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This paper studies the inter-seizure variability in thalamic recruitment in patients with refractory epilepsy, with the primary goal of identifying specific thalamic nuclei involved in seizure propagation. The authors conducted an analysis of 717 seizures from 44 patients, focusing on the relationships between the seizure onset region, the electrographic pattern at the seizure start, and the temporal dynamics of ictal spread. The core finding is that seizures with a broad onset tend to spread quickly to the centromedian (CM) and pulvinar (PLV) nuclei, whereas mesial temporal onsets preferentially engage the anterior nucleus (ANT) early in the seizure (1-6 s window) Key research findings.

Methodologies Used

• Patient Cohort: 44 patients (21 female, mean age = 31.5 years) with medication-refractory epilepsy were included. The patient selection was based on the availability of thalamic electrode implants in specific nuclei, thereby allowing detailed spatial and temporal analysis of thalamic activity Patient selection and demographics.
• Data Acquisition: EEG data were recorded using Natus Quantum systems with high sampling rates (1024 Hz/2048 Hz) and analyzed with MATLAB and FieldTrip, enabling fine resolution of seizure dynamics EEG acquisition and processing techniques.
• Analysis: Seizures were classified based on onset patterns (e.g., hypersynchronous vs sharp onset) and analyzed through both automated and expert visual assessment methods, with classification thresholds set using standardized deviations from baseline activity Seizure classification and modeling.

Key Findings

1. Distinct Propagation Patterns: Seizures with broad onsets exhibit early involvement of CM and PLV, whereas seizures from mesial temporal origins predominantly show early spread into ANT. This differentiation is crucial for patient-tailored neuromodulation Seizure propagation patterns.
2. Predictive Value of Electrographic Features: Specific EEG patterns, such as sharp onset vs hypersynchronous activity, correlate with different thalamic spread profiles. This provides a basis for developing precision neuromodulatory therapies that target the most relevant thalamic nuclei depending on the seizure type EEG pattern analysis.
3. Implications for Neuromodulation: The study suggests that considering inter-seizure variability could refine the selection of thalamic targets for neuromodulation, potentially enhancing clinical outcomes in epilepsy treatment Clinical implications.

Limitations and Future Directions

The authors note several limitations, including the uneven number of seizures recorded per patient and potential bias in the visual classification of ictal onset patterns. Furthermore, the generalizability of these findings is limited to the selected patient population with specific thalamic electrode placements. Future studies could involve larger cohort designs and integration of advanced machine learning algorithms for real-time detection and neuromodulation optimization Study limitations and future research.

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