Quantitative EEG Research Articles

Improving Neuroplasticity through Robotic Verticalization Training in Patients with Minimally Conscious State: A Retrospective Study.

In disorders of consciousness, verticalization is considered an effective type of treatment to improve motor and cognitive recovery. Our purpose is to investigate neurophysiological effects of robotic verticalization training (RVT) in patients with minimally conscious state (MCS). Thirty subjects affected by MCS due to traumatic or vascular brain injury, attending the intensive Neurorehabilitation Unit of the IRCCS Neurolesi (Messina, Italy), were included in this retrospective study. They were equally divided into two groups: the control group (CG) received traditional verticalization with a static bed and the experimental group (EG) received advanced robotic verticalization using the Erigo device. Each patient was evaluated using both clinical scales, including Levels of Cognitive Functioning (LCF) and Functional Independence Measure (FIM), and quantitative EEG pre (T0) and post each treatment (T1). The treatment lasted for eight consecutive weeks, and sessions were held three times a week, in addition to standard neurorehabilitation. In addition to a notable improvement in clinical parameters, such as functional (FIM) (p < 0.01) and cognitive (LCF) (p < 0.01) outcomes, our findings showed a significant modification in alpha and beta bands post-intervention, underscoring the promising effect of the Erigo device to influence neural plasticity and indicating a noteworthy difference between pre-post intervention. This was not observed in the CG. The observed changes in alpha and beta bands underscore the potential of the Erigo device to induce neural plasticity. The device's custom features and programming, tailored to individual patient needs, may contribute to its unique impact on brain responses.

Effects of Phytoncide Fragrance on Resting-State Brain Activity in Mild Cognitive Impairment: A Randomized Double-Blind Controlled Study.

Introduction: The therapeutic potential of phytoncide fragrances may be optimal for patients with mild cognitive impairment (MCI) that display complex symptomatology. This study aimed to explore the clinical value of phytoncide by evaluating its electrophysiological effects in patients with MCI. Materials and Methods: This was a double-blind, randomized controlled trial. A total of 24 community-dwelling patients were randomly assigned to either a phytoncide or no-odor group. Participants wore a dental mask, for 30 min at rest that had either the fragrance stimulus or water added to it. The quantitative electroencephalography (EEG) during the resting state was recorded before and after a single intervention. Results: There were significant interaction effects in absolute EEG-power values in the occipital (F = 6.52, p = 0.018) and parietal (F = 5.41, p = 0.030) left hemisphere at β frequency. Phytoncide odor significantly decreased low and high β activity in the occipital (corrected p = 0.009) and parietal (corrected p = 0.047) left hemisphere, respectively. In source localization, phytoncide odor significantly decreased deep source activation in the left inferior and middle frontal gyri at β 2 frequency band compared with the no-odor group (threshold = 4.25, p < 0.05). Conclusions: Reductions in β, indicative of anxiety, depression, and stress, suggest relief from emotion-related symptoms that are common in patients with MCI. Trial Registration: Clinical Trials Registry Korea (registration: KCT0007317).

Sleep alterations as a function of 88 health indicators

BackgroundAlterations in sleep have been described in multiple health conditions and as a function of several medication effects. However, evidence generally stems from small univariate studies. Here, we apply a large-sample, data-driven approach to investigate patterns between in sleep macrostructure, quantitative sleep EEG, and health.MethodsWe use data from the MrOS Sleep Study, containing polysomnography and health data from a large sample (N = 3086) of elderly American men to establish associations between sleep macrostructure, the spectral composition of the electroencephalogram, 38 medical disorders, 2 health behaviors, and the use of 48 medications.ResultsOf sleep macrostructure variables, increased REM latency and reduced REM duration were the most common findings across health indicators, along with increased sleep latency and reduced sleep efficiency. We found that the majority of health indicators were not associated with objective EEG power spectral density (PSD) alterations. Associations with the rest were highly stereotypical, with two principal components accounting for 85–95% of the PSD-health association. PC1 consists of a decrease of slow and an increase of fast PSD components, mainly in NREM. This pattern was most strongly associated with depression/SSRI medication use and age-related disorders. PC2 consists of changes in mid-frequency activity. Increased mid-frequency activity was associated with benzodiazepine use, while decreases were associated with cardiovascular problems and associated medications, in line with a recently proposed hypothesis of immune-mediated circadian demodulation in these disorders. Specific increases in sleep spindle frequency activity were associated with taking benzodiazepines and zolpidem. Sensitivity analyses supported the presence of both disorder and medication effects.ConclusionsSleep alterations are present in various health conditions.

Quantitative EEG and prediction of outcome in neonatal encephalopathy: a review.

Electroencephalogram (EEG) is an important biomarker for neonatal encephalopathy (NE) and has significant predictive value for brain injury and neurodevelopmental outcomes. Quantitative analysis of EEG involves the representation of complex EEG data in an objective, reproducible and scalable manner. Quantitative EEG (qEEG) can be derived from both a limited channel EEG (as available during amplitude integrated EEG) and multi-channel conventional EEG. It has the potential to enable bedside clinicians to monitor and evaluate details of cortical function without the necessity of continuous expert input. This is particularly useful in NE, a dynamic and evolving condition. In these infants, continuous, detailed evaluation of cortical function at the bedside is a valuable aide to management especially in the current era of therapeutic hypothermia and possible upcoming neuroprotective therapies. This review discusses the role of qEEG in newborns with NE and its use in informing monitoring and therapy, along with its ability to predict imaging changes and short and long-term neurodevelopmental outcomes. IMPACT: Quantitative representation of EEG data brings the evaluation of continuous brain function, from the neurophysiology lab to the NICU bedside and has a potential role as a biomarker for neonatal encephalopathy. Clinical and research applications of quantitative EEG in the newborn are rapidly evolving and a wider understanding of its utility is valuable. This overview summarizes the role of quantitative EEG at different timepoints, its relevance to management and its predictive value for short- and long-term outcomes in neonatal encephalopathy.

Objective sleep quality predicts subjective sleep ratings

In both clinical and observational studies, sleep quality is usually assessed by subjective self-report. The literature is mixed about how accurately these self-reports track objectively (e.g. via polysomnography) assessed sleep quality, with frequent reports of little to no association. However, previous research on this question focused on between-subject designs, which may be confounded by trait-level variables. In the current study, we used the novel Budapest Sleep, Experiences and Traits Study (BSETS) dataset to investigate if within-subject differences in subjectively reported sleep quality are related to sleep macrostructure and quantitative EEG variables assessed using a mobile EEG headband. We found clear evidence that self-reported sleep quality in the morning is influenced by within-subject variations in sleep onset latency, wake after sleep onset, total sleep time, and sleep efficiency. These effects were replicated if detailed sleep composition metrics (percentage and latency of specific vigilance states) or two alternative measures of subjective sleep quality were used instead. We found no effect of the number of awakenings or relative EEG delta and sigma power. Between-subject effects (relationships between individual mean values of sleep metrics and subjective sleep quality) were also found, highlighting that analyses focusing only on these may be erroneous. Our findings show that while previous investigations of this issue may have been confounded by between-subject effects, objective sleep quality is indeed reflected in subjective sleep ratings.

Reduced Interhemispheric Coherence and Cognition in Children with Fetal Alcohol Spectrum Disorder (FASD)-A Quantitative EEG Study.

Magnetic resonance imaging in fetal alcohol spectrum disorder (FASD) children showed altered connectivity, suggesting underlying deficits in networks, which may be related to cognitive outcome. Functional connectivity has been of interest in neurophysiological research with quantitative electroencephalography (QEEG) as useful tool for measuring pathology, not detectable by normal EEG. The aim of this study was to investigate differences in the EEG interhemispheric coherence (ICoh) in children diagnosed with FASD compared with healthy controls and to relate the results to cognitive scores. Analysis of ICoh in 81 FASD children (4-Digit Code) compared with 31 controls. The children underwent cognitive assessment, and EEG was performed and used for analysis. Group comparisons and analysis of covariance interaction models were used to test for differences between FASD and controls but also to look for differences between FASD subgroups. Significant findings were correlated to cognitive scores. Lower ICoh was found in the frontal and temporal derivations in the FASD group. When comparing FASD subgroups, children with fetal alcohol syndrome had lower ICoh occipital. Reduced ICoh in the temporal alpha band was correlated with lower performance IQ in the FASD group. Our findings could imply hypoconnectivity between the hemispheres with impact on cognition. We suggest that EEG coherence analysis could be a sensitive parameter in the detection of electrophysiological abnormalities in FASD with possible clinical relevance. These results may indicate that QEEG could be used as biomarker for FASD. However, further research is needed to determine the role of QEEG analysis in the diagnosis of FASD.

The Effect of Alpha Binaural Beats Auditory Stimulation on Quantitative Electroencephalography (QEEG) and Pain Intensity among Tension-Type Headache Patients

Tension-type headaches, the most prevalent primary headaches affecting 2-5% of the population, significantly impact sufferers' well-being. These headaches present a persistent health challenge, constituting a considerable portion of neurologist outpatient visits. Effectively managing tension-type headaches remains challenging and can lead to notable morbidity if untreated. Treatment typically involves prophylactic pharmacological therapy alongside non-pharmacological interventions. Among non-medication therapies, brainwave entrainment using binaural beats emerges as a promising option for chronic headaches. This experimental research employed a pre-test and post-test design over a 5-day period (30 minutes daily) to assess Alpha Binaural Beats Auditory stimulation's impact on the QEEG pattern and pain intensity reduction in tension-type headache patients. The study, involving 32 participants, revealed a statistically significant increase in relative alpha wave power (p-value of 0.000) and a significant decrease in relative beta wave power (p-value of 0.045) after exposure to alpha binaural beats. Additionally, the Numerical Rating Scale (NRS) recorded a statistically significant decrease in pain intensity (p-value of 0.000). These findings suggest that Alpha binaural beats contribute to increased alpha wave activity, decreased beta wave activity in the QEEG pattern, and a substantial reduction in pain intensity associated with tension-type headaches. However, further research is needed to explore cumulative effects and long-term sustainability in tension-type headache patients, advancing our understanding and application of this therapy.

QEEG indices in traumatic brain injury - insights from the CAPTAIN RTMS trial.

This secondary analysis of the CAPTAIN-RTMS trial data focused on the significance of quantitative electroencephalography (qEEG) indices as indicators of recovery in patients with traumatic brain injury (TBI). By focusing on the delta alpha ratio (DAR), delta theta/alpha beta ratio (DTABR), and theta beta ratio (TBR), this study explored the shifts in brainwave activity as a response to an integrative treatment regimen of repetitive transcranial magnetic stimulation (rTMS) combined with the neurotrophic agent Cerebrolysin. Findings revealed significant increases in DAR and DTABR, suggesting changes in neurophysiological dynamics after treatment. However, variations in TBR were inconclusive in providing clear electrophysiological insights. These results indicate that further research is necessary to describe and understand the underlying mechanisms of brain recovery and to develop refined treatment frameworks for patients with TBI.

Neurophysiological biomarkers of speech-in-competition performance under different conditions of attentional load

A body of research has identified a complex integration of perceptual and cognitive processes that can modulate comprehension of speech-in-competition (SIC). However, it is not well understood how the neurophysiological correlates associated with SIC performance vary under different conditions of attentional load. Here, we analyzed the neurophysiological correlates of a SIC task using variations in masker type (spatialization, gender, language), target-to-masker ratios (TMRs), and presence of a simultaneous working memory (WM) task to manipulate attentional load during SIC performance. We used a counter-balanced block design to record EEG in each condition in 15 undergraduate young adults without hearing difficulties. SIC was assessed using the spatial release from masking task in the PART digital application. Behavioral results indicated significant differences in accuracy depending on TMR across types of maskers. We did not observe behavioral differences in SIC performance associated with the inclusion of a parallel WM task. Quantitative EEG showed a series of potential EEG biomarkers that can complement behavioral measurement in discriminating different attentional load conditions of SIC performance. These post hoc observations are discussed in relation to the extant literature and will be further investigated in future work.

Deciphering the Mysteries of Aromatic Incentive of Lemongrass Essential Oil Inhalation on Brain Activities in Healthy Adults

With the rapid advancement in brain science and imaging technology, there is a growing interest in investigating the connection between aromatherapy and its effects on the brain. This study employs Quantitative Electroencephalography (QEEG) to examine the impacts of exposure to the fragrance of lemongrass essential oil (LEO) on specific brain regions. The objective is to assess the influence of inhaling the scent of LEO on EEG patterns in awake, healthy adult females using power spectral analysis. In this experimental study, 30 healthy adult female participants were exposed to a water mist as a control after baseline recordings. Subsequently, participants inhaled LEO aromatic mist diffused into the room air, and their brain activity was recorded. Data from specific scalp electrode readings were analyzed using the Wilcoxon Matched-Pairs Signed Rank Test. The results revealed a significant increase in the relative power of alpha waves in the prefrontal, frontal and occipital regions, accompanied by heightened theta power and decreased beta power. These results suggests that the inhalation of LEO oil modulates brainwave activities, inducing relaxing effects on the brain.

Construction of machine learning models for recognizing comorbid anxiety in epilepsy patients based on their clinical and quantitative EEG features

BackgroundThis study aimed to construct prediction models for the recognizing of anxiety disorders (AD) in patients with epilepsy (PWEs) by combining clinical features with quantitative electroencephalogram (qEEG) features and using machine learning (ML). MethodsNineteen clinical features and 20-min resting-state EEG were collected from 71 PWEs comorbid with AD and another 60 PWEs without AD who met the inclusion-exclusion criteria of this study. The EEG were preprocessed and 684 Phase Locking Value (PLV) and 76 Lempel–Ziv Complexity (LZC) features on four bands were extracted. The Fisher score method was used to rank all the derived features. We constructed four models for recognizing AD in PWEs, whether PWEs based on different combinations of features using eXtreme gradient boosting (XGboost) and evaluated these models using the five-fold cross-validation method. ResultsThe prediction model constructed by combining the clinical, PLV, and LZC features showed the best performance, with an accuracy of 96.18%, precision of 94.29%, sensitivity of 98.33%, F1-score of 96.06%, and Area Under the Curve (AUC) of 0.96. The Fisher score ranking results displayed that the top ten features were depression, educational attainment, α_P3LZC, α_T6-PzPLV, α_F7LZC, β_Fp2-O1PLV, θ_T4-CzPLV, θ_F7-PzPLV, α_Fp2LZC, and θ_T4-PzPLV. ConclusionsThe model, constructed by combining the clinical and qEEG features PLV and LZC, efficiently identified the presence of AD comorbidity in PWEs and might have the potential to complement the clinical diagnosis. Our findings suggest that LZC features in the α band and PLV features in Fp2-O1 may be potential biomarkers for diagnosing AD in PWEs.

Quantitative EEG for the Monitoring of Walking Recovery in Chronic Stroke Patients Receiving Action Observation Training

The current study aimed to evaluate the effects of action observation on the walking ability and oscillatory brain activity of chronic stroke patients. Fourteen chronic stroke patients were allocated randomly to the action observation (AO) or sham observation (SO) groups. Both groups received 12 sessions of intervention. Each session composed of 12 min of observational training, which depicted exercises for the experimental group but nature pictures for the sham group and 40 min of occupational therapy, which was the same for the both groups. Walking ability was assessed by a motion analysis system and brain activity was monitored using quantitative electroencephalography (QEEG) before and after the intervention. Brain asymmetry at alpha frequency, the percentage of stance phase, and step length showed significant changes in the AO group. Only the change in global alpha power was significantly correlated with the change in velocity after the intervention in AO group. Despite more improvements in walking and brain activity of patients in the AO group, our study failed to show significant correlations between the brain activity changes and functional improvements after the intervention, which might be mainly due to the small sample size in our study. Trial registration: IRCT20181014041333N1

Single-channel qEEG characteristics distinguish delirium from no delirium, but not postoperative from non-postoperative delirium

ObjectiveThis exploratory study examined quantitative electroencephalography (qEEG) changes in delirium and the use of qEEG features to distinguish postoperative from non-postoperative delirium. MethodsThis project was part of the DeltaStudy, a cross-sectional,multicenterstudy in Intensive Care Units (ICUs) and non-ICU wards. Single-channel (Fp2-Pz) four-minutes resting-state EEG was analyzed in 456 patients. After calculating 98 qEEG features per epoch, random forest (RF) classification was used to analyze qEEG changes in delirium and to test whether postoperative and non-postoperative delirium could be distinguished. ResultsAn area under the receiver operatingcharacteristic curve (AUC) of 0.76 (95% Confidence Interval (CI) 0.71–0.80) was found when classifying delirium with a sensitivity of 0.77 and a specificity of 0.63 at the optimal operating point. The classification of postoperative versus non-postoperative delirium resulted in an AUC of 0.50 (95%CI 0.38–0.61). ConclusionsRF classification was able to discriminate delirium from no delirium with reasonable accuracy, while also identifying new delirium qEEG markers like autocorrelation and theta peak frequency. RF classification could not distinguish postoperative from non-postoperative delirium. SignificanceSingle-channel EEG differentiates between delirium and no delirium with reasonable accuracy. We found no distinct EEG profile for postoperative delirium, which may suggest that delirium is one entity, whether it develops postoperatively or not.

Quantitative Electroencephalography in Children With Autism Spectrum Disorders

The goal of this study is to compare the brain connectivity patterns of autistic patients with those of children who are developing normally and analyzing quantitative electroencephalography in children with autism. The study included 50 children who were developing normally and 60 preschoolers who met the DSM-V criteria for autism spectrum disorder. Routine and quantitative electroencephalography were carried out on each subject, as well as a Childhood Autism Rating Scale. The electroencephalograms of 76.67% of autistic children were normal; 6.67% showed focal changes, and 16.67% showed generalized changes. While the alpha power in the central and temporal areas is significantly lower in autistic children, it is unchanged in the frontal and parieto-occipital regions. Children with autism have significantly higher absolute delta and theta band activity both globally and locally. It was shown that the total and regional absolute delta and theta power activity had a significant positive correlation with the disease severity score. Quantitative electroencephalography is a more effective tool for assessing and diagnosing children with autism spectrum disorder because it shows abnormalities in all autistic children. A correlation exists between the quantitative electroencephalography data and the disease severity score.

Identification of Concussion Subtypes Based on Intrinsic Brain Activity

The identification of brain activity-based concussion subtypes at time of injury has the potential to advance the understanding of concussion pathophysiology and to optimize treatment planning and outcomes. To investigate the presence of intrinsic brain activity-based concussion subtypes, defined as distinct resting state quantitative electroencephalography (qEEG) profiles, at the time of injury. In this retrospective, multicenter (9 US universities and high schools and 4 US clinical sites) cohort study, participants aged 13 to 70 years with mild head injuries were included in longitudinal cohort studies from 2017 to 2022. Patients had a clinical diagnosis of concussion and were restrained from activity by site guidelines for more than 5 days, with an initial Glasgow Coma Scale score of 14 to 15. Participants were excluded for known neurological disease or history of traumatic brain injury within the last year. Patients were assessed with 2 minutes of artifact-free EEG acquired from frontal and frontotemporal regions within 120 hours of head injury. Data analysis was performed from July 2021 to June 2023. Quantitative features characterizing the EEG signal were extracted from a 1- to 2-minute artifact-free EEG data for each participant, within 120 hours of injury. Symptom inventories and days to return to activity were also acquired. From the 771 participants (mean [SD] age, 20.16 [5.75] years; 432 male [56.03%]), 600 were randomly selected for cluster analysis according to 471 qEEG features. Participants and features were simultaneously grouped into 5 disjoint subtypes by a bootstrapped coclustering algorithm with an overall agreement of 98.87% over 100 restarts. Subtypes were characterized by distinctive profiles of qEEG measure sets, including power, connectivity, and complexity, and were validated in the independent test set. Subtype membership showed a statistically significant association with time to return to activity. In this cohort study, distinct subtypes based on resting state qEEG activity were identified within the concussed population at the time of injury. The existence of such physiological subtypes supports different underlying pathophysiology and could aid in personalized prognosis and optimization of care path.

Effect of the COVID-19 Pandemic on Resting-State Brain Activity in Individuals with Tinnitus.

This study looked at the possible effect of the COVID-19 pandemic on individuals who came to our clinic seeking relief from tinnitus. The performance of the subjects during the COVID-19 pandemic was compared with similar individuals who came to our clinic before the pandemic began. The study involved 50 adults with chronic tinnitus, made up of a study group (24 subjects tested during the COVID-19 pandemic of 2020-2021) and a control group before the pandemic began (26 subjects tested from 2013 to 2017). None of the 24 reported having contracted COVID-19. Data collection involved the Tinnitus Handicap Inventory (THI) questionnaire, audiological tests, and quantitative electroencephalography (qEEG). In terms of THI scores, there were no statistically significant differences between the two groups. However, with regard to qEEG, some changes were observed, with significant decreases in alpha and beta band activity in the study group compared to the control group, particularly over the auditory cortex. We conclude that COVID-19 did not have a discernible impact on the general well-being of individuals with tinnitus. However, it did appear to alter brain activity, specifically in the alpha and beta bands over the auditory cortex, and these reults warrant further investigation.

Use of Quantitative Electroencephalography to Inform Age- and Sex-Related Differences in NMDA Receptor Function Following MK-801 Administration.

Sex- and age-related differences in symptom prevalence and severity have been widely reported in patients with schizophrenia, yet the underlying mechanisms contributing to these differences are not well understood. N-methyl-D-aspartate (NMDA) receptor hypofunction contributes to schizophrenia pathology, and preclinical models often use NMDA receptor antagonists, including MK-801, to model all symptom clusters. Quantitative electroencephalography (qEEG) represents a translational approach to measure neuronal activity, identify targetable biomarkers in neuropsychiatric disorders and evaluate possible treatments. Abnormalities in gamma power have been reported in patients with schizophrenia and correspond to psychosis and cognitive impairment. Further, as gamma power reflects cortical glutamate and GABA signaling, it is highly sensitive to changes in NMDA receptor function, and NMDA receptor antagonists aberrantly increase gamma power in rodents and humans. To evaluate the role of sex and age on NMDA receptor function, MK-801 (0.03-0.3 mg/kg, SC) was administered to 3- and 9-month-old male and female Sprague-Dawley rats that were implanted with wireless EEG transmitters to measure cortical brain function. MK-801-induced elevations in gamma power were observed in 3-month-old male and female and 9-month-old male rats. In contrast, 9-month-old female rats demonstrated blunted maximal elevations across a wide dose range. Importantly, MK-801-induced hyperlocomotor effects, a common behavioral screen used to examine antipsychotic-like activity, were similar across all groups. Overall, sex-by-age-related differences in gamma power support using qEEG as a translational tool to evaluate pathological progression and predict treatment response across a heterogeneous population.

EEG Frequency Correlates with α2-Receptor Density in Parkinson's Disease.

Increased theta and delta power and decreased alpha and beta power, measured with quantitative electroencephalography (EEG), have been demonstrated to have utility for predicting the development of dementia in patients with Parkinson's disease (PD). Noradrenaline modulates cortical activity and optimizes cognitive processes. We claim that the loss of noradrenaline may explain cognitive impairment and the pathological slowing of EEG waves. Here, we test the relationship between the number of noradrenergic α2 adrenoceptors and changes in the spectral EEG ratio in patients with PD. We included nineteen patients with PD and thirteen healthy control (HC) subjects in the study. We used positron emission tomography (PET) with [11C]yohimbine to quantify α2 adrenoceptor density. We used EEG power in the delta (δ, 1.5-3.9 Hz), theta (θ, 4-7.9 Hz), alpha (α, 8-12.9 Hz) and beta (β, 13-30 Hz) bands in regression analyses to test the relationships between α2 adrenoceptor density and EEG band power. PD patients had higher power in the theta and delta bands compared to the HC volunteers. Patients' theta band power was inversely correlated with α2 adrenoceptor density in the frontal cortex. In the HC subjects, age was correlated with, and occipital background rhythm frequency (BRF) was inversely correlated with, α2 adrenoceptor density in the frontal cortex, while occipital BRF was inversely correlated with α2 adrenoceptor density in the thalamus. The findings support the claim that the loss or dysfunction of noradrenergic neurotransmission may relate to the parallel processes of cognitive decline and EEG slowing.

Synchronous monitoring of brain-heart electrophysiology using heart rate variability coupled with rapid quantitative electroencephalography in orthostatic hypotension patients with α-synucleinopathies: Rapid prediction of orthostatic hypotension and preliminary exploration of brain stimulation therapy.

In α-synucleinopathies, the dysfunction of the autonomic nervous system which typically manifests as orthostatic hypotension (OH) often leads to severe consequences and poses therapeutic challenges. This study aims to discover the brain-cardiac electrophysiological changes in OH patients with α-synucleinopathies using the rapid quantitative electroencephalography (qEEG) coupled with heart rate variability (HRV) technique to identify rapid, noninvasive biomarkers for early warning and diagnosis, as well as shed new light on complementary treatment approaches such as brain stimulation targets. In this study, 26 subjects of α-synucleinopathies with OH (α-OH group), 21 subjects of α-synucleinopathies without OH (α-NOH group), and 34 healthy controls (control group) were included from September 2021 to August 2023 (NCT05527067). The heart rate-blood pressure variations in supine and standing positions were monitored, and synchronization parameters of seated resting-state HRV coupled with qEEG were collected. Time-domain and frequency-domain of HRV measures as well as peak frequency and power of the brainwaves were extracted. Differences between these three groups were compared, and correlations between brain-heart parameters were analyzed. The research results showed that the time-domain parameters such as MxDMn, pNN50, RMSSD, and SDSD of seated resting-state HRV exhibited a significant decrease only in the α-OH group compared to the healthy control group (p < 0.05), while there was no significant difference between the α-NOH group and the healthy control group. Several time-domain and frequency-domain parameters of seated resting-state HRV were found to be correlated with the blood pressure changes within the first 5 min of transitioning from supine to standing position (p < 0.05). Differences were observed in the power of beta1 waves (F4 and Fp2) and beta2 waves (Fp2 and F4) in the seated resting-state qEEG between the α-OH and α-NOH groups (p < 0.05). The peak frequency of theta waves in the Cz region also showed a difference (p < 0.05). The power of beta2 waves in the Fp2 and F4 brain regions correlated with frequency-domain parameters of HRV (p < 0.05). Additionally, abnormal electrical activity in the alpha, theta, and beta1 waves was associated with changes in heart rate and blood pressure within the first 5 min of transitioning from supine to standing position (p < 0.05). Rapid resting-state HRV with certain time-domain parameters below normal levels may serve as a predictive indicator for the occurrence of orthostatic hypotension (OH) in patients with α-synucleinopathies. Additionally, the deterioration of HRV parameters correlates with synchronous abnormal qEEG patterns, which can provide insights into the brain stimulation target areas for OH in α-synucleinopathy patients.

Effectiveness of cognitive-behavioral therapy for insomnia in quantitative EEG analysis of non-REM sleep

Effectiveness of cognitive-behavioral therapy for insomnia in quantitative EEG analysis of non-REM sleep