual outcome in AM trials was significant for theta-band activity in the right intraparietal sulcus. Prestimulus theta-band connectivity between V5/MT and intraparietal sulcus best predicted AM perceptual outcome. For both tasks, phase effects found could not be accounted by concomitant variations in power. These results show a strong relationship between specific spatiotemporal binding windows and specific oscillations, linked to the information flow between different areas of the where and when visual pathways.

Mutual information of multiple rhythms in schizophrenia.

Interactions between different cortical rhythms, such as slow and fast oscillations, have been hypothesized to underlie many cognitive functions. In patients diagnosed with schizophrenia, there is some evidence indicating that the interplay between slow and fast oscillations might be impaired or disrupted. In this study, we investigated multiple oscillatory interactions in schizophrenia using a novel approach based on information theory. This method allowed us to investigate interactions from a new perspective, where two or more rhythm interactions could be analyzed at the same time. We calculated the mutual information of multiple rhythms (MIMR) for EEG segments registered in resting state. Following previous studies, we focused on rhythm interactions between theta, alpha, and gamma. The results showed that, in general, MIMR was higher in patients than in controls for alpha-gamma and theta-gamma couplings. This finding of an increased coupling between slow and fast rhythms in schizophrenia may indicate complex interactions in the Default Mode Network (DMN) related to hyperactivation of internally guided cognition.

CLEP: Contrastive Learning for Epileptic Seizure Prediction Using a Spatio-Temporal-Spectral Network.

Seizure prediction of epileptic preictal period through electroencephalogram (EEG) signals is important for clinical epilepsy diagnosis. However, recent deep learning-based methods commonly employ intra-subject training strategy and need sufficient data, which are laborious and time-consuming for a practical system and pose a great challenge for seizure predicting. Besides, multi-domain characterizations, including spatio-temporal-spectral dependencies in an epileptic brain are generally neglected or not considered simultaneously in current approaches, and this insufficiency commonly leads to suboptimal seizure prediction performance. To tackle the above issues, in this paper, we propose Contrastive Learning for Epileptic seizure Prediction (CLEP) using a Spatio-Temporal-Spectral Network (STS-Net). Specifically, the CLEP learns intrinsic epileptic EEG patterns across subjects by contrastive learning. The STS-Net extracts multi-scale temporal and spectral representations under different rhythms from raw EEG signals. Then, a novel triple attention layer (TAL) is employed to construct inter-dimensional interaction among multi-domain features. Moreover, a spatio dynamic graph convolution network (sdGCN) is proposed to dynamically model the spatial relationships between electrodes and aggregate spatial information. The proposed CLEP-STS-Net achieves a sensitivity of 96.7% and a false prediction rate of 0.072/h on the CHB-MIT scalp EEG database. We also validate the proposed method on clinical intracranial EEG (iEEG) database from our Xuanwu Hospital of Capital Medical University, and the predicting system yielded a sensitivity of 95%, a false prediction rate of 0.087/h. The experimental results outperform the state-of-the-art studies which validate the efficacy of our method. Our code is available at https://github.com/LianghuiGuo/CLEP-STS-Net.

Frontal Intermittent Rhythmic Delta Activity Is a Useful Diagnostic Tool of Neurotoxicity After CAR T-Cell Infusion.

BACKGROUND AND OBJECTIVES: Chimeric antigen receptor (CAR) T-cell therapies have dramatically improved the prognosis of patients with relapsed or refractory hematologic malignancies; however, cytokine release syndrome and immune effector cell-associated neurotoxicity syndrome (ICANS) occur in ∼100 and 50% of patients, respectively. This study aimed to determine whether EEG patterns may be considered as diagnostic tools for ICANS. METHODS: Patients who received CAR T-cell therapy at Montpellier University Hospital between September 2020 and July 2021 were prospectively enrolled. Neurologic signs/symptoms and laboratory parameters were monitored daily for 14 days after CAR T-cell infusion. EEG and brain MRI were performed between day 6 and 8 after CAR T-cell infusion. EEG was performed again on the day of ICANS occurrence, if outside this time window. All collected data were compared between patients with and without ICANS. RESULTS: Thirty-eight consecutive patients were enrolled (14 women; median age: 65 years, interquartile range: [55-74]). ICANS was observed in 17 of 38 patients (44%) after a median time of 6 days after CAR T-cell infusion (4-8). The median ICANS grade was 2 (1-3). Higher C-reactive protein peak (146 mg/L [86-256], p = 0.004) at day 4 (3-6), lower natremia (131 mmol/L [129-132], p = 0.005) at day 5 (3-6), and frontal intermittent rhythmic delta activity (FIRDA, p < 0.001) on EEG between days 6 and 8 after infusion were correlated with ICANS occurrence. FIRDA was only observed in patients with ICANS (N = 15/17, sensitivity of 88%) and disappeared after ICANS resolution, usually after steroid therapy. Except for hyponatremia, no other toxic/metabolic marker was associated with FIRDA (p = 0.002). The plasma concentration of copeptin, a surrogate marker of antidiuretic hormone secretion, assessed at day 7 after infusion, was significantly higher in patients with (N = 8) than without (N = 6) ICANS (p = 0.043). DISCUSSION: FIRDA is a reliable diagnostic tool for ICANS, with a sensitivity of 88% and a negative predictive value of 100%. Moreover, as this EEG pattern disappeared concomitantly with ICANS resolution, FIRDA could be used to monitor neurotoxicity. Finally, our study suggests a pathogenic pathway that starts with increased C-reactive protein, followed by hyponatremia and eventually ICANS and FIRDA. More studies are required to confirm our results. CLASSIFICATION OF EVIDENCE: This study provides Class III evidence that FIRDA on spot EEG accurately distinguishes patients with ICANS compared with those without after CAR T-cell therapy for hematologic malignancy.

IMF-Based MF and HS Energy Feature Information of F5, and F6 Movement and Motor Imagery EEG Signals in Delta Rhythms Using HHT.

This study aims to extract the energy feature distributions in the form of marginal frequency (MF) and Hilbert spectrum (HS) in the intrinsic mode functions (IMF) domain for actual movement (AM)-based and motor imagery (MI)-based electroencephalogram (EEG) signals using the Hilbert-Huang transformation (HHT) time frequency (TF) analysis method. Accordingly, F5 and F6 EEG signal TF energy feature distributions in delta (0.5-4 Hz) rhythm are explored. We propose IMF-based and residue function (RF)-based MF and HS feature information extraction methods with IMFRFERDD (IMFRF energy refereed distribution density), IMFRFMFERDD (IMFRF MF energy refereed distribution density), and IMFRFHSERDD (IMFRF HS energy refereed distribution density) parameters using HHT with application to AM, MI EEG F5, and F6 signals in delta rhythm. The AM and MI tasks involve simultaneously opening fists and feet, as well as simultaneously closing fists and feet. Eight samples (32 in total) with a time duration of 1000 ms are extracted for analyzing F5AM, F5MI, F6AM, and F6MI EEG signals, which are decomposed into five IMFs and one RF. The maximum average IMFRFERDD values of IMF4 are 3.70, 3.43, 3.65, and 3.69 for F5AM, F5MI, F6 AM, and F6MI, respectively. The maximum average IMFRFMFERDD values of IMF4 in the delta rhythm are 21.50, 20.15, 21.02, and 17.30, for F5AM, F5MI, F6AM, and F6MI, respectively. Additionally, the maximum average IMFRFHSERDD values of IMF4 in delta rhythm are 39,21, 39.14, 36.29, and 33.06 with time intervals of 500-600, 800-900, 800-900, and 500-600 ms, for F5AM, F5MI, F6AM, and F6MI, respectively. The results of this study, advance our understanding of meaningful feature information of F5MM, F5MI, F6MM, and F6MI, enabling the design of MI-based brain-computer interface assistive devices for disabled persons.

High prevalence of electroencephalographic frontal intermittent rhythmic delta activity in patients with moderately severe COVID-19.

INTRODUCTION: The aim of our study was to analyse EEG findings in patients with COVID-19 not requiring respiratory support. MATERIAL AND METHODS: We reviewed EEGs performed in patients with COVID-19 between April 2020 and May 2021 at the University Hospital in Kraków, Poland. Demographic and clinical data, including comorbid conditions, discharge disposition, survival, neuroimaging findings, laboratory results, and treatment was collected. RESULTS: The study included 44 EEGs performed in 35 patients (51.4% females), aged 65.5 ± 13.9 years. Almost all patients had at least one comorbidity, and one-third had one or more preexisting neurological conditions. Three quarters of EEGs were abnormal. The most frequent EEG finding was background slowing (16 patients; 45.7%). Frontal findings included frontally predominant rhythmic delta (FIRDA) in 10 (28.6%) patients and focal slowing in the left frontal lobe. Patients with abnormal EEG significantly more often required oxygen supplementation (p = 0.003) and were less likely to recover (p = 0.048). CONCLUSIONS AND CLINICAL IMPLICATIONS: Patients with COVID-19 infection may frequently manifest with an abnormal EEG. FIRDA seems to be a frequent EEG pattern in less severe cases of COVID-19 infection. Future studies are needed to establish whether COVID-19 infection increases the risk for FIRDA, and to investigate its pathogenesis.

Kinase signalling in excitatory neurons regulates sleep quantity and depth.

Progress has been made in the elucidation of sleep and wakefulness regulation at the neurocircuit level1,2. However, the intracellular signalling pathways that regulate sleep and the neuron groups in which these intracellular mechanisms work remain largely unknown. Here, using a forward genetics approach in mice, we identify histone deacetylase 4 (HDAC4) as a sleep-regulating molecule. Haploinsufficiency of Hdac4, a substrate of salt-inducible kinase 3 (SIK3)3, increased sleep. By contrast, mice that lacked SIK3 or its upstream kinase LKB1 in neurons or with a Hdac4S245A mutation that confers resistance to phosphorylation by SIK3 showed decreased sleep. These findings indicate that LKB1-SIK3-HDAC4 constitute a signalling cascade that regulates sleep and wakefulness. We also performed targeted manipulation of SIK3 and HDAC4 in specific neurons and brain regions. This showed that SIK3 signalling in excitatory neurons located in the cerebral cortex and the hypothalamus positively regulates EEG delta power during non-rapid eye movement sleep (NREMS) and NREMS amount, respectively. A subset of transcripts biased towards synaptic functions was commonly regulated in cortical glutamatergic neurons through the expression of a gain-of-function allele of Sik3 and through sleep deprivation. These findings suggest that NREMS quantity and depth are regulated by distinct groups of excitatory neurons through common intracellular signals. This study provides a basis for linking intracellular events and circuit-level mechanisms that control NREMS.