It is known that temporal lobe epilepsy (TLE) causes seizures with widespread effects across the brain that result in complex events including loss of consciousness and motor phenomena. Additionally, repeated seizures can also produce cognitive deficits, primarily of memory and language related functions, suggesting an interaction between seizure propagation networks and those associated with these cognitive functions. These extensive connections and their potential interaction may play an important role in determining whether a drug-resistant TLE patient becomes seizure free and is without cognitive decline after surgical resection of the seizure focus. Therefore, the challenge is to quantify neuronal reorganization in TLE and utilize this information to accurately predict post-surgical seizure and cognitive outcome in order to identify the most appropriate surgical candidates. The overall goal of this project is to investigate and quantify the relationship between functional and structural network integrity in seizure propagation and language networks in TLE non- invasively using Magnetic Resonance Imaging (MRI); and to relate these network alterations to disease and cognitive characteristics before and after surgery. Both functional connectivity and structural connectivity will be measured in seizure propagation and language and memory networks of TLE patients prior to surgical treatment. The structural connectivity will be quantified with diffusion tensor MRI methods, while functional MRI will be used to determine the functional connectivity parameters. These measures will be compared to healthy controls, and the relationships between functional and structural connectivity in the networks will be determined. The structural and functional connectivity of the networks will then be related to the disease characteristics and language and memory function of the patients prior to surgery. Finally, a novel statistical method, robust Biological Parametric Mapping (rBPM), will be used to develop multivariate, multimodal linear models of presurgical MRI connectivity, disease characteristics and neuropsychological test scores to predict post-surgical seizure and cognitive outcome. The ultimate impact of this research is to provide the link between the structure, function and behavior of the two most relevant and widespread brain networks in TLE. This information would provide a significant advancement in identifying and quantifying neural reorganization and its consequences associated with this condition; and may improve clinical treatment of this disease by providing a more accurate method to predict post-surgical seizure and cognitive outcome in these patients. Furthermore, the proposed approach may be expanded and applied to other forms of focal epilepsy in both adults and children to increase the utilization of surgical treatment for these patients.
The ultimate goal of this study is to determine how temporal lobe epilepsy affects widespread functional networks across the brain in order to understand how this disease causes seizures and cognitive defects in patients. This information is essential to efficiently develop methods to diagnose and treat these patients successfully.
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