Epilepsy affects millions of individuals worldwide. Functional magnetic resonance imaging (fMRI) already has been integrated into the clinical evaluation and treatment process for epilepsy to lateralize and localize language function. Repurposing the data can provide new insights about how epilepsy affects language function and improve performance of established methods in diagnosis and treatment of epilepsy. Two avenues of research in fMRI for epilepsy have been the analysis of task-induced brain activity, which we hope to expand on, and the analysis of resting state data, which we hope to improve through the generation of simulated resting state data. We aim to use the clinical language task fMRI data available to characterize the language network in patients with epilepsy and generate resting state fMRI data from task-based data. Future work could focus on various metrics to better describe the language network and improving the quality of generated resting state approximations.