Signal Processing Commons^™

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 …

A Method For Non-Invasive, Automated Behavior Classification In Mice, Using Piezoelectric Pressure Sensors, Steven R. Gooch

Theses and Dissertations--Electrical and Computer Engineering

While all mammals sleep, the functions and implications of sleep are not well understood, and are a strong area of investigation in the research community. Mice are utilized in many sleep studies, with electroencephalography (EEG) signals widely used for data acquisition and analysis. However, since EEG electrodes must be surgically implanted in the mice, the method is high cost and time intensive. This work presents an extension of a previously researched high throughput, low cost, non-invasive method for mouse behavior detection and classification. A novel hierarchical classifier is presented that classifies behavior states including NREM and REM sleep, as well …