Nonlinear Kalman-filtering estimation of unobserved cortical layer population activity from EEG recordings in a realistic cortical microarchitecture model

الموضوعات

علوم تطبيقية وتكنولوجية

الملخص

The Electroencephalogram (EEG) measures global brain electrical activity using electrodes placed on the scalp. EEG measurement continues to be an important tool for understanding brain dynamics since it is closely related to the underlying neuronal activity in real time. A main challenge in relating EEG to its neural origin is the non-uniqueness of possible sources (or so called inverse solution). In this regard, constraining the estimation problem using realistic models of EEG generation can produce a small set of potential source configurations. In this thesis we aim to, first, introduce a set of neuro-physiologically plausible models that simulate EEG generation and, second, to employ novel nonlinear estimation tools based on Kalman filtering to identify, within the developed models, a set of key parameters that affect EEG generation under specific cognitive states. Cubature kalman filter (CKF), a state of art nonlinear estimator developed in 2009 and recently applied in neuroscience on understanding fMRI signals, is used for the first time for estimation based on EEG signals in order to reveal contributing neural brain dynamics and localize current sources. The thesis presents simulation and estimation results based on a case scenario of idling and attentive processing in the early and intermediate visual cortical areas (V1-V4, IT) relying on recent literature describing intra-cortical origins of alpha oscillations collected in awake behaving monkeys. Overall, CKF estimation shows accurate prediction of hidden neuronal firing in the simulated model despite the highly nonlinear interaction between cortical populations within lamina and across hierarchies in the visual cortex.

روابط وملفات

التعريف والنوع

رقم الوثيقة

f501868a-dc96-4fbd-ac1b-4be6226d4e42

رقم العقد

0

نوع الوسائط

Crawler

نوع المحتوى

الرسائل العلمية

صيغة المصدر

رسائل ماجيستير

نوع الملف

pdf text

أسماء الملفات

1635947_1.pdf

بيانات النشر

ألقاب المؤلفين

[{"name_ar":"حسان سمير فرحات","title_ar":"اعداد","title_en":"Preparation"},{"name_ar":"فادي كرامة","title_ar":"اشراف","title_en":"Supervision"}]

اللغة

English

المصدر والدورية

اسم المصدر

Nonlinear Kalman-filtering estimation of unobserved cortical layer population activity from EEG recordings in a realistic cortical microarchitecture model

المحتوى والصفحات

عدد الصفحات

0

إشراف وإعداد

الإشراف

فادي كرامة

الإعداد

حسان سمير فرحات

الاقتباسات الببليوغرافية