LARGE-SCALE EEG-FMRI DATA EXPLORATION APPLIED TO EPILEPSIES

• Grant number: 17/25795-7
• Support Opportunities: Regular Research Grants
• Start date: May 01, 2018
• End date: October 31, 2020
• Field of knowledge: Health Sciences - Medicine - Medical Radiology
• Principal Investigator: Brunno Machado de Campos
• Grantee: Brunno Machado de Campos
• Host Institution: Faculdade de Ciências Médicas (FCM). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil
• Associated researchers: Ana Carolina Coan ; Clarissa Lin Yasuda ; Fernando Cendes ; Marina Koutsodontis Machado Alvim ; Natalia Paschoal Divino

Abstract

Epilepsy is a debilitating condition characterised by recurrent, unprovoked seizures. It is one of the most common neurological disorders in children and adults. Patients with focal epilepsy who do not respond to medication might benefit from another treatment option: surgical resection to remove the part of the brain that is most implicated in generating seizures (the epileptogenic zone) and that may yield seizure control. The success of this approach depends on the ability to identify the epileptogenic zone and 30-40% of patients persist with seizures after surgery. There is an urgency to develop methods/techniques capable to delineate precisely the epileptogenic zone in individual patients, similarly to the requirements of personalized treatment for cancer, in which "precision medicine" has offered better outcomes for patients.The combination of EEG and functional MRI (EEG-fMRI) permits a non-invasive simultaneous measurement of the neural activity taking advantage of the high spatial resolution of MRI and the high temporal resolution of the EEG. The EEG-fMRI technique has the potential to reveal the hemodynamic changes related to epileptiform discharges, thereby helping to predict the epileptogenic zone as well as the improving the diagnosis and management of individual patients. We will focus on the use of functional connectivity (FC), an increasingly widely applied technique for brain imaging, which is able to provide differentiation of a wide variety of neurological and psychiatric disorders. The exploration of FC with EEG-fMRI data enables highly reliable and controlled data to address fundamental questions about brain organisation and how it is disrupted by epilepsy. The addition of physiological information along with confirmation and characterisation of the rest condition through EEG patterns may improve data quality and allow more sophisticated inferences about the dynamic connectivity between brain regions.This project will address these issues, building on the expertise at UNICAMP to provide new developments in EEG-fMRI analysis. The improved understanding of the epileptic brain and the methods we will develop to characterise it will provide open access tools for the neuroscience community, generate high impact papers at the interface between basic and clinical science. (AU)