Structure-function coupling reveals seizure onset connectivity patterns

Abstract

The implications of combining structural and functional connectivity to quantify the most active brain regions in seizure onset remain unclear. We obtained structural connectomes from diffusion MRI (dMRI) and functional connectomes from electroencephalography (EEG) to assess whether high structure-function coupling corresponded with the seizure onset region. We mapped individual electrodes to their nearest cortical region to allow for a one-to-one comparison between the structural and functional connectomes. A seizure laterality score and expected onset zone were defined. The patients with well-lateralised seizures revealed high structure-function coupling consistent with the seizure onset zone. However, a lower seizure lateralisation score translated to reduced alignment between the high structure-function coupling regions and the seizure onset zone. This feasibility study tested a new model for incorporating dMRI in clinical practice. We illustrate that dMRI, in combination with EEG, can improve the identification of the seizure onset zone. Our model may be valuable in enhancing ultra-long-term monitoring by indicating optimal, individualised electrode placement.

Deep learning distinguishes focal epilepsy groups using connectomes: Feasibility and clinical implications

“…The analysis of structural connectomes in focal epilepsy has yielded a range of network-based biomarkers that may aid pre-surgical selection and pharmacological treatment planning [6,13,14]. The combination of structural connectomes with functional data from electroencephalography (EEG) has revealed the influence of structurefunction coupling in seizure dynamics [15,16], seizure propagation [17], and postoperative seizure freedom [18]. Importantly, phenomenologic models have shown that structural alterations can give rise to FBTCS [19].…”