Investigating Epileptic and Functional Networks in Patients with Drug Resistant Focal Epilepsy

National Institute Of Neurological Disorders And Stroke

Investigators

Linked publications & trials

Abstract

Over the past year, my lab has continued to devote significant effort to this project, continuing to acquire functional and structural neuroimaging data, electroencephalography (EEG) and magnetoencephalography (MEG) data, and clinical and neuropsychological data in patients with drug resistant epilepsy undergoing clinical pre- and post-surgical evaluations. Over the past year, we have continued our work in developing novel imaging biomarkers for seizure focus lateralization and/or localization. We previously developed an MRI postprocessing method to aid with detection of focal cortical dysplasias which are often epileptogenic. This has continued to be an important clinical tool for our patients undergoing presurgical evaluation. We also previously explored the utility of ASL to lateralize perfusion changes in temporal lobe epilepsy, finding ipsilateral temporal hypoperfusion, although with asymmetric hypoperfusion in patients with lesional and not non-lesional temporal lobe epilepsy. This past year, we have optimized the use of similar image processing tools and a machine learning approach to improve tissue segmentation in structurally abnormal brains and are using these segmentations to create automated resection masks in patients who undergo epilepsy surgery. This work will be submitted for publication in the near future. This past year, we also developed an approach using these same segmentation tools to identify enlarged perivascular spaces in 3T and 7T, which may help to lateralize seizure foci. We are also exploring whether increased enlarged perivascular spaces may also be useful in predicting surgical outcomes. The second goal of this project is related to exploring the relationship between propagation of epileptiform activity and underlying structural and functional networks in individual patients with epilepsy. In Withers et al. 2023, we found that white matter propagation can impact localization of sources of interictal epileptiform activity observed in intracranial EEG recordings. We used MRI diffusion tensor imaging obtained in our cohort of patients to estimate white matter connectivity in combination with spike timing observed during intracranial EEG recordings. We found that our source localization approach frequently identifies unique and at times distant potential sources of epileptiform activity that were not previously suspected. Over the past year, we have continued with this line of work, seeking to identify similar propagation patterns of interictal activity in magnetoencephalography (MEG) recordings in our patient cohort. Compared to invasive EEG recordings, MEG is complementary, retaining excellent temporal resolution and allowing for more widespread coverage across the cortical surface, although only obtained over minutes to hours. We have now developed processing pipelines in our lab to allow us to observe propagation patterns of interictal epileptiform activity non-invasively using distributed source modeling (dSPM). In Hayday et al. (Clinical Neurophysiology 2025), we showed that IED-related activations observed using dSPM localize to similar regions as the gold standard equivalent current dipole (ECD) approach. Indeed these area of activation are more stable over time than ECD localizations, and overlap more closely with areas of resection in seizure free patients. Within these areas of activation, using the high temporal resolution of MEG recordings, we have also been able to demonstrate timing consistent with both cortical traveling wave and white matter propagation (Srinivasan, submitted). During the next year, we hope to explore whether the discrete IED activation areas we have identified follow MRI-based estimates of structural and functional connectivity, as well as how these spiking regions compare to IED activity measured using intracranial EEG recordings. We have also contributed EEG data to a multisite collaborative effort through Sridevi Sarma and her lab aiming to develop novel biomarkers to diagnose epilepsy (Myers et al. 2025) and to predict epileptogenic zones and surgical success (Roy et al. 2025). Finally, as part of our ongoing epilepsy imaging study, we continue to prospectively obtain pre- and post-operative language and resting state functional MRI (fMRI) data. This data serves as the basis for several new and ongoing collaborative efforts. Over the past year, Dr. Nadia Biassou and her group (Acker et al. 2024) used data from this project to explore dynamic functional connectivity in relation to language task, and will continue these efforts over the coming year. Finally, we established two new collaborations over the past year. We have contributed resting state fMRI data to Thomas Yeo and his lab, with a manuscript currently in preparation comparing resting state brain networks created in patients with epilepsy at the individual and group levels in comparison with healthy volunteers. We hope to pursue this work further over the coming year. Also, we have begun a collaboration with Tina Liu, previously in NIMH and now at Georgetown University, exploring homotopic reorganization of the visual word form area following temporal lobe epilepsy surgery using reading task fMRI collected in our patient population pre- and post-operatively. We also plan to continue this collaboration over the coming year.