Intellectual Merit: For this proposal, we will develop a neurobiologically-based instrument to identify seizure foci in epilepsy. Seizures gradually destroy the brain; therefore, early intervention is critical to maximize chances of full recovery. For the roughly one third of all patients whose seizures cannot be managed through medication, the most common treatment option is surgical removal of the brain areas thought to be seizure foci. However, the procedure assumes that foci can be identified with precision. When they cannot be identified through standard techniques in neuroimaging, as in about half of all patients with medication-resistant focal epilepsy, the options are either no treatment or surgical trial and error, both of which can lead to neurodegeneration as severe as the disease itself. Entropic methods adapted from dynamical systems and statistical physics have been applied to EEG to identify seizures, and most recently have been applied to the identification of seizure foci, with some success. However, clinical adoption of these techniques has failed due to EEG's poor spatial resolution and inability to access sub-cortical regions commonly implicated in seizures. FMRI has the three-dimensional whole brain coverage and spatial resolution required for identifying neurosurgical targets. Unfortunately, hemodynamic time-series are typically too short and sparse to permit application of most standard information theoretic methods, and the degree to which fMRI acquisition and processing techniques preserve signal dynamics is a fundamental engineering question that remains unaddressed. The proposed three-year research plan provides for comprehensive optimization, including innovations in acquisition, hardware, software, and analytical techniques, and is comprised of four parts. First, we will assess and improve the fidelity of fMRI dynamics. This includes both instrumentation development of a Dynamic Phantom for fMRI, for the first time permitting quantitative comparison/correction between known "hemodynamic" inputs and signal outputs at each stage of the image processing pipeline, as well as between time-series acquired from the same spatial coordinates using intracranial EEG (the "gold standard"), scalp EEG, and fMRI. Second, in order to aid in identification of network abnormalities, we will derive normative masks to control for stimulus or default-network activation patterns. Third, we will investigate the relationship between abnormalities of signal complexity and network connectivity, the latter of which has critical implications for understanding the etiology of seizure vulnerability at the synaptic level. Finally, we will use support vector machine to develop automated algorithms for identification of putative seizure foci, as confirmed by intracranial electrodes and/or seizure freedom following surgical resection. If successful, our proposed direction would culminate in providing neurosurgeons with a potentially revolutionary advance in surgical treatment of intractable cryptogenic epilepsy, and thus satisfies the mission of the NSF funding mechanism, designed to support "significant advancement of fundamental engineering and scientific knowledge" rather than incremental improvements. This proposal integrates development of computational techniques and instrumentation with direct clinical applications.
Broader Impact: In 2007, the National Academy of Science, National Academy of Engineering, and Institute of Medicine were charged by Congress to form a committee to address the challenges associated with maintaining scientific innovation and economic competitiveness within an increasingly global economy. For this proposal, we will focus on addressing specific recommendations. an action item was to strengthen children's K-12 preparation in science and technology by enhancing the science and engineering education of the science teachers themselves. The action item will be addressed through the development of a hands-on engineering design and innovation curriculum for grades 1-6. This curriculum will be iteratively tested and refined in a socioeconomically-diverse school, disseminated through our website, and will include follow-up NWEA individualized assessment to measure efficacy in improving student STEM performance. By training students in the lab to develop engineering design and innovation in their own research, and then training them to teach teachers and elementary school students the same conceptual tools at a more basic level, we are able to integrate our research and educational goals to the fullest extent possible.
