Nearly 50 million people are afflicted with epilepsy, worldwide. These patients suffer from unprovoked seizures, where neurons in the cerebral cortex under go uncontrolled, hypersynchronous firing of neurons. 30\% of patients with epilepsy do not respond to drug treatments. For these patients, surgical treatment involving the removal or disconnection of brain matter is one of the only alternatives. Such surgical treatments often rely on long-term monitoring of neuronal activity in the brain using subdurally implanted surface electrodes to locate the epileptic focus, but these clinical methods for mapping neuronal activity suffer from low spatial resolutions and poor noise, which can limit the success of surgical treatments where an error of even 1 mm can be critical. The work described here involves the development of an implantable system for performing optical recordings of intrinsic signal (ORIS) on the surface of the brain. By taking advantage of the unique absorption spectrum of hemoglobin, cerebral blood volume (CBV) can be measured via reflectivity changes in the brain at at specific wavelengths of light. Due to the metabolic demands of the brain, the exaggerated neuronal activity and spiking associated with epileptic seizures can be detected indirectly through changes in CBV. While high resolution ORIS measurements have been recorded using externally mounted CCD sensors, this work presents some of the first developments in producing a fully implantable ORIS sensor. Progress in the development of an implantable ORIS sensor described here includes: an implantable organic light emitting diode (OLED) and organic photodetector (OPD) integrated on a highly flexible parylene-c substrate, an implantable sensor using a microLED array embedded on a flexible polyimide substrate, and the application of quantum dots to microLEDs for optical down-conversion. Successful in vivo detection of seizures is achieved with high signal-to-noise using these methods. Additionally, spatial localization of seizure activity is performed using the microLED array. These developments represent crucial first steps in the development of a full 2D neuronal mapping system using implantable ORIS devices.

Functional magnetic resonance imaging (fMRI) as it exists, in its many forms and vari- ants, has revolutionized the fields of neurology and psychology by revealing functional differences non-invasively. Although blood oxygenation level dependent (BOLD) fMRI is used interchangeably with fMRI, it measures one single difference in a phys- iological measurement using a set sequence. As such, there are other established changes in the brain that relate to blood movement and capacity that can also be measured using MRI. One measure, exogenous steady state cerebral blood volume, uses a bolus routine contrast agent administered intravenously alongside a pair of high resolution ‘structural-like’ MRI images to provide detailed information within small cortical and subcortical structures. In this thesis I design a semi-automated algorithm to generate maps of steady state exogenous cerebral blood volume magnetic resonance imaging datasets. To do this I developed an algorithm and tested it on existing MRI scanning protocols. A series of automated pre-processing steps are developed and tested, including automated scan flagging for artifacts and requisite vascular segmentation. Then, a methodology is developed to create cerebral blood volume (CBV) region of interest (ROI) masks that can then be applied on an existing database to test known CBV dysfunction in a group of patients at high risk for psychosis. Finally, we develop an experiment to see if template based cerebral blood alterations co-registered with class segmentation maps have any positive predictive value in determining disease state in a well characterized cohort of five age-matched groups in an Alzheimer’s disease neuroimaging study.