Graph Theoretical Measures of Fast Ripples Support the Epileptic Network Hypothesis.

Abstract

The epileptic network hypothesis and epileptogenic zone (EZ) hypothesis are two theories of ictogenesis. The network hypothesis posits that coordinated activity among interconnected nodes produces seizures. The EZ hypothesis posits that distinct regions are necessary and sufficient for seizure generation. High-frequency oscillations (HFOs), and particularly fast ripples (FR), are thought to be biomarkers of the EZ. We sought to test these theories by comparing HFO rates and networks in surgical responders and non-responders, with no appreciable change in seizure frequency or severity, within a retrospective cohort of 48 patients implanted with stereo-EEG electrodes. We recorded inter-ictal activity during non-rapid eye movement sleep and semi-automatically detected and quantified HFOs. Each electrode contact was localized in normalized coordinates. We found that the accuracy of seizure-onset zone (SOZ) electrode contact classification using HFO rates (ripples 80-250 Hz, and FR 250-600 Hz) was not significantly different in surgical responders and non-responders, suggesting that in non-responders the EZ partially encompassed the SOZ(s) (p>0.05). We also found that in the responders, FR on oscillations exhibited a higher spectral content in the SOZ compared to the non-SOZ (p<1e-5). In contrast, in the non-responders the FR had a lower spectral content in the SOZ (p<1e-5). We constructed two different networks of FR with a spectral content > 350 Hz. The first was a rate-distance network that multiplied the Euclidian distance between FR generating contacts by the average rate of FR in the two contacts. The radius of the rate-distance network, which excluded SOZ nodes, discriminated non-responders, including patients not offered resection or responsive neurostimulation (RNS) due to diffuse multi-focal onsets, with an accuracy of 0.77 [95% confidence interval (CI) 0.56-0.98]. The second FR network was constructed using the mutual information (MI) between the timing of the events to measure functional connectivity. For most non-responders, this network had a longer characteristic path length, lower mean local efficiency in the non-SOZ, and a higher nodal strength among non-SOZ nodes relative to SOZ nodes. The graphical theoretical measures from the rate-distance and MI networks of 22 non-RNS treated patients was used to train a support vector machine, which when tested on 13 distinct patients classified non-responders with an accuracy of 0.92 [95% CI 0.75-1]. These results support the epileptic network hypothesis, refute the EZ hypothesis, and suggest that surgical non-responders, and patients not selected for resection or RNS, exhibit a decentralized FR network consisting of widely distributed, hyperexcitable FR generating nodes.