Networks in Epilepsy Surgery

Epilepsy surgery has emerged as an important and possibly curative treatment for many treatment resistant focal epilepsies. However, it is becoming increasingly clear that even 'focal' epilepsy is a dynamic condition involving a whole network of brain areas. Predicting whether or not surgery can be successful, and identifying which surgical approach will lead to seizure freedom still remains a challenge.  

In this research stream, we are applying advanced computational modelling of neuronal dynamics to intracranial EEG recordings from paediatric patients undergoing evaluation for epilepsy surgery. We are hoping that this work will help improve our planning for epilepsy surgery to help as many patients as possible achieve seizure freedom.

Collaborators

Rachel Thornton
Consultant Neurophysiologist
Great Ormond Street Hospital, London (UK)

Martin Tisdall
Consultant Neurosurgeon
Great Ormond Street Hospital, London (UK)

Pierre Bourdillon
Neurosurgeon
University Hospitals,
Lyon (France)

Yujiang Wang
Research Fellow
Newcastle University,
Newcastle (UK)

Gabrielle Schroeder
Doctoral Student
Newcastle University, 
Newcastle (UK)


Subnetworks.png

Using a dynamic causal modelling approach may be helpful to make quantitative predictions for epilepsy surgery

Figshare: Patient-specific SEEG model

29378229-32a5129e-82b6-11e7-90e9-3d9b14250b56.png

Using a mixture of functional-connectivity based approaches, and dynamic causal modelling, this code infers the generative structure underlying SEEG recordings

Github: SEEG Networks