Clinical EEG and neuroscience最新文献

IntroductionFacial emotion recognition is impaired in schizophrenia and contributes to profound social impairments. Healthy adults exhibit larger N170 amplitudes to emotional compared to neutral faces. Preliminary evidence suggests an inability to modulate N170 amplitude by emotional expression during chronic stages of the illness. The present investigation examined N170 modulation by emotion among patients with chronic (ChSz) and first hospitalized (FHSz) schizophrenia.MethodsEEG was recorded from 26 FHSz and 28 ChSz participants as well as 19 young (YC) and 21 older (OC) matched controls. Participants were asked to detect neutral faces among happy, angry, disgusted, fearful, and sad faces. N170 amplitudes were measured from P9/P10 electrodes. Symptoms were assessed using the Positive and Negative Syndrome Scale (PANSS).ResultsN170 amplitude modulation by facial emotion was observed across FHSz and YC (P < .001), though the typical right-hemisphere lateralization of this response observed in YC (P = .001) was absent in FHSz (P = .56). In contrast to OC (P = .009), ChSz did not exhibit N170 modulation by emotion (P = .32). Among ChSz, N170 modulation (mean N170 across emotional expressions minus N170 to neutral faces) at P9 were inversely correlated with PANSS negative scores (r = -.53).DiscussionResults suggests a progressive impairment of emotional facial expression processing as indexed by N170 modulation across illness stage. While losing the hemispheric specialization of face processing, FHSz exhibited preserved N170 amplitude modulation by facial emotion in contrast to ChSz. This deficit was also associated with negative symptoms, implicating progressive pathology of N170 generators in persistent and debilitating symptoms of the disorder.

P3a is an event-related potential that reflects the involuntary orienting of attention to salient stimuli. Abnormalities in P3a have been described in schizophrenia, but it is not known when they arise over the course of illness and whether they are progressive. Previous longitudinal studies of P3a have been inconclusive because of the heterogeneity in the diagnosis of psychotic patients, lack of follow-up data on controls, and relatively short follow-up periods. P3a, elicited by novel sounds, was assessed in 21 patients with first-episode schizophrenia and 36 healthy controls at baseline and reassessed in 14 patients and 23 controls after an average follow-up of six years. The longitudinal evaluation showed that the P3a amplitude was reduced in patients compared to controls at baseline but did not differ between groups at follow-up. Although P3a was reduced over the six-year interval in both groups, the reduction was greater in controls compared to patients. Longitudinal findings suggest that the P3a amplitude deficit is present at the onset of schizophrenia. Normalization of P3a amplitudes in patients at follow-up may reflect the premature aging effect on P3a at the onset of illness, a floor effect in P3a amplitudes of both groups at follow-up, or the reversal of the P3a deficit in patients over time. Interestingly, at baseline, the P3a amplitude in patients without follow-up data did not differ from controls and was greater than in patients with follow-up data. Baseline findings indicate a heterogeneity within the first-episode schizophrenia group.

ObjectiveThis cross-sectional study aimed to identify electrophysiological markers distinguishing stages of development, stability, and early aging in cortical auditory processing to elucidate neurophysiological changes in healthy auditory aging.MethodsWe evaluated 149 healthy participants (both sexes; aged 7-59 years) recruited from the general community via electronic media, posters, radio, and regional television, divided into six age groups (7-11, 12-17, 18-29, 30-39, 40-49, and 50-59 years). Eligibility criteria included normal hearing, no neurological disorders, and normal otoscopy. Cortical auditory evoked potentials (CAEPs) were recorded using the syllable /da/ (binaural stimulation, 70 dB HL) with eye-movement control.ResultsSignificant differences in P1 latency were observed between children (7-11 years) and older participants (12-59 years). N1 latency differed between children and adults (30-59 years), while N1 amplitude varied between adolescents (12-19 years) and adults aged 40-49 years. P1-N1 latency differed between adolescents and adults aged 40-59 years. Age correlated moderately negatively with P1/N1 latencies and weakly positively with N1 amplitude.ConclusionMaturational changes in P1/N1 latencies were evident, but no decline occurred during adulthood or pre-senescence, suggesting stable auditory processing until at least age 59.

IntroductionObsessive-compulsive disorder (OCD) affects 1.1-1.8% of the population, and adult females are more likely to suffer from it. Deep transcranial magnetic stimulation (dTMS) stimulates dorsomedial prefrontal cortex and anterior cingulate cortex - two frontal brain networks implicated in OCD. This study aims to identify a biological marker for beta rhythm that correlates with the treatment response works following dTMS.MethodsA total of 56 right-handed treatment-resistant OCD patients (35 female and 21 male) were retrospectively included in the study which were treated with FDA-approved dTMS protocol by using H7-coil for OCD. The Yale-Brown Obsessive Compulsive Scale (Y-BOCS) was used before and after dTMS to determine the severity of OCD symptoms and the responsiveness to therapy. Also, beta oscillations gathered from 19 electrodes quantitative electroencephalogram (QEEG) was assessed as treatment response prediction while controlling age and sex parameters.ResultsWhen controlling for sex and age, the Y-BOCS decline rate was linked to higher pretreatment beta activity in the parietal and occipital regions. In the second step of our analysis, we used a stepwise linear regression analysis to create a model predicting YBOCS decline rate. In this model, age (beta = -0.284, p = 0.030) and pretreatment beta parietal power band (beta = 0.312, p = 0.018) were the predictors.ConclusionAge and pretreatment parietal beta power bands may be used as a biomarker for predicting response to dTMS therapy if confirmed by further studies.

ObjectiveTo present a case of epileptic palinopsia successfully treated with lamotrigine and systematically review EEG findings, clinical features, and treatment outcomes of epileptic palinopsia.MethodsWe report a 58-year-old male with right occipital hemorrhage who developed seizures characterized by palinoptic phenomena four years post-injury. A systematic review of available cases was conducted using PRISMA guidelines and multiple databases (PubMed, Scopus, Embase, and Web of Science) through December 2024.ResultsThe patient's seizures included visual perseveration followed by bilateral tonic-clonic activity and achieved a >50% reduction in palinoptic phenomena with lamotrigine treatment over 20 months. Interictal EEG showed sharp and slow wave activity in the right temporal region, while MRI revealed right occipital encephalomalacia. The systematic review identified 40 cases from 34 articles (mean age 50.56 ± 16.10 years, 65.0% male). Interictal EEG abnormalities were present in 70.0% of cases, predominantly spikes/sharp waves (60.7%) localized to the right temporal and occipital regions. Ictal EEG recordings were available in 22.5% of cases. Both interictal (71.4%) and ictal (71.4%) findings demonstrated right-hemisphere predominance, particularly in the occipital region (30% of all cases, with 58.3% being right-sided). Structural abnormalities were identified in 26 cases, with tumors (42.3%) being the most common etiology. Anti-seizure drugs were prescribed in 57.5% of cases.ConclusionOur study highlights palinopsia as an overlooked seizure symptom with potential right hemispheric lateralization. Recognizing its EEG and neuroimaging patterns is essential for early diagnosis and treatment. Clinicians should maintain a high suspicion for epileptic palinopsia in patients with structural brain lesions involving temporo-occipital regions.

The term visual working memory (VWM) refers to the temporary storage of visual information. In electrophysiological recordings during the change detection task which relates to VWM, contralateral negative slow activity was detected. It was found to occur during the information is kept in memory and it was called contralateral delay activity. In this study, the characteristics of electroencephalogram frequencies of the contralateral and ipsilateral responses in the retention phase of VWM were evaluated by using time-frequency analysis (discrete wavelet transform [DWT]) in the change detection task. Twenty-six volunteers participated in the study. Event-related brain potentials (ERPs) were examined, and then a time-frequency analysis was performed. A statistically significant difference between contralateral and ipsilateral responses was found in the ERP. DWT showed a statistically significant difference between contralateral and ipsilateral responses in the delta and theta frequency bands range. When volunteers were grouped as either high or low VWM capacity the time-frequency analysis between these groups revealed that high memory capacity groups have a significantly higher negative coefficient in alpha and beta frequency bands. This study showed that during the retention phase delta and theta bands may relate to visual memory retention and alpha and beta bands may reflect individual memory capacity.

Quantitative electroencephalogram (QEEG) is a technology which has grown exponentially since the foundational publication by in Science in 1997, introducing the use of age-regressed metrics to quantify characteristics of the EEG signal, enhancing the clinical utility of EEG in neuropsychiatry. Essential to the validity and reliability of QEEG metrics is standardization of multi-channel EEG data acquisition which follows the standards set forth by the American Clinical Neurophysiology Society including accurate management of artifact and facilitation of proper visual inspection of EEG paroxysmal events both of which are expanded in this guideline. Additional requirements on the selection of EEG, quality reporting, and submission of the EEG to spectral, statistical, and topographic analysis are proposed. While there are thousands of features that can be mathematically derived using QEEG, there are common features that have been most recognized and most validated in clinical use and these along with other mathematical tools, such as low resolution electromagnetic tomographic analyses (LORETA) and classifier functions, are reviewed and cautions are noted. The efficacy of QEEG in these applications depends strongly on the quality of the acquired EEG, and the correctness of subsequent inspection, selection, and processing. These recommendations which are described in the following sections as minimum standards for the use of QEEG are supported by the International QEEG Certification Board (IQCB).

Background. Predicting neurological outcomes after hypoxic-ischemic brain injury (HIBI) is difficult. Objective. Electroencephalography (EEG) can identify acute and subacute brain abnormalities after hypoxic brain injury and predict HIBI recovery. We examined EEG's ability to predict neurologic outcomes following HIBI. Method. A PRISMA-compliant search was conducted in the Medline, Embase, Cochrane, and Central databases until January 2023. EEG-predicted neurological outcomes in HIBI patients were selected from relevant perspective and retrospective cohort studies. RevMan did meta-analysis, while QDAS2 assessed research quality. Results. Eleven studies with 3761 HIBI patients met the inclusion and exclusion criteria. We aggregated study-level estimates of sensitivity and specificity for EEG patterns determined a priori using random effect bivariate and univariate meta-analysis when appropriate. Positive indicators and anatomical area heterogeneity impacted prognosis accuracy. Funnel plots analyzed publication bias. Significant heterogeneity of greater than 80% was among the included studies with P < 0.001. The area under the curve was 0.94, the threshold effect was P < 0.001, and the sensitivity and specificity, with 95% confidence intervals, were 0.91 (0.84-0.99) and 0.86 (0.75-0.97). EEG detects status epilepticus and burst suppression with good sensitivity, specificity, and little probability of false-negative impairment result attribution. Study quality varied by domain, but patient flow and timing were well conducted in all. Conclusion. EEG can predict the outcome of HIBI with good prognostic accuracy, but more standardized cross-study protocols and descriptions of EEG patterns are needed to better evaluate its prognostic use for patients with HIBI.

Over the past decade, the Diagnostic and Statistical Manual's method of prescribing medications based on presenting symptoms has been challenged. The shift toward precision medicine began with the National Institute of Mental Health and culminated with the World Psychiatric Association's posit that a paradigm shift is needed. This study supports that shift by providing evidence explaining the high rate of psychiatric medication failure and suggests a possible first step toward precision medicine. A large psychiatric practice began collecting electroencephalograms (EEGs) for this study in 2012. The EEGs were analyzed by the same neurophysiologist (board certified in electroencephalography) on 1,233 patients. This study identified 4 EEG biomarkers accounting for medication failure in refractory patients: focal slowing, spindling excessive beta, encephalopathy, and isolated epileptiform discharges. Each EEG biomarker suggests underlying brain dysregulation, which may explain why prior medication attempts have failed. The EEG biomarkers cannot be identified based on current psychiatric assessment methods, and depending upon the localization, intensity, and duration, can all present as complex behavioral or psychiatric issues. The study highlights that the EEG biomarker identification approach can be a positive step toward personalized medicine in psychiatry, furthering the clinical thinking of "testing the organ we are trying to treat."

Objective: Post-stroke seizures (PSS) are one of the major stroke-related complications. Early therapeutic interventions are critical therefore using electroencephalography (EEG) as a predictive tool for future recurrence may be helpful. We aimed to assess frequencies of different EEG patterns in patients with PSS and their association with seizure recurrence and functional outcomes. Methods: All patients admitted with PSS were included and underwent interictal EEG recording during their admission and monitored for seizure recurrence for 24 months. Results: PSS was reported in 106 patients. Generalized slow wave activity (GSWA) was the most frequent EEG pattern observed (n  =  62, 58.5%), followed by Focal sharp wave discharges (FSWDs) (n  =  57, 55.8%), focal slow wave activity (FSWA) (n  =  56, 52.8%), periodic discharges (PDs) (n  =  13, 12.3%), and ictal epileptiform abnormalities (n  =  6, 5.7%). FSWA and ictal EAs were positively associated with seizure recurrence (p < .001 and p  =  .015 respectively) and it remained significant even after adjusting for age, sex, stroke severity, stroke subtype, or use of anti-seizure medications (ASMs). Other positive associations were status epilepticus (SE) (p  =  .015), and use of older ASM (p < .001). FSWA and GSWA in EEG were positively associated with severe functional disability (p  =  .055, p  =  .015 respectively). Other associations were; Diabetes Mellitus (p  =  .034), Chronic Kidney Disease (p  =  .002), use of older ASMs (p  =  .037), presence of late PSS (p  =  .021), and those with Ischemic stroke (p  =  .010). Conclusions: Recognition and documentation of PSS-related EEG characteristics are important, as certain EEG patterns may help to identify the patients who are at risk of developing recurrence or worse functional outcomes.