Intracranial interictal functional networks predict the effect of subacute cortical stimulation in focal epilepsy

Abstract

BackgroundElectric neurostimulation is being developed as an alternative treatment for drug-resistant epilepsy patients. A major challenge is to identify, among all possible combinations of stimulation parameters, the most effective stimulation protocol to achieve seizure control for each patient.\n\nObjectiveTo estimate the value of interictal intracranial EEG recordings in identifying the most effective stimulation protocol in order to decrease number of seizures during intracranial subacute cortical stimulation (SCS).\n\nMethodsFive patients undergoing SCS were included in this retrospective study. Bivariate correlation measures were applied to baseline interictal intracranial EEG recordings to infer functional correlation networks. The node strength of these networks was calculated for each recording electrode (indicating the overall correlation between activity from one electrode with the activity from all other electrodes). The relationship between node strength and the change in seizure rate associated with SCS was studied for the electrodes used for stimulation.\n\nResultsAcross all five patients, node strength was negatively correlated with seizure rate ratio (ratio of seizure rate during SCS relative to during baseline) for all frequency bands tested (delta, theta, alpha, beta, gamma, and high gamma), and both the common reference and the common average montage.\n\nConclusionInterictal functional correlation networks contain information that correlates with the effect of SCS on the rate of epileptic seizures, suggesting that stimulation of those regions with higher node strength (derived from correlation networks) is more effective in reducing number of seizures.\n\nHIGHLIGHTSO_LIIn focal epilepsy, effective brain stimulation targets are lacking\nC_LIO_LIWe use baseline interictal functional networks to outline stimulation targets\nC_LIO_LIStimulation of regions with higher node strength is most effective in our study\nC_LI