Epilepsy surgery is an invasive procedure that removes the part of the brain thought to cause seizures. This procedure fails to completely stop seizures in many patients, in part due to the difficulty of accurately localising the problematic neural tissue.
In our pilot study and review in 2014, we suggested approaches for improving localisation and predicting surgical outcome using new data and analysis methods. Since then, we have shown that interictal functional networks combined with computational models can predict surgical outcome and suggest alternative surgery locations.
Another study used diffusion imaging data with a machine learning model to find white matter connections that best predict surgical outcome.
We have multiple other studies using scalp EEG, intracranial EEG, MEG, and MRI to localise epileptogenic tissue. Check out our publications for more examples, including studies performing multimodal integration of several modalities.