EAGER: Using Network Dynamic fMRI for Pre-Surgical Localization of Epileptogenic Foci

Suny At Stony Brook, Stony Brook NY

Investigators

Abstract

PI: Mujica-Parodi, L., Millett, D. E. and Shaw, S. Proposal Number: 1141995 INTELLECTUAL MERIT Intractable epilepsy is often treated surgically through the ablation of presumed epileptogenic foci, yet there exists a significant portion of patients for whom foci cannot currently be identified with precision through standard diagnostic techniques (EEG, MRI, PET). Information-theoretic 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. While fMRI has excellent spatial resolution, its hemodynamic time-series are significantly too short and sparse to permit application of most standard information theoretic methods, such as time-delay embedding, fractal dimension, and entropy. The research proposed in this application is designed to establish the clinical utility of computational techniques that combine the sensitivity to circuit dysregulation found in EEG with the spatial resolution found in fMRI, thereby defining a fundamentally new direction for future clinical research. In this application, we will develop techniques for the application of power spectrum scale invariance to fMRI time-series, a method we have previously shown to have utility with respect to the identification and anatomical localization of dysregulation within the paralimbic circuit. These techniques will be tested in the identification of epileptogenic foci, validated by comparison with standard neuropsychological assessment, intracranial monitoring, and/or surgical outcomes. BROADER IMPACTS Approximately three million Americans suffer from epilepsy; it is estimated that fully two thirds of these individuals are unsuccessfully treated by the current state of the art. Successfully managing the disease early is critical, since repeated seizures can cause irreversible brain damage and death. Because the current state of the art is not capable of clearly identifying epileptogenic foci with the high degree of spatial resolution required for successful surgical intervention; if successful, our proposed direction would revolutionize treatment of intractable epilepsy. This proposal is unique in that it is organically interdisciplinary, integrating computational techniques adapted from dynamical systems and statistical physics with direct and immediate clinical applications, and thus fits within the scope of the National Science Foundation's GARDE program and EAGER funding mechanism by addressing the treatment of disability through the novel and transformative development of advanced engineering tools.