EEG Spectral Analysis Research Articles

Spectral quantitative and semi-quantitative EEG provide complementary information on the life-long effects of early childhood malnutrition on cognitive decline.

This study compares the complementary information from semi-quantitative EEG (sqEEG) and spectral quantitative EEG (spectral-qEEG) to detect the life-long effects of early childhood malnutrition on the brain. Resting-state EEGs (N = 202) from the Barbados Nutrition Study (BNS) were used to examine the effects of protein-energy malnutrition (PEM) on childhood and middle adulthood outcomes. sqEEG analysis was performed on Grand Total EEG (GTE) protocol, and a single latent variable, the semi-quantitative Neurophysiological State (sqNPS) was extracted. A univariate linear mixed-effects (LME) model tested the dependence of sqNPS and nutritional group. sqEEG was compared with scores on the Montreal Cognitive Assessment (MoCA). Stable sparse classifiers (SSC) also measured the predictive power of sqEEG, spectral-qEEG, and a combination of both. Multivariate LME was applied to assess each EEG modality separately and combined under longitudinal settings. The univariate LME showed highly significant differences between previously malnourished and control groups (p < 0.001); age (p = 0.01) was also significant, with no interaction between group and age detected. Childhood sqNPS (p = 0.02) and adulthood sqNPS (p = 0.003) predicted MoCA scores in adulthood. The SSC demonstrated that spectral-qEEG combined with sqEEG had the highest predictive power (mean AUC 0.92 ± 0.005). Finally, multivariate LME showed that the combined spectral-qEEG+sqEEG models had the highest log-likelihood (-479.7). This research has extended our prior work with spectral-qEEG and the long-term impact of early childhood malnutrition on the brain. Our findings showed that sqNPS was significantly linked to accelerated cognitive aging at 45-51 years of age. While sqNPS and spectral-qEEG produced comparable results, our study indicated that combining sqNPS and spectral-qEEG yielded better performance than either method alone, suggesting that a multimodal approach could be advantageous for future investigations. Based on our findings, a semi-quantitative approach utilizing GTE could be a valuable diagnostic tool for detecting the lasting impacts of childhood malnutrition. Notably, sqEEG has not been previously explored or reported as a biomarker for assessing the longitudinal effects of malnutrition. Furthermore, our observations suggest that sqEEG offers unique features and information not captured by spectral quantitative EEG analysis and could lead to its improvement.

Effects of conscious connected breathing on cortical brain activity, mood and state of consciousness in healthy adults

Breathwork as a means of inducing non-ordinary states of consciousness is gaining traction as a potential therapeutic modality. We examined the effects of breathwork (in the form of connected breathing) on electroencephalography (EEG) and mood in 20 healthy participants (aged between 23 and 39 years (female = 11, Mage = 29). In addition, to compare with other means of inducing non-ordinary states of consciousness, we assessed the subjective effects of breathwork using the 11 Dimension Altered State of Consciousness questionnaire. EEG spectral power analysis of eyes closed rest recordings before and after the breathwork session showed a decrease in delta (1–4 Hz) and theta (4–8 Hz) frequencies in frontotemporal and parietal regions, respectively no changes were seen in Alpha (9–12 Hz) and Beta (12–30 Hz) bands. However, after decomposing the beta waves in Beta 1 (12–15 Hz), Beta 2 (15–20 Hz), Beta 3 (20–30 Hz), decreases in power were observed across Beta1 and Beta 2 in parietotemporal regions. Notably, the spectral power in gamma increased in experienced practitioners. Scores on the Profile of Mood States questionnaire showed a reduction in negative affect (anger, tension, confusion, and depression) and an increase in esteem. Scores on the 11D-ASC scale indicated that subjective experiences during breathwork were similar to those after medium to high doses of psilocybin, suggesting the occurrence of experiences of mystical quality. Present results indicate that breathwork changes brain activity and mood, and induces mystical experiences. These results are promising and suggest that such techniques could be useful to improve mental well-being.

Electroencephalographic Characterization by Covariance Analysis in Men with Parkinson’s Disease Reveals Sex- and Age-Related Differences

Parkinson’s disease (PD) is the fastest growing neurological disease associated with ageing; its symptomatology varies between sexes. Several quantitative electroencephalography analyses have been used to study the early stages and progression of PD. In this study, we aim to characterize the brain activity by considering the five brainwaves in an eyes-closed resting state, using covariance wavelet analysis (CWA) of electroencephalographic records (EEGs) to analyze the influence of sex and age. To effectively eliminate artifacts from the EEG dataset and extract pertinent brain activity, we employ the inverse wavelet analysis. EEGs from men with PD were divided into two age groups (PD &lt; 60 and PD &gt; 60 years old) with their respective age-matched controls (CL). Brain activity patterns in frequency and power domains were analyzed with the CWA. Main frequency profiles, global wavelet curves, power anomalies, and power per brainwave were used to illustrate the CWA patterns. Power anomalies were used to generate anteroposterior power gradients. In PD &lt; 60 men, frequency and power for the α brainwave decreased, while the δ brainwave increased. The θ brainwave increased and was dominant over the α brainwave in PD &gt; 60 men. The anteroposterior power gradient in PD &lt; 60 men had a positive slope, but it was negative in CL. In both PD and CL &gt; 60 men, the anteroposterior gradient was negative. In PD &gt; 60 men, the θ brainwave increased and became dominant. Men with PD had twice the θ brainwave increase. An inverse relationship between α and δ brainwaves was detected in a PD &lt; 60 sex comparison. A conventional EEG spectral analysis using CWA indicated significant differences in brain activity patterns in the PD/CL groups affected by sex and age, yielding previously unknown information.

A hyperthermic seizure unleashes a surge of spreading depolarizations in Scn1a-deficient mice.

Spreading depolarization (SD) is a massive wave of cellular depolarization that slowly migrates across the brain gray matter. Cortical SD is frequently generated following brain injury, while less is understood about its potential contribution to genetic disorders of hyperexcitability, such as SCN1A-deficient epilepsy, in which febrile seizure often contributes to disease initiation. Here we report that spontaneous SD waves are predominant EEG abnormalities in the Scn1a-deficient mouse (Scn1a+/R1407X) and undergo sustained intensification following a single hyperthermic seizure. Chronic DC-band EEG recording detected spontaneous SDs, seizures, and seizure-SD complexes in Scn1a+/R1407X mice but not WT littermates. The SD events were infrequent, while a single hyperthermia-induced seizure robustly increased SD frequency over 4-fold during the initial postictal week. This prolonged neurological aftermath could be suppressed by memantine administration. Video, electromyogram, and EEG spectral analysis revealed distinct neurobehavioral patterns; individual seizures were associated with increased motor activities, while SDs were generally associated with immobility. We also identified a stereotypic SD prodrome, detectable over a minute before the onset of the DC potential shift, characterized by increased motor activity and bilateral EEG frequency changes. Our study suggests that cortical SD is a pathological manifestation in SCN1A-deficient epileptic encephalopathy.

Perceptual Integration Compensates for Attention Deficit in Elderly during Repetitive Auditory-Based Sensorimotor Task.

Sensorimotor integration (SI) brain functions that are vital for everyday life tend to decline in advanced age. At the same time, elderly people preserve a moderate level of neuroplasticity, which allows the brain's functionality to be maintained and slows down the process of neuronal degradation. Hence, it is important to understand which aspects of SI are modifiable in healthy old age. The current study focuses on an auditory-based SI task and explores: (i) if the repetition of such a task can modify neural activity associated with SI, and (ii) if this effect is different in young and healthy old age. A group of healthy older subjects and young controls underwent an assessment of the whole-brain electroencephalography (EEG) while repetitively executing a motor task cued by the auditory signal. Using EEG spectral power and functional connectivity analyses, we observed a differential age-related modulation of theta activity throughout the repetition of the SI task. Growth of the anterior stimulus-related theta oscillations accompanied by enhanced right-lateralized frontotemporal phase-locking was found in elderly adults. Their young counterparts demonstrated a progressive increase in prestimulus occipital theta power. Our results suggest that the short-term repetition of the auditory-based SI task modulates sensory processing in the elderly. Older participants most likely progressively improve perceptual integration rather than attention-driven processing compared to their younger counterparts.

0422 The relationship between EEG spectral analysis and pre-sleep cognitive arousal in insomnia disorder

Abstract Introduction The hyperarousal model suggests that insomnia is characterized by increased cortical, cognitive, and physiological arousal. However, the relationship between these domains of arousal remains insufficiently studied. The aim of the current observational study was to investigate pre-sleep cognitive arousal, cortical arousal during the night, and the relationship between these domains. Methods 109 patients with insomnia disorder (ID) and 109 age-and gender matched healthy controls (GSC) were investigated on two sleep laboratory nights. As a measure of cortical arousal, EEG spectral power was analyzed during NREM and REM sleep. In addition, participants completed the Pre-Sleep Arousal Scale (PSAS), which consists of a subscale for cognitive arousal (PSAS-CA) and another subscale for self-reported somatic arousal (PSAS-SA). The relationship between the subscale scores and EEG spectral power was calculated by multivariate and univariate analyses of variance. Results The total sample consisted of 218 participants. ID patients had a mean age of 44.7 years (± 10.6 years) and GSC had a mean age of 44.4 years (± 12.6 years). Both groups consisted of 78 women and 31 men.During NREM and REM sleep, patients with ID showed significantly increased spectral power in the EEG gamma band (NREM: p &amp;lt; .001; REM: p = .002). In addition, patients with ID showed significantly increased scores on the PSAS-SA (ID: M = 12.4, SD = 4.4; GSC: M = 10.7, SD = 3.3; t(216) = 3.34, p = .001, d = 0.45) and the PSAS-CA (ID: M = 18.3, SD = 7.2; GSC: M = 10.6, SD = 2.9; t(216) = 10.33, p &amp;lt; .001, d = 1.40). The PSAS-CA score was significantly associated with increased NREM (p = .001) and REM gamma power (p = .004), whereas PSAS-SA was associated with significant decreases in NREM (p &amp;lt; .001) and REM gamma power (p = .001). Conclusion In line with our hypothesis, patients with ID showed increased cortical and cognitive arousal. Moreover, there was a relationship between pre-sleep cognitive arousal and high-frequency EEG activity during the night. This might suggest that the latter is caused (at least in part) by pre-sleep worry and rumination. Support (if any)

Physiological Metrics of Surgical Difficulty and Multi-Task Requirement during Robotic Surgery Skills.

Previous studies in robotic-assisted surgery (RAS) have studied cognitive workload by modulating surgical task difficulty, and many of these studies have relied on self-reported workload measurements. However, contributors to and their effects on cognitive workload are complex and may not be sufficiently summarized by changes in task difficulty alone. This study aims to understand how multi-task requirement contributes to the prediction of cognitive load in RAS under different task difficulties. Multimodal physiological signals (EEG, eye-tracking, HRV) were collected as university students performed simulated RAS tasks consisting of two types of surgical task difficulty under three different multi-task requirement levels. EEG spectral analysis was sensitive enough to distinguish the degree of cognitive workload under both surgical conditions (surgical task difficulty/multi-task requirement). In addition, eye-tracking measurements showed differences under both conditions, but significant differences of HRV were observed in only multi-task requirement conditions. Multimodal-based neural network models have achieved up to 79% accuracy for both surgical conditions.

Resting-state EEG Predicts Cognitive Impairment in Parkinson’s Disease (P6-11.015)

<h3>Objective:</h3> To develop and evaluate an EEG-based assay to predict cognitive functions in Parkinson’s disease (PD) using resting-state EEG data. <h3>Background:</h3> Cognitive dysfunction is a prominent feature of PD. PD related cognitive impairment is usually diagnosed by neuropsychological testing; however, these tests are complex, cannot capture cognitive fluctuations in PD patients, and are not readily compatible with repeated measurements, real-time feedback, or closed-loop neuromodulation therapies. <h3>Design/Methods:</h3> We recorded a few minutes of resting-state EEG data from a few electrodes. Our approach optimized a data-driven, machine-learning technique called ‘Linear predictive coding EEG Algorithms for Parkinson’s disease’ (LEAD-PD) to predict cognitive measures from 100 PD and 49 control participants. We compared our EEG-based cognitive index with the Montreal Cognitive Assessment (MOCA), as well as with different cognitive domains from NIH Toolbox, using multiple cross-validation schemes and randomization tests. We also investigated the relationship between them with multiple regression models, compared our approach with traditional EEG-based features and measured robustness with data truncation tests. <h3>Results:</h3> We found a strong correlation (rho = 0.69, <i>p</i> value &lt; 0.001) between our proposed LEAD-PD cognitive index and the MOCA score using data from only 8 EEG electrodes. LEAD-PD index also strongly predicted other cognitive domains from the NIH toolbox (Dimensional Change Card Sort, Flanker Attention and Inhibitory Control, Picture Vocabulary Task, Pattern Completion Speed Processing, and the Picture Sequence Memory tests). Our approach was consistently more predictive than traditional EEG spectral analysis, yielded 80.44% accuracy (0.90 AUC, 79.52 % sensitivity, and 81.14% specificity) in detecting cognitive impairment, and extended to both PD and control participants. The relationship between our approach and the MOCA was nonlinear with an R² of 0.46 for quadratic regression models. <h3>Conclusions:</h3> LEAD-PD approach using resting-state EEG is computationally-efficient and capable of providing continuous real-time control and feedback, facilitating the diagnosis and monitoring of cognitive impairment in PD. <b>Disclosure:</b> An immediate family member of Dr. Uc has received personal compensation in the range of $500-$4,999 for serving as an officer or member of the Board of Directors for American Board of Pediatrics. Dr. Uc has received personal compensation in the range of $500-$4,999 for serving as an Editor, Associate Editor, or Editorial Advisory Board Member for Elsevier. The institution of Dr. Uc has received research support from Department of Veterans Affairs. The institution of Dr. Uc has received research support from Department of Defense. The institution of Dr. Uc has received research support from Michael J. Fox Foundation. The institution of an immediate family member of Dr. Uc has received research support from NIH. Dr. Anjum has nothing to disclose. Dr. Dasgupta has nothing to disclose. Dr. Narayanan has nothing to disclose.

Monitorización perioperatoria de la función cerebral, mucho más que «hipnometría»

The neural networks of the central nervous system have three possible natural states: wakefulness, REM sleep and Non-REM sleep. On 16 October 1846, a new brain state was artificially induced, which later became known as anaesthesia. Until 1995, this new state was mainly monitored using clinical signs, although as early as 1937 Gibbs and Lennox recommended the routine use of electroencephalogram (EEG) for this purpose.In 1996, the US Food and Drug Administration (FDA) approved the bispectral index (a dimensionless parameter calculated from the EEG using copyrighted, patented algorithms). This index made it possible for the first time to “quantify” hypnosis during anaesthesia in a simple way based on EEG. Subsequently, other “hypnometers” have been developed by different commercial firms.In the first decade of this century, anaesthesia monitoring has focused on the use of the spectrogram and conventional EEG, not only as hypnometers, but also as brain state monitors. In 2020, the PeriOperative Quality Initiative called for the EEG to be considered a fundamental monitoring tool, and recommended that anaesthesiologists be trained in the interpretation of EEG, both in its conventional form and as a spectrogram. Some monitors available in daily clinical practice display conventional EEG, spectrograms, and different parameters of EEG spectral analysis. We just have to learn how to interpret them.

On the relationship between EEG spectral analysis and pre-sleep cognitive arousal in insomnia disorder: towards an integrated model of cognitive and cortical arousal.

According to the hyperarousal model, insomnia is characterised by increased arousal in the cortical, cognitive, and physiological domains. However, the interaction between these arousal domains is poorly understood. The present observational case-control study aimed to investigate cortical arousal during the night, pre-sleep cognitive arousal and the relationship between these two domains. A total of 109 patients with insomnia disorder (ID) and 109 age-and gender matched healthy controls were investigated on two sleep laboratory nights. Electroencephalographic (EEG) spectral power during non-rapid eye movement (NREM) and REM sleep was analysed as a measure of cortical arousal. In addition, patients completed the Pre-Sleep Arousal Scale (PSAS), which consists of two subscales, one for cognitive arousal (PSAS-CA) and one for self-reported somatic arousal (PSAS-SA). The relationship between the subscale scores and EEG spectral power was calculated by multi- and univariate analyses of variance. During NREM and REM sleep, patients with ID showed significantly increased spectral power in the EEG gamma band. In addition, patients with ID showed significantly increased scores on both subscales of the PSAS. The PSAS-CA score was significantly associated with increased NREM and REM gamma power, whereas PSAS-SA was associated with decreases in NREM and REM gamma power. Consistent with our hypothesis, patients with ID showed increased cortical and cognitive arousal. Moreover, there was an association between these two arousal domains, which may indicate that cortical arousal during the night is (at least in part) elicited by pre-sleep worry and rumination.

Comparative characterization of 5XFAD and hAbetaSAA mouse models of familial AD

AbstractBackgroundThe failure of most clinical Alzheimer’s disease (AD) trials has been partially attributed to the lack of translatability of current AD mouse models to human patients. A recently developed model of familial AD (fAD), expressing Swedish, Arctic and Austrian mutations in App (hAbetaSAA), has been shown to be a useful amyloidogenic model which recapitulates many aspects of human AD, including plaque distribution and microglial transcriptional changes. Our aim is to further characterize the hAbetaSAA model and compare it to the widely used 5xFAD transgenic model.MethodMotion Sequencing (MoSeq) software was used to model the underlying structure of spontaneous behaviors recorded in an open field in hAbetaSAA and 5xFAD mice longitudinally from 10 to 18 months of age. Aged hAbetaSAA and 5xFAD brain tissue was used for spatial transcriptomic/proteomic profiling, performed by Nanostring’s GeoMx®, which allowed for quantification of gene and protein expression in plaque‐associated and non‐plaque‐associated regions of interest. A fluorophore‐conjugated amyloid antibody (Methoxy‐X04) was administered to cohorts of hAbetaSAA and 5xFAD prior to harvest at various ages. An additional fluorophore‐conjugated antibody (lectin Dylight®594) was administered to 19‐month‐old cohorts permitting visualization of cerebral amyloid angiopathy (CAA). Whole brains were sectioned/imaged using Serial Two‐Photon Tomography on the TissueCyte (TissueVision), creating indexed tissue sections and high‐resolution 3D models of each brain. Subsequent rounds of staining permitted characterization of disease‐associated microglia (DAM) and dystrophic neurites. An independent cohort was evaluated for EEG telemetry.ResultMoSeq revealed divergent behaviors of 5xFAD and hAbetaSAA mice suggesting differences in behavioral phenotypes of these two models. Preliminary GeoMx data shows upregulation of DAM genes localized to plaques in hAbetaSAA homozygotes as identified by RNA‐seq; correlating 5xFAD data is in progress. Further assessments of bulk RNA‐Seq, amyloid distribution, CAA burden and cortical EEG spectral analysis are underway.ConclusionComparison of hAbetaSAA and 5xFAD using innovative modes of assessment showcase hAbetaSAA as an amyloidogenic mouse model of fAD that aligns more closely with human than 5xFAD. This model is available for preclinical research with no licensing restrictions and is devoid of artifacts related to transgenic overexpression, positioning it as an improved mouse model for studying fAD mutations.

P117 A pilot study of a novel electrode system for brainwave acquisition during sleep: Tripolar Concentric Ring Electrodes

Abstract Introduction Tri-concentric ring electrodes (TCRE) evaluate current density underlying each electrode rather than a voltage difference between two conventionally placed electroencephalography (EEG) electrodes. TCRE signals are more focal and show improved signal-to-noise with markedly reduced electromyographic interference compared to conventional EEG. This pilot study is the first to evaluate sleep using TCRE and power spectral analysis of TCRE versus conventional EEG emulated (eEEG) recordings obtained from TCRE and the outer rings of paired electrodes. Method Twenty healthy sleepers (8 men, mean±SD age 27.8±9.6 y) completed a single overnight sleep study with a 9-hr sleep opportunity. Participants were set up for polysomnography recording using TCRE for brain activity (18 sites) and conventional gold-cup electrodes for eye movements, muscle activity, and heart rate. A fast Fourier transform using multitaper-based estimation was applied in 5-s epochs to calculate relative powers in delta, alpha, theta, sigma and beta frequency bands for eEEG and TCRE signals throughout sleep. Results At the Cz position, TCRE showed greater relative delta power and reduced beta powers across sleep stages compared to eEEG. For example, TCRE had higher delta activity during NREM stage 2 sleep than eEEG (mean [SD]; 89% [5.7] vs 64% [6]) and lower beta activity during wake (3.4% [2] vs 17.3% [7.9]). Ongoing analyses will compare outcomes across electrode locations. Conclusions Brain activity acquisition via TCRE may reduce artefact interference and potentially identify new markers during sleep that are associated with sleep quality, health, and functioning.

Elevated beta activity in the nighttime sleep and multiple sleep latency electroencephalograms of chronic insomnia patients.

To examine the 24-h hyperarousal hypothesis of insomnia using electroencephalographic (EEG) spectral analysis of overnight polysomnography (PSG) and daytime multiple sleep latency tests (MSLTs). Standard PSG and MSLT were recorded in 31 chronic insomniacs (CIs) (21 females, mean age 36.19) and in 21 normal controls (NCs) (18 females, mean age 34.76). EEG spectral analyses were conducted and relative power was obtained for each sleep stage during PSG and each session during MSLTs. Subsequently, CIs were subdivided based on sleep efficiency (SE < or ≥ 85%) or mean sleep latency (MSL) of MSLT (< or ≥ 15 min), and beta power was compared among NCs and CIs subgroups. General liner regression analyses of beta power and PSG parameters were conducted. CIs had significantly greater beta power in nighttime W, N1, N2, NREM, and in total overnight and in MSLT sessions compared with NCs. CIs with lower PSG-SE or longer MSLT-MSL showed higher beta power at nighttime. Compared with NCs, increased beta power was limited to CIs with lower PSG-SE or longer MSLT-MSL during MSLT sessions. In all subjects, total daytime beta was positively correlated to total overnight beta and MSL, total overnight beta was negatively related to SE. In CIs, total daytime beta and total overnight beta were positively correlated. Our results support the hypothesis of 24-h cortical hyperarousal in insomnia. We conclude that 24-h cortical hyperarousal is clearly present in insomnia and is greater in insomnia with objective findings.

Alternating hemiplegia of childhood: An electroclinical study of sleep and hemiplegia.

Alternating Hemiplegia of Childhood (AHC) is characterised by paroxysmal hemiplegic episodes and seizures. Remission of hemiplegia upon sleep is a clinical diagnostic feature of AHC. We investigated whether: 1) Hemiplegic events are associated with spectral EEG changes 2) Sleep in AHC is associated with clinical or EEG spectral features that may explain its restorative effect. We retrospectively performed EEG spectral analysis in five adults with AHC and twelve age-/gender-matched epilepsy controls. Five-minute epochs of hemiplegic episodes and ten-minute epochs of four sleep stages were selected from video-EEGs. Arousals were counted per hour of sleep. We found 1) hemispheric differences in pre-ictal and ictal spectral power (p = 0.034), during AHC hemiplegic episodes 2) 22% reduced beta power (p = 0.017) and 26% increased delta power (p = 0.025) during wakefulness in AHC versus controls. There were 98% more arousals in the AHC group versus controls (p = 0.0003). There are hemispheric differences in spectral power preceding hemiplegic episodes in adults with AHC, and sleep is disrupted. Spectral EEG changes may be a potential predictive tool for AHC hemiplegic episodes. Significantly disrupted sleep is a feature of AHC.

Gender specificities of neurodymanic processes and development of mental disorders with the HIV-infected

Objective. The study of gender specificities in adaptive transformation of regular neurodynamic (EEG) processes and also the development of maladaptation and mental disorders among men and women with HIV infection.Materials and methods. The research includes 46 men and 54 women, aged 18 and 60, on follow-up care in St. Petersburg Center of AIDS who didn’t get antiretroviral therapy. Clinical infectious, clinical psychiatric, experimental psychological, instrumental functional diagnostics (EEG). To describe neurodymanic processes, EEG spectral analysis was applied, as well as based on graph theory analysis of the structure of interaction (mutual transition of opposite) between wave components of basic EEG rhythms.Results and discussion. In the group of HIV-infected women the rate of mental illness is higher than in the men’s one. It is revealed the men and women have progressing frequency-dependent EEG changes due to neurotic, stress-related and organic mental disorders. Developing of HIV-encephalopathy among the women is accompanied by the growth of spectral power fluctuation in beta range and among the men — in alfa range of EEG frequency. These changes were most pronounced in the frontal and posttemporal areas both with the men and women that may reflect growing pathological process in structures of limbic system. Comparing to men, HIVinfected women have a higher EEG organization, characterized by high-frequency (beta) core formation of functional EGG rhythm interaction, representing decrease in the plasticity level of self-regulation process and developing stable pathological condition.Conclusion. Тhere are gender differences of psychic reaction on HIV infection, thus, it is necessary to have a personalized approach to patient care, taking into account a higher demand of women in psychocorrectional and psychopharmacological help.

Exploration of cortical inhibition and habituation in insomnia: Based on CNV and EEG.

Cognitive dysfunction with abnormal cortical inhibition and habituation has frequently been found in patients with insomnia. And the so-called contingent negative variation (CNV) and EEG power spectral density (FFT) may be the best choice to explore the underlining pathophysiology. We used polysomnography (PSG) to record such objective PSG parameters. The amplitudes, latencies, areas of different CNV components such as oCNV, iCNV and tCNV, PINV have been selected and analyzed. Behavioral data such as manual reaction time (RT) has been analyzed. Spectral analysis was performed with fast Fourier transformation (FFT) on all channels to make a spectral analyses of EEG datas. The A-latency located in CZ or PZ were statistically longer in insomnia group than control group, the iCNV-latency located in insomnia group were statistically shorter than control group. The iCNV-amplitude located in insomnia group was lower than control group. The oCNV-amplitude or the tCNV-amplitude located in insomnia group was higher than control group. The oCNV-square, tCNV-square, or PINV-square located in insomnia group were significant larger than control group. β1 or β2 activity distributed in bilateral hemisphere were significantly increased in insomnia group than control group with different distributions. Our study revealed varied attentional and information processing in insomnia patients. Above all, we made a hypothesis with ceiling theory: Frontal lobe play an important role in maintaining cognitive processing, which needs much more energy consumption and leads to decreased fast EEG activity in frontal cortex, which contributes to reduced cortical inhibition, represented as abnormal CNV.

Decoding brain activities of literary metaphor comprehension: An event-related potential and EEG spectral analysis.

Novel metaphors in literary texts (hereinafter referred to as literary metaphors) seem to be more creative and open-ended in meaning than metaphors in non-literary texts (non-literary metaphors). However, some disagreement still exists on how literary metaphors differ from non-literary metaphors. Therefore, this study explored the neural mechanisms of literary metaphors extracted from modern Chinese poetry by using the methods of Event-Related Potentials (ERPs) and Event-Related Spectral Perturbations (ERSPs), as compared with non-literary conventional metaphors and literal expressions outside literary texts. Forty-eight subjects were recruited to make the semantic relatedness judgment after reading the prime-target pairs in three linguistic conditions. According to the ERPs results, the earliest differences were presented during the time window of P200 component (170–260 ms) in the frontal and central areas, with the amplitude of P200 for literary metaphors more positive than the other two conditions, reflecting the early allocation of attention and the early conscious experience of the experimental stimuli. Meanwhile, significant differences were presented during the time window of N400 effect (430–530 ms), with the waveform of literary metaphors more negative than others in the frontal and central topography of scalp distributions, suggesting more efforts in retrieving conceptual knowledge for literary metaphors. The ERSPs analysis revealed that the frequency bands of delta and theta were both involved in the cognitive process of literary metaphor comprehension, with delta band distributed in the frontal and central scalp and theta band in parietal and occipital electrodes. Increases in the two power bands during different time windows provided extra evidences that the processing of literary metaphors required more attention and effort than non-literary metaphors and literal expressions in the semantic related tasks, suggesting that the cognitive process of literary metaphors was distinguished by different EEG spectral patterns.

Effects of Treatment of Sleep Disordered Breathing on Sleep Macro- and Micro-Architecture in Children with Down Syndrome.

Background: Children with Down syndrome (DS) are at increased risk of obstructive sleep disordered breathing (SDB), which is associated with intermittent hypoxia and sleep disruption affecting daytime functioning. We aimed to examine the effects of treatment of SDB on sleep quality and daytime functioning in children with DS. Methods: Children with DS and SDB (n = 24) completed a baseline and follow-up overnight polysomnographic (PSG) study 22 ± 7 months (mean ± SD) later. Sleep micro-architecture was assessed using EEG spectral analysis, and parents completed a number of questionnaires assessing sleep, behavior, daytime functioning, and quality of life (QOL). Results: A total of nine children (38%) were treated. At baseline, the treated group had more severe SDB compared to the untreated group. SDB severity was significantly improved from 40.3 ± 46.9 events/h to 17.9 ± 26.9 events/h (p < 0.01) at follow up in children who were treated. There were no significant differences in sleep macro-architecture parameters from baseline to follow up in either the treated or untreated group. Sleep micro-architecture was not different between studies in the treated group, however this tended to improve in the untreated group, particularly in REM sleep. Daytime functioning and behavior were not different between the studies in either group, however, QOL improved after treatment. Conclusions: Our study identified that treatment of SDB improves severity of the disease as defined by PSG, and this was associated with parental reports of improved QOL, despite treatment having no demonstrable impacts on sleep quality, behavior, or daytime functioning.

EEG Power Spectrum: Errors and Application Practice (lecture three). Spectral analysis in the study of variability of EEG rhythms

The traditional EEG spectral analysis is not suitable for the study of dynamic processes in the brain, since the size of the recording segments required for plotting the spectrum graphs should be significantly longer than the physiological variability of the electroencephalogram itself. For these purposes, special methodological approaches have been developed: dynamic observation of EEG rhythms using the Berg-Fourier analysis method and various options for plotting trends of frequency and amplitude values of brain potentials. Almost no one knows the real significance of fluctuations in the frequency of the dominant EEG rhythm, since in fact there was no instrument for studying this phenomenon in dynamics. In panic attacks with a high level of anxiety, the opposite picture is observed, a pathological decrease in the severity of fluctuations in the frequency of the alpha rhythm.

Watching Nature Videos Promotes Physiological Restoration: Evidence From the Modulation of Alpha Waves in Electroencephalography.

Various lines of evidence have shown that nature exposure is beneficial for humans. Despite several empirical findings pointing out to cognitive and emotional positive effects, most of the evidence of these effects are correlational, and it has been challenging to identify a cause-effect relationship between nature exposure and cognitive and emotional benefits. Only few of the published studies use psychophysiological methods to assess the biological correlates of these positive effects. Establishing a connection between human physiology and contact with natural settings is important for identifying cause-effect relationships between exposure to natural environments and the positive effects commonly reported in connection to nature exposure. In the present study, we recorded physiological indexes of brain activity (electroencephalography) and sympathetic nervous system (electrodermal activity), while the participants were presented with a series of videos displaying natural, urban, or neutral (non-environmental, computerized) scenes. Participants rated the scenes for their perceived relaxing value, and after each experimental condition, they performed a cognitive task (digit span backward). Participants rated natural videos as the most relaxing. Spectral analyses of EEG showed that natural scenes promoted alpha waves, especially over the central brain. The results suggest that experiencing natural environments virtually produces measurable and reliable brain activity markers which are known to be related to restorative processes.