White matter contribution to outcome in epilepsy surgery
Abstract
Traditional models for function and dysfunction in focal epilepsy are cortico-centric, both localised to regions in the cortex. Evidence from direct white matter stimulation in awake surgery as well as seizure control from thalamic neuromodulation, however, oppose this, suggesting both cognition and epilepsy may be organised in circuits composed of white matter pathways. This thesis investigates how specific white matter pathways influence surgical outcomes in patients with drug-resistant epilepsy. My findings challenge the concept of focal epilepsy as a localised disorder. Analysis of seizure recurrence patterns and predictors of lasting seizure freedom reveal an epileptogenic network that extends beyond the boundaries of focal resections. This network organisation may explain why some patients experience late seizure recurrence, and how thalamostriatal disconnection is associated with lasting seizure freedom in frontal lobe epilepsy surgery. In a novel technique leveraging specific tract stimulation with white matter contacts of epilepsy patients implanted with depth electrodes, I suggest that white matter pathways may have specific contributions to function, and that this can be exploited to map and avoid damage to tracts critical to behaviour in both hemispheres. In summary, my data provide compelling evidence that both cognition and epilepsy are organised as distributed circuits rather than regionally localised. By targeting epileptic networks as circuits rather than lesions, additional seizure control may be achieved while preserving cognitive function. This circuit-based understanding has important implications for epilepsy surgery, as circuit-based approaches may lead to novel surgical strategies that blur the traditional distinction between "focal" and "generalized" epilepsies.
Fields of Study & Subjects
Epilepsy research and treatment
Neurological disorders and treatments
Vagus Nerve Stimulation Research
Publication details
- Journal / source
- UCL Discovery (University College London)
- Publication date
- 28 January 2026
- Language
- EN
- Document type
- Thesis