Clinical EEG and neuroscience最新文献

BackgroundPsychosocial stress-particularly bullying-has been recognized as a critical determinant of mental and neurophysiological health in children. Chronic stress exposure may disrupt cortical regulatory mechanisms detectable through quantitative electroencephalography (q-EEG).ObjectiveThis study examined the correlation between perceived psychological stress, involvement in bullying, and q-EEG spectral anomalies among Indonesian school-aged children, seeking to determine if bullying-related stress generates unique neurophysiological patterns or indicates a general dysregulation of stress responses.MethodsA two-phase design was implemented. Phase I included 2781 8-13-year-olds who completed the PSS-10 and a validated bullying questionnaire. Using a Mitsar-EEG 201 equipment, Phase II selected 24 students with increased stress levels (PSS ≥ 27) for q-EEG examination. Electroencephalogram signals from 19 scalp sites were converted into z-scores using age-adjusted NeuroGuide database standards. Stress level and brain activity were correlated using Spearman's rho.ResultsThe majority of subjects (23 out of 25; 95.8%) had EEG activity above ±2 standard deviations, especially in the temporal and prefrontal areas. There was a negative correlation between stress and temporal alpha power (r = -0.43, p = 0.028) and a positive correlation between stress with enhanced prefrontal high-beta power (r = 0.47, p = 0.021). Neurophysiological alterations among bullied children closely paralleled those under non-bullying stressors such as academic overload or family conflict.ConclusionElevated stress intensity, regardless of its psychosocial origin, was associated with convergent cortical dysregulation patterns. These results suggest that q-EEG may be a viable non-invasive method for early stress-related neurophysiological dysfunction diagnosis and that pediatric populations require integrated emotional regulation therapies.

BackgroundAssessment and treatment monitoring in alcohol dependence syndrome often rely on subjective measures, particularly in resource-limited settings. Quantitative electroencephalogram (qEEG) provides an objective alternative, though its role in alcohol use and abstinence remains underexplored in the Indian context.AimTo study changes in the quantitative electroencephalogram in persons with alcohol dependence syndrome undergoing treatment.MethodsPatients diagnosed with alcohol dependence syndrome as per ICD-11 were recruited. At baseline, the Severity of Alcohol Dependence Questionnaire (SADQ) (mean 22.60 ± 4.81) and Clinical Institute Withdrawal Assessment for Alcohol-Revised (CIWA-Ar) (mean 10.98 ± 2.45) were administered to assess the severity of dependence and withdrawal symptoms. qEEG was recorded at baseline, following detoxification and at 12 weeks. Detoxification was done using benzodiazepines via a symptom-triggered regimen. Baclofen was offered post-detoxification with regular follow-ups. EEG signals were analysed for changes across standard frequency bands in various scalp regions and in terms of absolute powers.ResultsSixty patients completed the 12-week follow-up. The sample consisted of all males, with a mean age of 40.85 ± 8.30 years. Alpha and gamma powers showed increasing trends, while beta, theta, and delta powers declined across most scalp regions. Absolute power trends were similar, with a statistically significant reduction noted in the delta wave (p-value=.024). No significant correlation was found between severity of dependence and wave powers, except for gamma in the fronto-parietal region (p-value=.01) and beta in the central region (p-value=.021).ConclusionqEEG changes with detoxification and abstinence may serve as an objective indicator for assessing treatment efficacy and abstinence status in alcohol dependence.

To investigate the relationship between age-related brain volume loss and neural functional connectivity (FC), whole brain volume and mean FC were calculated in 75 healthy participants aged 20 to 86 years (39 women, 36 men; mean age: 59.31 years). Resting-state MEG with eyes closed and MRI were conducted. Correlations between age and whole brain volume, mean neural connectivity expressed as amplitude envelope correlation (AEC) in the alpha frequency band across 66 functional parcellations, and the standard deviation (SD) of AEC were analyzed. In seven brain regions showing significant age-related volume loss, mean AEC and SD of AEC with other regions were assessed. Whole brain volume decreased with age (r = -0.322, p = .00480), particularly in participants older than 75 years (p < .05, ANOVA). AEC values also declined with age (r = -0.359, p = .00153), with significant differences observed between generational subgroups under 45 and over 75 years (p < .05). The SD of AEC decreased across the brain with age (r = -0.326, p = .0043). However, seven brain regions with significant age-related volume loss did not consistently show significant differences in AEC or its SD between generational subgroups, in contrast to consistent volume differences observed. Overall, brain volume and neural FC declined with age, accompanied by reduced variability in FC across the brain. Nevertheless, regions exhibiting significant volume loss were not always associated with functional decline in FC or its variability, suggesting the brain may compensate for global decline through localized functional adaptations.

Breach rhythm (BR) is a well-recognized EEG pattern characterized by high-amplitude, sharply contoured fast activity over areas of skull defect, most often following craniotomy or trauma. Although considered physiological, BR may closely mimic epileptiform discharges, leading to diagnostic uncertainty. We report a 33-year-old man with bilateral skull defects secondary to traumatic brain injury who presented with recurrent generalized tonic-clonic seizures. EEG showed continuous fast and sharp activity over the right F4-C4 region, consistent with BR, and diffuse slow waves over the left hemisphere. During two focal seizures, ictal discharges originating from the right F8 electrode transiently modified the morphology and rhythmicity of the ongoing BR before spreading bilaterally. Interestingly, no BR was observed over the left hemisphere despite a large skull defect, likely reflecting severe cortical injury. Following treatment with levetiracetam and phenytoin, seizures resolved, while the right-sided BR persisted unchanged. This case highlights that BR is not merely a passive artifact of altered conductivity but a dynamic indicator of cortical function. Its modulation during seizures and absence over structurally damaged cortex support the concept that BR may serve as a potential marker of cortical viability. Recognizing these patterns may prevent misinterpretation of physiological BR as epileptiform activity and enhance EEG evaluation in patients with structural brain lesions.

BackgroundSubacute sclerosing panencephalitis (SSPE) is a rare progressive encephalitis due to persistent measles infection. While classically a childhood disorder, atypical, adult-onset, and subclinical variants are increasingly reported. Ocular findings may precede neurological involvement by years. We aimed to underline EEG's role in tracking disease evolution from isolated ocular signs to neurological progression.CaseA 31-year-old woman presented with isolated ocular complaints and bilateral optic atrophy. Cerebrospinal fluid revealed measles IgG and IgG index positivity, confirming SSPE. For four years, she remained neurologically asymptomatic. EEG initially showed bilateral central theta paroxysms, later progressing to generalized periodic discharges. Serial EEGs demonstrated progressively shortened inter-discharge intervals. Additional features emerged, including frontally predominant generalized rhythmic delta activity and hyperventilation-provoked discharges. Importantly, when EEG abnormalities first appeared, neuropsychometric testing detected deficits in attention and executive function, despite the absence of subjective complaints. With time, cognitive decline became clinically evident, and negative myoclonus appeared.ConclusionThis case illustrates the importance of long-term surveillance in subclinical SSPE. EEG abnormalities preceded overt neurological decline, providing the earliest clues to disease progression. Careful interpretation of evolving EEG patterns may anticipate cognitive impairment and guide timely interventions. Our patient's trajectory underscores that even clinically silent SSPE carries a hidden risk of deterioration, and that vigilant EEG monitoring can act as a window into the disease course.

This manuscript examines the pivotal role of neuroinflammation in the central nervous system (CNS), particularly considering the impact of the COVID-19 pandemic. Neuroinflammation serves as a defense mechanism against various insults, including toxins, infections, and trauma. However, if left untreated, neuroinflammation can become chronic, leading to significant symptomatic and structural brain damage. Notably, neuroinflammation can mimic psychological disorders, complicating diagnosis and treatment. Current diagnostic methods for neuroinflammation-such as lumbar punctures, MRIs, brain biopsies, blood tests, and PET scans-are often hindered by inaccuracy, invasiveness, and cost. This study posits that electroencephalography (EEG), particularly identifying spindling excessive beta (SEB) activity, offers a promising, non-invasive, and cost-effective alternative for detecting neuroinflammation. This study investigates the relationship between SEB activity and neuroinflammation, focusing on traumatic brain injury (TBI). Through statistical analysis of EEG data from 1,233 psychiatric patients, we identified and compared two groups: 75 non-benzodiazepine-using adults without TBI and 79 non-benzodiazepine using adults with TBI exhibiting SEB activity. We identified a significant prevalence of SEB in individuals with refractory psychiatric conditions, underscoring the significance of this biomarker for neuroinflammation. Furthermore, we examine the therapeutic implications of reducing SEB through interventions such as guanfacine combined with N-Acetyl Cysteine (NAC), photobiomodulation, and hyperbaric oxygen therapy, all of which have demonstrated efficacy in mitigating neuroinflammation. These findings suggest that EEG could play a transformative role in the early detection and management of neuroinflammatory conditions, paving the way for more personalized and effective treatments for mental health disorders.

Background: As a leading cause of severe morbidity, acute ischemic stroke (AIS) necessitates precise prognostic evaluation to inform critical treatment strategies. Recent advancements have identified quantitative electroencephalography (qEEG) as a pivotal instrument in refining prognostic accuracy for AIS. This investigation aimed to construct a robust prognostic model, anchored in qEEG parameters, to enhance the precision of clinical prognosis 6 months after discharge in AIS patients. Methods: In a retrospective observational study, we analyzed AIS cases from January 2022 to March 2023. Data encompassing demographic profiles, clinical manifestations, qEEG findings, and modified Rankin Scale (mRS) assessments were evaluated for 109 patients with AIS. These metrics were instrumental in developing prognostic models, segregating outcomes into either favorable (mRS: 0-2) or unfavorable categories (mRS: 3-6) at 6 months post-discharge. Prognostic models were developed using clinical and qEEG parameters. Results: The formulation of two distinct prognostic models was predicated on an integration of baseline clinical data (age, unilateral limb weakness, ataxia and red blood cell count) and specific qEEG metrics (T3-P3 (TAR) and T4-P4 (TAR)). The synthesis of these models culminated in the Prognostic Model 3, which exhibited a marked enhancement in prognostic accuracy, as evidenced by an area under the curve (AUC) of 0.8227 (95% CI: 0.7409-0.9045), thereby signifying a superior prediction of AIS prognosis 6 months after discharge relative to the individual models. Conclusion: Quantitative EEG, especially increased theta/alpha power ratio (TAR), might improve the prediction of prognosis 6 months after discharge of acute ischemic stroke in clinical practice.

Objective: This study aimed to compare electroencephalogram microstates of patients with chronic stroke to healthy subjects and correlated microstates with clinical and functional characteristics in stroke. Methods: This cross-sectional, exploratory and correlational study was performed with chronic stroke patients (n = 27) and healthy subjects (n = 27) matched for age and gender. We recorded electroencephalography microstates using 32 channels during eyes-closed and eyes-open conditions and analyzed the four classic microstates maps (A, B, C, D). Post-stroke participants were assessed using the modified Rankin Scale and the Fugl-Meyer Scale. All participants were assessed for cognitive function, fear of falling, and static balance. Student's t-test was used to compare groups and Pearson's correlation coefficient was used to assess correlations between microstates parameters and stroke-related clinical outcomes. Results: In the eyes-open condition, moderate correlations were observed between the duration of microstate C and functional disability. In the eyes-closed condition, moderate correlations were observed between the coverage of microstate C, the occurrence of microstate C and D, and the duration of microstate B with functional aspects (eg, lower limb motor function, balance, functional disability, and fear of falling). Conclusions: Changes in microstates and correlations between topographies and clinical and functional aspects suggest that electroencephalogram could be used as a biomarker in stroke patients.

Psychogenic non-epileptic seizures (PNES) are complex episodes that outwardly resemble epileptic seizures but are not caused by any underlying neurological disease. Unlike true epileptic seizures, PNES are more likely to be linked to psychological factors and do not show any abnormal activity on electroencephalography (EEG) recordings. This differentiation is crucial for accurate diagnosis and treatment, as misdiagnosing can lead to unnecessary treatments.Diagnosis of PNES might become difficult in the presence of particular benign EEG variants such as Rhythmic Midtemporal Discharges (RMTD). RMTD is a rare benign variant of normal EEG, characterized by rhythmic 5-7 Hz discharges in the temporal regions. This pattern could be present in normal individuals, in patients with psychiatric disorders or epilepsy. It could mimic interictal epileptiform discharges. Recognition of this pattern is essential to avoid misinterpretation of EEG findings that might eventuate in inappropriate treatment and adverse effects on a patient's medical condition, especially when there is a recent suspicious event in terms of an epileptic seizure. Among patients with PNES, the occurrence of benign variants might be much harder to interpret and physicians may mistakenly interpret RMTD on the EEG as indicative for epilepsy, especially in the absence of clear clinical criteria for PNES. This report is the first to document RMTD in first-degree relatives with PNES, suggesting a possible genetic predisposition and the need for further research into the interaction between RMTD and PNES.Our aim is to raise awareness that will enable accurate EEG reading and correct diagnosis.