Clinical EEG and Neuroscience最新文献_第3页

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

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":" ","pages":"185-191"},"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

Epilepsy Surgery Outcome of Traumatic Intradiploic Meningoencephalocele: A Case Report and Literature Review. 外伤性腹腔内脑膜脑疝的癫痫手术效果：病例报告和文献综述。

IF 2 4区医学

Clinical EEG and Neuroscience Pub Date : 2024-03-01 Epub Date: 2022-12-15 DOI: 10.1177/15500594221144420

Faisal Alsallom, Majed Alzahrany, Jorge Gonzalez-Martinez, Lara Jehi

引用次数: 0

Enhanced Punishment Responses in Patients With Schizophrenia: An Event-Related Potential Study. 精神分裂症患者的惩罚反应增强：事件相关电位研究

IF 2 4区医学

Clinical EEG and Neuroscience Pub Date : 2024-03-01 Epub Date: 2023-08-10 DOI: 10.1177/15500594231190966

Özge Akgül, Ezgi Fide, Fatih Özel, Köksal Alptekin, Emre Bora, Berna Binnur Akdede, Görsev Yener

{"title":"Enhanced Punishment Responses in Patients With Schizophrenia: An Event-Related Potential Study.","authors":"Özge Akgül, Ezgi Fide, Fatih Özel, Köksal Alptekin, Emre Bora, Berna Binnur Akdede, Görsev Yener","doi":"10.1177/15500594231190966","DOIUrl":"10.1177/15500594231190966","url":null,"abstract":"It is well known that abnormal reward processing is a characteristic feature of various psychopathologies including schizophrenia. Reduced reward anticipation has been suggested as a core symptom of schizophrenia. The Monetary Incentive Delay Task (MID) is frequently used to detect reward anticipation. The present study aims to evaluate the amplitude and latency of event-related potential (ERP) P300 in patients with schizophrenia (SCH) compared to healthy controls during the MID task. Twenty patients with SCH and 21 demographically matched healthy controls (HC) were included in the study. ERP P300 amplitude and latency values were compared between groups using an MID task in which reward and loss cues were presented. Relations between P300 and clinical facets were investigated in the patient group. SCH group had enhanced mean P300 amplitudes and delayed peak latency in the punishment condition compared with HC. These higher responses were also associated with negative symptoms. SCH group showed altered reward processing as being more sensitive to loss of reward conditions as firstly evidenced by electrophysiological methods, possibly due to abnormality in various systems including social withdrawal, social defeat, and behavioral inhibition system.","PeriodicalId":10682,"journal":{"name":"Clinical EEG and Neuroscience","volume":" ","pages":"219-229"},"PeriodicalIF":2.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10346289","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

Response to Hydrocortisone in an Extremely Preterm Neonate With Late-Onset Sepsis, Meningoencephalitis, and Drug-Resistant Seizures. 晚期败血症、脑膜脑炎和耐药性癫痫发作的极早产新生儿对氢化可的松的反应

IF 2 4区医学

Clinical EEG and Neuroscience Pub Date : 2024-03-01 Epub Date: 2022-12-25 DOI: 10.1177/15500594221147138

Ralf Eberhard, Katryn Paquette, Jarred Garfinkle, Kenneth A Myers

引用次数: 0

Predictive Value of qEEG in Manic Switch of Depressed Patients. qEEG 对抑郁症患者躁狂转换的预测价值。

IF 2 4区医学

Clinical EEG and Neuroscience Pub Date : 2024-03-01 Epub Date: 2023-07-31 DOI: 10.1177/15500594231190278

Mehmet Kemal Arıkan, Reyhan İlhan, Mahmut Taha Özulucan, Muhammed Taha Esmeray, Mehmet Güven Günver

{"title":"Predictive Value of qEEG in Manic Switch of Depressed Patients.","authors":"Mehmet Kemal Arıkan, Reyhan İlhan, Mahmut Taha Özulucan, Muhammed Taha Esmeray, Mehmet Güven Günver","doi":"10.1177/15500594231190278","DOIUrl":"10.1177/15500594231190278","url":null,"abstract":"Backgrounds: More than half of the patients with bipolar disorder (BD) had depressive episodes at the onset of BD. Despite some suggested clinical predictors, there are no certain criteria for predicting which unipolar depression patient switch to manic episodes during the treatment course. Electrophysiological markers can address this issue. Methods: Pretreatment quantitative electroencephalography (qEEG) records of patients diagnosed with major depressive disorder (MDD) or BD at the first visit were included in the study. Patients with MDD were also grouped with manic switch (MS) or MDD based on the diagnosis of later visits. The qEEG spectral power was analyzed across 3 groups, that is, MS, MDD, and BD. Results: Compared to patients whose diagnosis did not change, patients with MS had accelerated high-frequency activities predominantly in the left hemisphere (central-parietal-occipital regions). In contrast, they showed increased slow wave activity predominantly in the right hemisphere (parietal-occipital regions). Conclusion: It can be concluded that searching for electrophysiological markers, which have distinct advantages of repeatability, noninvasiveness, and cost-effectiveness, can facilitate the prediction of the MS.","PeriodicalId":10682,"journal":{"name":"Clinical EEG and Neuroscience","volume":" ","pages":"192-202"},"PeriodicalIF":2.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10268980","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

Gamma Oscillations and Potassium Channel Modulation in Schizophrenia: Targeting GABAergic Dysfunction. 精神分裂症中的伽马振荡和钾通道调节：针对 GABA 能功能障碍。

IF 2 4区医学

Clinical EEG and Neuroscience Pub Date : 2024-03-01 Epub Date: 2023-01-02 DOI: 10.1177/15500594221148643

Stephen J Kaar, Judith F Nottage, Ilinca Angelescu, Tiago Reis Marques, Oliver D Howes

{"title":"Gamma Oscillations and Potassium Channel Modulation in Schizophrenia: Targeting GABAergic Dysfunction.","authors":"Stephen J Kaar, Judith F Nottage, Ilinca Angelescu, Tiago Reis Marques, Oliver D Howes","doi":"10.1177/15500594221148643","DOIUrl":"10.1177/15500594221148643","url":null,"abstract":"Impairments in gamma-aminobutyric acid (GABAergic) interneuron function lead to gamma power abnormalities and are thought to underlie symptoms in people with schizophrenia. Voltage-gated potassium 3.1 (Kv3.1) and 3.2 (Kv3.2) channels on GABAergic interneurons are critical to the generation of gamma oscillations suggesting that targeting Kv3.1/3.2 could augment GABAergic function and modulate gamma oscillation generation. Here, we studied the effect of a novel potassium Kv3.1/3.2 channel modulator, AUT00206, on resting state frontal gamma power in people with schizophrenia. We found a significant positive correlation between frontal resting gamma (35-45 Hz) power (n = 22, r = 0.613, P < .002) and positive and negative syndrome scale (PANSS) positive symptom severity. We also found a significant reduction in frontal gamma power (t13 = 3.635, P = .003) from baseline in patients who received AUT00206. This provides initial evidence that the Kv3.1/3.2 potassium channel modulator, AUT00206, may address gamma oscillation abnormalities in schizophrenia.","PeriodicalId":10682,"journal":{"name":"Clinical EEG and Neuroscience","volume":" ","pages":"203-213"},"PeriodicalIF":2.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10851642/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10517718","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The Hybrid Deep Learning Model for Identification of Attention-Deficit/Hyperactivity Disorder Using EEG. 基于脑电识别注意缺陷/多动障碍的混合深度学习模型。

IF 2 4区医学

Clinical EEG and Neuroscience Pub Date : 2024-01-01 Epub Date: 2023-09-08 DOI: 10.1177/15500594231193511

Nupur Chugh, Swati Aggarwal, Arnav Balyan

{"title":"The Hybrid Deep Learning Model for Identification of Attention-Deficit/Hyperactivity Disorder Using EEG.","authors":"Nupur Chugh, Swati Aggarwal, Arnav Balyan","doi":"10.1177/15500594231193511","DOIUrl":"10.1177/15500594231193511","url":null,"abstract":"Common misbehavior among children that prevents them from paying attention to tasks and interacting with their surroundings appropriately is attention-deficit/hyperactivity disorder (ADHD). Studies of children's behavior presently face a significant problem in the early and timely diagnosis of this disease. To diagnose this disease, doctors often use the patient's description and questionnaires, psychological tests, and the patient's behavior in which reliability is questionable. Convolutional neural network (CNN) is one deep learning technique that has been used for the diagnosis of ADHD. CNN, however, does not account for how signals change over time, which leads to low classification performances and ambiguous findings. In this study, the authors designed a hybrid deep learning model that combines long-short-term memory (LSTM) and CNN to simultaneously extract and learn the spatial features and long-term dependencies of the electroencephalography (EEG) data. The effectiveness of the proposed hybrid deep learning model was assessed using 2 publicly available EEG datasets. The suggested model achieves a classification accuracy of 98.86% on the ADHD dataset and 98.28% on the FOCUS dataset, respectively. The experimental findings show that the proposed hybrid CNN-LSTM model outperforms the state-of-the-art methods to diagnose ADHD using EEG. Hence, the proposed hybrid CNN-LSTM model could therefore be utilized to help with the clinical diagnosis of ADHD patients.","PeriodicalId":10682,"journal":{"name":"Clinical EEG and Neuroscience","volume":" ","pages":"22-33"},"PeriodicalIF":2.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10239399","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

EEG Asymmetry Characteristics in Relation to Childhood Anxiety Subtypes: A Dimensional Approach. 脑电图不对称特征与儿童焦虑亚型的关系:一个维度的方法。

IF 2 4区医学

Clinical EEG and Neuroscience Pub Date : 2024-01-01 Epub Date: 2023-01-05 DOI: 10.1177/15500594221150213

Nathaniel A Shanok, Nancy Aaron Jones

{"title":"EEG Asymmetry Characteristics in Relation to Childhood Anxiety Subtypes: A Dimensional Approach.","authors":"Nathaniel A Shanok, Nancy Aaron Jones","doi":"10.1177/15500594221150213","DOIUrl":"10.1177/15500594221150213","url":null,"abstract":"Introduction: Right frontal EEG asymmetry has been a commonly neurophysiological marker of anxiety and depressive symptoms throughout development. Method: In the current study, EEG asymmetry measures in frontal and parietal regions were examined as markers for specific subtypes of childhood anxiety disorder (eg, panic, generalized, social, separation, and school avoidance). Results: Notably, panic trait levels were significantly associated with prefrontal and lateral frontal alpha asymmetry, general anxiety was predicted by parietal beta asymmetry measures, and social anxiety levels were associated with mid-frontal alpha and beta asymmetry. School avoidance was significantly correlated with prefrontal and lateral frontal beta asymmetry scores; however, no significant findings were detected relating to separation anxiety which is considered unique to childhood anxiety. Discussion: In all cases, increased anxiety subtype scores related to a rightward shift in asymmetry, signifying this trait as a key neurophysiological marker of childhood anxiety symptoms. Conclusion: Overall, biomarker research of specific subtypes of broad conditions like anxiety could be highly useful for facilitating a deeper understanding of the mechanisms involved, as well as customizing treatment approaches.","PeriodicalId":10682,"journal":{"name":"Clinical EEG and Neuroscience","volume":" ","pages":"34-42"},"PeriodicalIF":2.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10489777","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: 1