Intracranial EEG synchrony tracks antiseizure medication load in drug-resistant epilepsy

Epilepsy care is often guided by incomplete snapshots: patient-reported seizures, intermittent drug levels and medication histories that may not reflect current exposure. Between these snapshots, clinicians have little objective information about how the brain is responding to antiseizure medication. In this study, we tested whether intracranial EEG synchrony, a measure of coordinated neural activity across intracranial electrodes, tracks antiseizure medication load in patients with drug-resistant epilepsy. We retrospectively studied 80 consecutive patients with drug-resistant epilepsy who underwent presurgical intracranial EEG monitoring at the Hospital of the University of Pennsylvania. Antiseizure medication load was estimated continuously from medication administration records using a validated pharmacokinetic model. Synchrony was computed from intracranial EEG using the Kuramoto order parameter. We first compared synchrony within the same patient during high and low medication exposure. We then tested the continuous association between synchrony and medication load across the epilepsy monitoring unit admission, adjusting for time since admission, seizure timing, wakefulness, time of day and interictal spike rate. Analyses accounted for repeated measurements within patients and tested robustness to temporal structure in the recordings. We also assessed whether synchrony dynamics were preserved when fewer electrodes were sampled. Forty-five patients had sufficient high- and low-exposure data after peri-ictal exclusion. Synchrony was higher during low medication exposure in 32 of 45 patients, corresponding to a median 7.4% increase and a median paired difference of 0.0082 on the 0-1 synchrony scale (sign test P = 0.007; Wilcoxon P < 0.001). In the continuous analysis of 67 patients and 23,402 repeated 10-minute observations, higher synchrony was associated with lower medication load (β = -0.153, 95% confidence interval -0.293 to -0.012, P = 0.033); interictal spike rate was not independently associated with medication load. The inverse association remained evident in circular-shift, temporally binned and likelihood-based sensitivity analyses. Relative synchrony dynamics were preserved under electrode subsampling, with a median correlation of 0.85 with full-array synchrony at 40% sampling. These findings support synchrony as a candidate continuous physiological readout of antiseizure medication load in patients with drug-resistant epilepsy. By linking medication exposure to a measurable brain-network state, synchrony may help move epilepsy monitoring beyond seizure counting alone and toward continuous assessment of how the brain is responding to treatment.