Nucleus-specific thalamic involvement in seizure networks differentiates neuromodulation outcomes

Closed-loop neuromodulation via responsive neurostimulation (RNS) of the thalamus has emerged as a promising therapy for drug-resistant epilepsy (DRE), particularly in patients with broad or multifocal onset. However, response to thalamic RNS is inconsistent, and there is a crucial need to identify factors that distinguish responders from non-responders. Given the heterogeneous composition of the thalamus, the specific contributions of individual thalamic nuclei during seizures may explain the variability in outcomes between patients and could potentially serve as biomarkers for guiding target selection. We analyzed 129 seizures from 28 patients with DRE who underwent stereo-EEG monitoring with recordings of the centromedian (CM: n = 15) or pulvinar (PLV: n = 13) thalamic nuclei and were subsequently treated with RNS targeting the corresponding nucleus (CM: 11/15 [73%] responders; PLV: 7/13 [54%] responders). Patients were classified as responders (Engel class I-III) or non-responders (Engel class IV) based on reduction in seizure frequency. For each seizure, we constructed functional connectivity networks spanning seizure onset to termination and quantified the role of the thalamic nucleus by computing its total node strength. We also used an automated detection algorithm to measure the time of seizure spread to each thalamic nucleus relative to seizure onset. Connectivity and spread timing were then compared between responders and non-responders within each nucleus group. The timing of thalamic recruitment following seizure onset did not differ significantly between responders and non-responders in either nucleus, although CM responders showed a non-significant trend toward earlier recruitment. Analysis of functional connectivity revealed nucleus-specific patterns. CM responders exhibited significantly higher thalamic node strength than non-responders during the late-seizure phase, with no significant difference at early- or middle-seizure phases. PLV responders showed significantly higher thalamic node strength during the middle-seizure phase, but there was no significant difference at early- or late-seizure phases. These findings suggest that the degree and timing of thalamic involvement during seizures may serve as biomarkers for predicting response to thalamic RNS in DRE. CM involvement in responders was characterized by stronger connectivity that persisted through seizure termination, whereas PLV involvement in responders was reflected primarily in connectivity during seizure propagation and progression. Incorporating these nucleus-specific ictal network features into pre-surgical evaluation could improve patient selection and guide nucleus-specific targeting for thalamic RNS.