Biomedical Engineering and Bioengineering Commons^™

High Frequency Oscillations In The Epileptic Brain: Accurate Detection, Effect Of Vigilance State, And Sample Size Considerations, Amir Fared Partu Al-Bakri

Theses and Dissertations--Biomedical Engineering

About a third of all epilepsy patients may experience seizures that are resistant to medication. Surgical resection may be an option for some of these patients, but localization of the epileptogenic zone is difficult and expensive. For this process, the seizures must be observed and recorded in a clinical setting over several days. High-frequency oscillations (HFOs) have emerged as a possible biomarker for predicting the epileptogenic zone from a brief interictal recording of brain electrical activity without having to wait for seizures. The broad objective of this dissertation is to devise methods and criteria for accurate detection, sampling and localization …

Differentiating Epileptic From Psychogenic Nonepileptic Eeg Signals Using Time Frequency And Information Theoretic Measures Of Connectivity, Sarah Barnes

Masters Theses

Differentiating psychogenic nonepileptic seizures from epileptic seizures is a difficult task that requires timely recording of psychogenic events using video electroencephalography (EEG). Interpretation of video EEG to distinguish epileptic features from signal artifacts is error prone and can lead to misdiagnosis of psychogenic seizures as epileptic seizures resulting in undue stress and ineffective treatment with antiepileptic drugs. In this study, an automated surface EEG analysis was implemented to investigate differences between patients classified as having psychogenic or epileptic seizures. Surface EEG signals were grouped corresponding to the anatomical lobes of the brain (frontal, parietal, temporal, and occipital) and central coronal …

Connectivity Analysis Of Electroencephalograms In Epilepsy, Panuwat Janwattanapong

FIU Electronic Theses and Dissertations

This dissertation introduces a novel approach at gauging patterns of informa- tion flow using brain connectivity analysis and partial directed coherence (PDC) in epilepsy. The main objective of this dissertation is to assess the key characteristics that delineate neural activities obtained from patients with epilepsy, considering both focal and generalized seizures. The use of PDC analysis is noteworthy as it es- timates the intensity and direction of propagation from neural activities generated in the cerebral cortex, and it ascertains the coefficients as weighted measures in formulating the multivariate autoregressive model (MVAR). The PDC is used here as a feature extraction …

Brain Connectivity Networks For The Study Of Nonlinear Dynamics And Phase Synchrony In Epilepsy, Hoda Rajaei

FIU Electronic Theses and Dissertations

Assessing complex brain activity as a function of the type of epilepsy and in the context of the 3D source of seizure onset remains a critical and challenging endeavor. In this dissertation, we tried to extract the attributes of the epileptic brain by looking at the modular interactions from scalp electroencephalography (EEG). A classification algorithm is proposed for the connectivity-based separation of interictal epileptic EEG from normal. Connectivity patterns of interictal epileptic discharges were investigated in different types of epilepsy, and the relation between patterns and the epileptogenic zone are also explored in focal epilepsy.

A nonlinear recurrence-based method is …

Developing An Imaging Biomarker To Detect Aberrant Brain Connectivity In Individual Patients, Esther Cox

Master's Theses (2009 -)

Resting state functional MRI (rsfMRI) has been proven to be a valuable tool in clinical applications such as pre-surgical mapping, but there is not yet a functional and usable algorithm that can be used by physicians in a clinical setting to evaluate an individual patient for diseases and aberrant brain connectivity. If a physician wants to evaluate a patient in this way, the rsfMRI data must be looked at “by hand,” i.e. the physician must manually evaluate the data and identify the functional ICN’s and whether they are normal or aberrant. An algorithm that would automate this process and supplement …

The Effects Of Vagus Nerve Stimulation On Neuroinflammation In Epilepsy, Elizabeth A. St. Clair, Gabriel O Albors, Pedro Irazoqui Dr., Amy Brewster

The Summer Undergraduate Research Fellowship (SURF) Symposium

Epilepsy is a neurological disorder characterized by chronic, unexplainable seizures. Recurring epileptic seizures are associated with long-term structural damage and cognitive deficits, and can even lead to sudden, unexplainable death. Approximately 30% of epilepsy cases are not responsive to medication. Epileptic seizures often induce inflammation in the brain and may increase the frequency of future seizures, resulting in a detrimental cycle. Vagus nerve stimulation (VNS) is a non-pharmaceutical treatment method for epilepsy that has been shown to reduce inflammation in peripheral pathways. The role of VNS in the modulation of neuroinflammation has yet to be demonstrated experimentally. To explore this, …

Experimental-Computational Analysis Of Vigilance Dynamics For Applications In Sleep And Epilepsy, Farid Yaghouby

Theses and Dissertations--Biomedical Engineering

Epilepsy is a neurological disorder characterized by recurrent seizures. Sleep problems can cooccur with epilepsy, and adversely affect seizure diagnosis and treatment. In fact, the relationship between sleep and seizures in individuals with epilepsy is a complex one. Seizures disturb sleep and sleep deprivation aggravates seizures. Antiepileptic drugs may also impair sleep quality at the cost of controlling seizures. In general, particular vigilance states may inhibit or facilitate seizure generation, and changes in vigilance state can affect the predictability of seizures. A clear understanding of sleep-seizure interactions will therefore benefit epilepsy care providers and improve quality of life in patients. …