Abstracts

This is a Late Breaking abstract

Rationale: Thalamic neuromodulation has been shown to be effective in reducing seizure frequency by more than 50% in some patients with epilepsy. However, the efficacy of neurostimulation is highly variable across patients and it is essential to understand the dynamics of thalamic activity and possible biomarkers for appropriate use of thalamic neuromodulation in patients. Here, we sought to better understand thalamic involvement in seizures with an eye toward developing patient-specific biomarkers for thalamic neuromodulation success.

Methods: Seizures (n=66) recorded from eight patients who received thalamic implants as part of their presurgical evaluation were analyzed. For each seizure, the seizure onset times/zones were visually identified and the time at which the first rhythmic electrographic changes were visible in the thalamus was marked. Betweenness centrality (BC) for each thalamic electrode was calculated to evaluate the influence thalamus has over other regions. In addition, the coherence between seizure onset zones and the ipsilateral thalamic nuclei (SOZ-IT), as well as that between the left and right thalamus (LT-RT), was measured for different frequency bands (delta, theta, alpha, beta, gamma). The coherence for each frequency band then was averaged over seizures for each patient/seizure onset.

Results: To evaluate whether the appearance of the first electrographic changes in the thalamic activity is indicative of thalamic influence within the epileptic network, we compared the time of the initial changes to the time of the first increase in BC of the thalamic electrodes. We found that the first thalamic changes across all seizures were visually identified at 10.35±1.83 s after the seizure onset (within 10% of the seizure duration) whereas the network analysis revealed that the first increase in BC for thalamic contacts occurred within 30% of the seizure duration. The measures of functional connectivity thus suggest a later timing for thalamic involvement compared to the time of the rhythmic activity visible on the signal recorded from the thalamus. Additionally, for each seizure, the SOZ-IT coherence was compared to that of the rest of the contacts for each frequency band. We found that alpha coherence is most correlated with seizure onset, always increasing at seizure onset between SOZ-IT in all focal seizures. Surprisingly, in seizures with more widespread onset, the increased coherence was prominent in the alpha band, but it was highest between LT-RT at seizure onset rather than between the cortex and thalamus.

Conclusions: These findings suggest that while thalamic involvement can be determined in different ways, the thalamus appears to mediate seizure propagation rather than onset. More importantly, the degree of thalamic involvement differs for seizures with particular dynamical signatures, with highly focal seizures showing early interactions of cortical and thalamic regions while seizures with a more generalized signature involve intra-thalamic interactions. These results suggest that specific signatures of thalamic activity may differentiate seizure types and, therefore, responses to neuromodulatory therapies.

Funding: NIH/NINDS R01-2NS062092, DoD CDMRP W81XWH-22-1-0315