Clinical EEG and Neuroscience最新文献_第3页

High-Density (HD) Scalp EEG Findings in "Benign" Childhood Epilepsy with Centrotemporal Spikes (BCECTS). 颞叶中心棘波 "良性 "儿童癫痫 (BCECTS) 的高密度 (HD) 头皮脑电图结果。

IF 2 4区医学

Clinical EEG and Neuroscience Pub Date : 2024-03-01 Epub Date: 2022-12-14 DOI: 10.1177/15500594221145265

Sonal Bhatia, Andrew Todd Ham, Ekrem Kutluay

{"title":"High-Density (HD) Scalp EEG Findings in \"Benign\" Childhood Epilepsy with Centrotemporal Spikes (BCECTS).","authors":"Sonal Bhatia, Andrew Todd Ham, Ekrem Kutluay","doi":"10.1177/15500594221145265","DOIUrl":"10.1177/15500594221145265","url":null,"abstract":"Despite characteristic clinical and scalp EEG findings, BCECTS pathophysiology is unclear regarding involvement of large-scale neuronal networks. Higher number of scalp electrodes with HD-EEG may promote accurate localization of the cortical generators in BCECTS providing additional insight in those with neurocognitive problems. We aimed to determine the value of visual interpretation of topographical maps using 256 channels (when compared to standard 21 channel array) HD-EEG in BCECTS and attempted to source localize interictal discharges (IEDs) using Geosource 2 software. Patient records were reviewed for demographic, seizure, brain magnetic resonance imaging (MRI) details; scalp and HD-EEG findings. HD-EEG software was used to review raw EEG data (21 scalp EEG electrodes were compared to 256 HD-EEG electrodes); select, average, and source localize IEDs.Five BCECTS patients with HD-EEG were identified. Seizure onset age ranged from 5-11 years with 1-18 lifetime seizures; both focal (n = 3) and focal to bilateral tonic-clonic (n = 2). Neurocognitive co-morbidities noted in our cohort included attention deficit hyperactivity disorder, speech/developmental delay and a specific learning disorder. Scalp EEG showed typical findings with IEDs over the centrotemporal regions (bilateral n = 3; unilateral n = 2). Visualization and inspection of expanded coverage topographic maps with HD-EEG showed well-defined islands of maximum negativity and positivity of a dipole compared to conventional channels where boundary delineation was obscured. Further, HD-EEG localized IEDs/\"spike-generator\" to areas such as the pre-and post-central, middle-frontal and temporal gyrus, and the inferior parietal lobule. In BCECTS, HD-EEG may show affection for a broader neural network and may provide a better insight into the associated neurocognitive morbidities.","PeriodicalId":10682,"journal":{"name":"Clinical EEG and Neuroscience","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10338255","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Connectivity Disturbances in Self-Limited Epilepsy with Centrotemporal Spikes: A Partial Directed Coherence Analysis of Electroencephalogram. 自限性癫痫与中心颞区棘波的连接紊乱：脑电图的部分定向相干性分析。

IF 2 4区医学

Clinical EEG and Neuroscience Pub Date : 2024-03-01 Epub Date: 2023-05-25 DOI: 10.1177/15500594231177979

Ching-Tai Chiang, Rei-Cheng Yang, Yu-Chia Kao, Rong-Ching Wu, Chen-Sen Ouyang, Lung-Chang Lin

{"title":"Connectivity Disturbances in Self-Limited Epilepsy with Centrotemporal Spikes: A Partial Directed Coherence Analysis of Electroencephalogram.","authors":"Ching-Tai Chiang, Rei-Cheng Yang, Yu-Chia Kao, Rong-Ching Wu, Chen-Sen Ouyang, Lung-Chang Lin","doi":"10.1177/15500594231177979","DOIUrl":"10.1177/15500594231177979","url":null,"abstract":"Although the remission of self-limited epilepsy with centrotemporal spikes (SeLECTS) usually occurs by adolescence, deficits in cognition and behavior are not uncommon. Several functional magnetic resonance imaging (fMRI) studies have revealed connectivity disturbances in patients with SeLECTS associated with cognitive impairment. However, the disadvantages of fMRI are expensive, time-consuming, and motion sensitive. In the current study, we used a partial directed coherence (PDC) method to analyze electroencephalogram (EEG) for exploring brain connectivity in patients with SeLECTS. This study enrolled 38 participants (19 patients with SeLECTS and 19 healthy controls) for PDC analysis. Our results demonstrated that the controls had significantly higher PDC inflow connectivity in the F7, T3, FP1, and F8 channels than patients with SeLECTS. By contrast, the patients with SeLECTS demonstrated significantly higher PDC inflow connectivity than did the controls in the T5, Pz, and P4 channels. We also compared the PDC connectivity in different Brodmann areas between the patients with SeLECTS and the controls. The results revealed that the inflow connectivity in the BA9_46_L area was significantly higher in the controls than in the patients with SeLECTS, whereas the inflow connectivity in the MIF_L area 4 was significantly higher in the patients with SeLECTS than in the controls. Our proposed approach of combining EEG with PDC provides a convenient and useful tool for investigating functional connectivity in patients with SeLECTS. This approach is time-saving and inexpensive compared with fMRI, but it achieves similar results to fMRI.","PeriodicalId":10682,"journal":{"name":"Clinical EEG and Neuroscience","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9526707","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The Prevalence and Risk Factors of Electrical Status Epilepticus During Slow-Wave Sleep in Self-Limited Epilepsy With Centrotemporal Spikes. 伴有中心颞区棘波的自限性癫痫患者慢波睡眠时电癫痫状态的发生率和风险因素

IF 2 4区医学

Clinical EEG and Neuroscience Pub Date : 2024-03-01 Epub Date: 2023-06-18 DOI: 10.1177/15500594231182758

Guangshuang Lu, Yun Cheng, Yun Wang, Jie Hu, Fan Zhang, Wenbo Li, Minnong Xia, Xiaoyan Lu, Wu Yang

{"title":"The Prevalence and Risk Factors of Electrical Status Epilepticus During Slow-Wave Sleep in Self-Limited Epilepsy With Centrotemporal Spikes.","authors":"Guangshuang Lu, Yun Cheng, Yun Wang, Jie Hu, Fan Zhang, Wenbo Li, Minnong Xia, Xiaoyan Lu, Wu Yang","doi":"10.1177/15500594231182758","DOIUrl":"10.1177/15500594231182758","url":null,"abstract":"Objective. To investigate the prevalence and risk factors for electrical status epilepticus during slow-wave sleep (ESES) in patients with self-limited epilepsy with centrotemporal spikes (SeLECTS). Methods. The clinical and follow-up data of children with SeLECTS were collected between 2017 and 2021. Patients were divided into typical ESES, atypical ESES, and non-ESES groups according to spike-wave indices (SWI). Clinical and electroencephalography characteristics were retrospectively analyzed. Logistic regression was used to identify risk factors for ESES. Results. A total of 95 patients with SeLECTS were enrolled. Seven patients (7.4%) developed typical ESES, 30 (31.6%) developed atypical ESES, 25 (26.3%) developed ESES at the first visit, and 12 (12.6%) developed ESES during treatment and follow-up. Multivariate logistic regression analysis showed that the risk factors for SeLECTS combined with ESES were Rolandic double or multiple spikes (OR = 8.626, 95% CI: 2.644-28.147, P < .001) and Rolandic slow waves (OR = 53.550, 95% CI: 6.339-452.368, P < .001). There were no significant differences in seizure characteristics, electroencephalogram (EEG) findings, or cognitive impairment between the atypical and typical ESES groups. Conclusion. More than one-third of the SeLECTS patients combined with ESES. Both atypical and typical ESES scores can affect cognitive function. On electroencephalography, interictal Rolandic double/multiple spikes and slow-wave abnormalities may indicate SeLECTS with ESES.","PeriodicalId":10682,"journal":{"name":"Clinical EEG and Neuroscience","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9655669","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The Deep Learning Method Differentiates Patients with Bipolar Disorder from Controls with High Accuracy Using EEG Data. 深度学习方法利用脑电图数据高精度区分双相情感障碍患者和对照组。

IF 2 4区医学

Clinical EEG and Neuroscience Pub Date : 2024-03-01 Epub Date: 2022-11-06 DOI: 10.1177/15500594221137234

Barış Metin, Çağlar Uyulan, Türker Tekin Ergüzel, Shams Farhad, Elvan Çifçi, Ömer Türk, Nevzat Tarhan

{"title":"The Deep Learning Method Differentiates Patients with Bipolar Disorder from Controls with High Accuracy Using EEG Data.","authors":"Barış Metin, Çağlar Uyulan, Türker Tekin Ergüzel, Shams Farhad, Elvan Çifçi, Ömer Türk, Nevzat Tarhan","doi":"10.1177/15500594221137234","DOIUrl":"10.1177/15500594221137234","url":null,"abstract":"Background: Bipolar disorder (BD) is a mental disorder characterized by depressive and manic or hypomanic episodes. The complexity in the diagnosis of Bipolar disorder (BD) due to its overlapping symptoms with other mood disorders prompted researchers and clinicians to seek new and advanced techniques for the precise detection of Bipolar disorder (BD). One of these methods is the use of advanced machine learning algorithms such as deep learning (DL). However, no study of BD has previously adopted DL techniques using EEG signals. Method: EEG signals of 169 BD patients and 45 controls were cleaned from the artifacts and processed using two different DL methods: a one-dimensional convolutional neural network (1D-CNN) combined with the long-short term memory (LSTM) and a two-dimensional convolutional neural network (2D-CNN). Additionally, Class Activation Maps (CAMs) acquired from the bipolar and control groups were used to obtain distinctive regions to specify a particular class in an image. Results: Group identifications were confirmed with 95.91% overall accuracy through the 2D-CNN method, demonstrating very high sensitivity and lower specificity. Also, the overall accuracy obtained from the 1D-CNN + LSTM method was 93%. We also found that F4, C3, F7, and F8 electrode activities produce predominant features to detect the bipolar group. Conclusion: To our knowledge, this study used EEG-based DL analysis for the first time in BD. Our results suggest that the raw EEG-based DL algorithm can successfully differentiate individuals with BD from controls. Class Activation Map (CAM) analysis suggests that prefrontal changes are predominant in EEG data of patients with BD.","PeriodicalId":10682,"journal":{"name":"Clinical EEG and Neuroscience","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40452153","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Abdominal Compartment Syndrome with Super-K (Ketamine) for Super-R(efractory) Status Epilepticus: A Case Report. 腹腔隔室综合征用超k(氯胺酮)治疗超r(难治性)癫痫持续状态:1例报告。

IF 2 4区医学

Clinical EEG and Neuroscience Pub Date : 2024-03-01 Epub Date: 2022-10-25 DOI: 10.1177/15500594221134920

Prashant A Natteru, Shoba Jayaram, Oriana Sanchez, Kyla Leon, Aditi Mishra, Christa O'Hana Nobleza

引用次数: 0

How Can a Focal Seizure Lead to a Dacrystic Behavior? A Case Analyzed with Functional Connectivity in Stereoelectroencephalography. 局灶性癫痫发作如何导致达克里斯特行为？利用立体脑电图功能连接分析的一个案例。

IF 2 4区医学

Clinical EEG and Neuroscience Pub Date : 2024-03-01 Epub Date: 2023-06-20 DOI: 10.1177/15500594231182808

Barbara Marx, Samuel Medina-Villalon, Fabrice Bartolomei, Stanislas Lagarde

引用次数: 0

qEEG in the Diagnosis and Prognosis of a Case with Delusional Infestation. qEEG 在一例妄想性感染病例的诊断和预后中的应用。

IF 2 4区医学

Clinical EEG and Neuroscience Pub Date : 2024-03-01 Epub Date: 2023-03-21 DOI: 10.1177/15500594231163383

Mehmet Kemal Arıkan, Reyhan İlhan, Mahmut Taha Ozulucan, Murat Aşık

引用次数: 0

Ictal EEG: Etiology and Mortality in Older Adults With Nonconvulsive Status Epilepticus. 异位脑电图：老年非惊厥性癫痫状态患者的病因和死亡率。

IF 2 4区医学

Clinical EEG and Neuroscience Pub Date : 2024-03-01 Epub Date: 2023-07-27 DOI: 10.1177/15500594231183554

Glória M A S Tedrus

{"title":"Ictal EEG: Etiology and Mortality in Older Adults With Nonconvulsive Status Epilepticus.","authors":"Glória M A S Tedrus","doi":"10.1177/15500594231183554","DOIUrl":"10.1177/15500594231183554","url":null,"abstract":"Clinical-electroencephalogram (EEG), as well as etiological and prognostic data on subtypes of nonconvulsive status epilepticus (NCSE) are yet to be established. Objective: Evaluate the clinical semiology and EEG findings and prognostic data of older adults with NCSE. Methodology: Characterize the clinical-EEG and prognostic data in the subtypes of NCSE in older adults consecutively admitted to the emergency room of the Pontifícia Universidade Católica de Campinas (PUC-Campinas) University Hospital. Results: When evaluating 105 older adults with altered consciousness, it was possible to diagnose NCSE in 50 (47.6%) older adults, with a mean age of 72.8 ± 8.8 years. NCSE-coma occurred in 6 cases, with NCSE-without coma in 44 cases. The etiology was structural in 41(82%) cases, metabolic in 5 cases, and unknown etiology in 4 cases. Twelve cases had a history of epileptic seizures. On the EEG, epileptiform discharges (EDs > 2.5 Hz) were present in 34(68%) cases and rhythmic delta activity /lateralized periodic patterns occurred in 35(70%) cases. There was clinical improvement after the initial pharmacological treatment in 36 cases and, within 30 days, 18 cases died. The better prognosis was associated with a good response to initial pharmacological treatment (n = 14) and with EDs > 2.5 Hz on EEG (Fisher's exact test; 26 vs 8; P = .012). Conclusion: Focal NCSE with impaired consciousness was the most frequent subtype. The most frequent finding on the EEG was the recording of focal/regional seizures. A high number of cases showed initial clinical improvement, but mortality was high. The favorable prognosis was associated with initial clinical improvement and the presence of EDs > 2.5 Hz. There was no relationship between EEG patterns and the etiology and subtypes of NCSE in older adults.","PeriodicalId":10682,"journal":{"name":"Clinical EEG and Neuroscience","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10241494","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

QEEG Predictors of Treatment Response in Major Depressive Disorder- A Replication Study from Northwest India. 重度抑郁障碍治疗反应的 QEEG 预测因素--印度西北部的一项重复研究。

IF 2 4区医学

Clinical EEG and Neuroscience Pub Date : 2024-03-01 Epub Date: 2022-11-29 DOI: 10.1177/15500594221142396

Akashdeep Singh, Priti Arun, Gurvinder Pal Singh, Damanjeet Kaur, Simranjit Kaur

{"title":"QEEG Predictors of Treatment Response in Major Depressive Disorder- A Replication Study from Northwest India.","authors":"Akashdeep Singh, Priti Arun, Gurvinder Pal Singh, Damanjeet Kaur, Simranjit Kaur","doi":"10.1177/15500594221142396","DOIUrl":"10.1177/15500594221142396","url":null,"abstract":"Background: Predicting treatment response with antidepressant is a challenging task for clinicians and researchers. An important limitation of an antidepressant trial is the increased time spent before an adequacy of trial can be decided. Quantitative Electroencephalography has shown some evidence in identifying early changes seen with antidepressants. No data has been reported from Indian population on its predictive capabilities. Aim: To examine whether early changes in frontal and prefrontal theta value in QEEG could predict antidepressant treatment response. Methods: Structured clinical assessments were conducted at baseline and after one week in a sample of treatment-seeking adults with major depressive disorder (n = 50). Patients were started on SSRI (Escitalopram, fluoxetine, paroxetine or sertraline) and followed for 8 weeks. QEEG recordings were carried out at baseline and week 1 and its parameters (relative theta power and cordance) were assessed to identify its predictive value for treatment response. Treatment response was assessed using Hamilton depression rating scale with 50% reduction after 8 weeks being considered as response. Results: Mean age of the sample was 39 ± 10 years and majority of them were females (64%). A significant reduction was found in relative frontal theta value (p = 0.021) from baseline to one week in responders. However, linear regression revealed that this change could not predict the treatment response (p = 0.37). Conclusions: QEEG changes are observed in initial phase of antidepressant treatment but these changes can't predict the treatment response.","PeriodicalId":10682,"journal":{"name":"Clinical EEG and Neuroscience","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40489696","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Decreased Resting-State Alpha Self-Synchronization in Depressive Disorder. 抑郁症患者静息态阿尔法自同步性降低

IF 2 4区医学

Clinical EEG and Neuroscience Pub Date : 2024-03-01 Epub Date: 2023-03-21 DOI: 10.1177/15500594231163958

Yousef Mohammadi, Mohadeseh Shafiei Kafraj, Carina Graversen, Mohammad Hassan Moradi

{"title":"Decreased Resting-State Alpha Self-Synchronization in Depressive Disorder.","authors":"Yousef Mohammadi, Mohadeseh Shafiei Kafraj, Carina Graversen, Mohammad Hassan Moradi","doi":"10.1177/15500594231163958","DOIUrl":"10.1177/15500594231163958","url":null,"abstract":"Background. Depression disorder has been associated with altered oscillatory brain activity. The common methods to quantify oscillatory activity are Fourier and wavelet transforms. Both methods have difficulties distinguishing synchronized oscillatory activity from nonrhythmic and large-amplitude artifacts. Here we proposed a method called self-synchronization index (SSI) to quantify synchronized oscillatory activities in neural data. The method considers temporal characteristics of neural oscillations, amplitude, and cycles, to estimate the synchronization value for a specific frequency band. Method. The recorded electroencephalography (EEG) data of 45 depressed and 55 healthy individuals were used. The SSI method was applied to each EEG electrode filtered in the alpha frequency band (8-13 Hz). The multiple linear regression model was used to predict depression severity (Beck Depression Inventory-II scores) using alpha SSI values. Results. Patients with severe depression showed a lower alpha SSI than those with moderate depression and healthy controls in all brain regions. Moreover, the alpha SSI values negatively correlated with depression severity in all brain regions. The regression model showed a significant performance of depression severity prediction using alpha SSI. Conclusion. The findings support the SSI measure as a powerful tool for quantifying synchronous oscillatory activity. The data examined in this article support the idea that there is a strong link between the synchronization of alpha oscillatory neural activities and the level of depression. These findings yielded an objective and quantitative depression severity prediction.","PeriodicalId":10682,"journal":{"name":"Clinical EEG and Neuroscience","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9525408","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0