عنوان
پدید آورنده
موضوع
رده
کتابخانه
محل استقرار
شماره کتابشناسی ملی
شماره
TL50964
زبان اثر
زبان متن نوشتاري يا گفتاري و مانند آن
انگلیسی
عنوان و نام پديدآور
عنوان اصلي
Developing Non-Linear and Adaptive Neuronal Synchrony and Connectivity Analysis to Personalize Closed-Loop Dbs Therapy for Treating Epilepsy
نام عام مواد
[Thesis]
نام نخستين پديدآور
Farahmand, Sina
نام ساير پديدآوران
Mogul, David J.
وضعیت نشر و پخش و غیره
نام ناشر، پخش کننده و غيره
Illinois Institute of Technology
تاریخ نشرو بخش و غیره
2019
يادداشت کلی
متن يادداشت
117 p.
یادداشتهای مربوط به پایان نامه ها
جزئيات پايان نامه و نوع درجه آن
Ph.D.
کسي که مدرک را اعطا کرده
Illinois Institute of Technology
امتياز متن
2019
یادداشتهای مربوط به خلاصه یا چکیده
متن يادداشت
Epilepsy disease afflicts more than seventy million people worldwide. In approximately one third of the cases, antiepileptic medications fail to control seizures. Over the last few decades, electrical stimulation of the brain has been evaluated as a potential alternative to treat surgically and medically refractory epilepsy patients. Despite some successes, most of the devices using this protocol operate based on pre-determined stimulation parameters (e.g. frequency and location of stimulation) that have little or no relationship to the individuals' underlying brain dynamics, which we hypothesize may explain their low clinical efficacy in preventing or terminating seizures. In this study, a non-linear adaptive neuronal synchrony and connectivity analysis was developed in order to extract stimulation parameters from endogenous, multi-site brain dynamics of epilepsy patients. A non-linear analytical methodology was proposed to assess phase-synchrony dynamics in epilepsy patients as seizures evolve. This study revealed a desynchronization around seizure onset. However, the synchrony level started to increase gradually towards seizure end and reached its maximum at seizure termination. This results reveal that hyper-synchronization of the epileptic network may be a critical self-regulatory mechanism by which the brain terminates seizures. In the other phase of this study, a non-linear adaptive phase-connectivity analysis was developed in order to extract frequency and locations of stimulation that match the synchronized network dynamics at seizure termination. Matching these parameters to the endogenous brain dynamics of epilepsy patients as seizure naturally terminates may not only terminate seizures prior to their development, but it may also lead to a personalized deep brain stimulation (DBS) therapy with higher clinical efficacy.
اصطلاحهای موضوعی کنترل نشده
اصطلاح موضوعی
Bioengineering
اصطلاح موضوعی
Neurosciences
نام شخص به منزله سر شناسه - (مسئولیت معنوی درجه اول )
مستند نام اشخاص تاييد نشده
Farahmand, Sina
نام شخص - ( مسئولیت معنوی درجه دوم )
مستند نام اشخاص تاييد نشده
Mogul, David J.
شناسه افزوده (تنالگان)
مستند نام تنالگان تاييد نشده
Illinois Institute of Technology
دسترسی و محل الکترونیکی
نام الکترونيکي
مطالعه متن کتاب وضعیت انتشار
فرمت انتشار
p
اطلاعات رکورد کتابشناسی
نوع ماده
[Thesis]
کد کاربرگه
276903
اطلاعات دسترسی رکورد
سطح دسترسي
a
تكميل شده
Y
