0% Complete
فارسی
Home
/
سی و دومین کنفرانس ملی و دهمین کنفرانس بین المللی مهندسی زیست پزشکی ایران
Mapping Epileptic Networks: IED-Triggered Hemodynamic Changes Identified via Simultaneous EEG-fMRI Recordings
Authors :
Elias Ebrahimzadeh
1
Mostafa Asgarinejad
2
Melika Akbarimehr
3
Hamid Soltanian-Zadeh
4
1- دانشگاه تهران دانشکده علوم مهندسی
2- موسسه آموزش عالی علوم شناختی
3- دانشگاه علوم پزشکی قم
4- دانشگاه تهران دانشکده علوم مهندسی
Keywords :
Simultaneous EEG-fMRI،Epilepsy،Independent Component Analysis (ICA)،Blood-oxygen-level dependent imaging (BOLD)،Generalized Linear Model (GLM)
Abstract :
A primary objective in presurgical evaluation for refractory focal epilepsy is the precise delineation of the epileptogenic zone (EZ)—the cortical area essential for seizure generation. Given that electroencephalography (EEG) provides superior temporal resolution while functional magnetic resonance imaging (fMRI) offers enhanced spatial localization, integrating these modalities holds significant promise for improving epileptic focus identification. In this study, we first derived characteristic spike patterns by detecting and averaging interictal epileptiform discharges (IEDs) from extraoperative EEG recordings. These patterns were then correlated with intracranial EEG data to develop an automated system for precise temporal mapping of seizure activity. Finally, we convolved the resulting temporal regressor with the hemodynamic response function (HRF) within a general linear model (GLM) framework to achieve robust localization of epileptic foci. This study was performed on five medication-resistant epilepsy patients whose neuroimaging and electrophysiological data were acquired at the National Brain Mapping Lab (NBML). Our proposed methodology demonstrated strong concordance with clinical EEG findings across all five cases. Notably, for the three surgical candidates, the approach provided additional localizing information beyond conventional EEG data. Quantitative analysis revealed statistically significant enhancements in both localization accuracy (p<0.05) and spatial precision (mean ± SEM: 2.3 ± 0.4 mm) compared to current gold-standard techniques reported in recent literature.
Papers List
List of archived papers
A survey over deep learning methods for early detection in mammogram images
Zeinab Shirkool - Mohammad Ali Tabarzad - Reza Boostani
بهبود راهکار انتخاب ویژگی ترکیبی با ارزیابی یکپارچه روابط خطی و غیرخطی ویژگیها
سید مجتبی سیف
Deep Brain Stimulation with a Computational both combined Biphasic and Monophonic square pulse Model for the Essential Tremor of CBGTHC Network of the Parkinson’s Disease
Shabnam Andalibi Miandoab - Nazlar Ghasemzadeh
A vortex-promoting cross-junction microchannel for efficient hydroporation in immunotherapy applications
Soheil Mahdavi - Zohre Nazemi Dehkordi - Ali Abouei Mehrizi
Dynamics modeling of cardiac electromechanical intervals and hysteresis analysis
Sina Asadi - Mohammad Bagher Shamsollahi
Investigating the impact of arm swing on lower limb forces using machine learning techniques
Mohammad Reza Seidgar - Hadi Farahani - Mostafa Rostami - Elham Naziri - Sadegh Madadi
بهبود تشخیص تومور مغزی با استفاده از ترکیب شبکه های عمیق به روش رای اکثریت
مریم صباغ کاخکی - عقیله حیدری
تهدیدهای حریم خصوصی در شهرهای هوشمند
محمد امیری نسب - محمد عادلی نیا
مکان یابی ایستگاههای آتشنشانی با استفاده از الگوریتم بهینهسازی ازدحام ذرات
مهدی عزیزمحمدی - سید محسن میرحسینی - آرش شعبانی
بررسی عوامل موثر و پیامدهای افشاگری تقلب در میان شاغلین حسابداری
زهره عارف منش - زهرا سادات خاشعی
more
Samin Hamayesh - Version 42.4.1