INTRODUCTION:Despite surgical resection of a defined epileptogenic focus (EF), about 50% of patients go on to have refractory seizures. Recently, focal epilepsy is being redefined as a network disorder and studies have demonstrated that resection of nodes outside the EF may contribute to better surgical outcomes. Additionally, our group has shown higher interictal connectivity between nodes involved in seizure onset in a cohort of epilepsy patients, further suggesting the presence of an underlying distributed epileptogenic network in focal epilepsy.METHODS:Primary mixed cultures of cortical neurons from P1 rat pups were cultured on 96-well multi-electrode array (MEA) plates with eight active electrodes per well for stimulation and recording. We developed an in vitro stimulation model of cortical epilepsy to study epilepsy network formation using a biphasic tetanic stimulation at 50 or 100 Hz, 500 μV, 250 μA applied for one hour daily for ten days.RESULTS:Four-days of daily in vitro stimulation demonstrated significant increases in neuronal baseline bursting, modeling kindled seizures. Tetanic stimulation with 50 Hz had the highest elevation in neuronal busting. In order to compare distributed network connectivity, we calculated and ranked coherences (13-32 Hz) across all electrode pairs (n = 24) and identified the top 15% for comparison to control. The average coherence across the top connected pairs was significantly higher in stimulated wells compared to controls (0.27 vs. 0.17, p = 0.0002). Furthermore, coherence across the highest-ranking electrode pair was strengthened with daily stimulation. This was not seen in control wells.CONCLUSION:Similar to human data, this in vitro model suggests an elevated interictal coherence among electrode pairs involved in seizure formation. Next, we aim to characterize the structure of this network quantifying axonal boutons and dendritic spines. Ultimately, our work aims to enable a better understanding of network formation in epilepsy that will inform future epilepsy surgery decision making.

Electrocorticography (ECoG) data are commonly obtained during drug-resistant epilepsy (DRE) workup, in which subdural grids and stereotaxic depth electrodes are placed on the cortex for weeks at a time, with the goal of elucidating seizure origination. ECoG data can also be recorded from neuromodulatory devices, such as responsive neurostimulation (RNS), which involves the placement of electrodes deep in the brain. Of the neuromodulatory devices, RNS is the first to use recorded ECoG data to direct the delivery of electrical stimulation in order to control seizures. In this review, we first introduced the clinical management for epilepsy, and discussed the steps from seizure onset to surgical intervention. We then reviewed studies discussing the emergence and therapeutic mechanism behind RNS, and discussed why RNS may be underperforming despite an improved seizure detection mechanism. We discussed the potential utility of incorporating machine learning techniques to improve seizure detection in RNS, and the necessity to change RNS targets for stimulation, in order to account for the network theory of epilepsy. We concluded by commenting on the current and future status of neuromodulation in managing epilepsy, and the role of predictive algorithms to improve outcomes.

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Deep brain stimulation (DBS) is a widely used clinical therapy that modulates neuronal firing in subcortical structures, eliciting downstream network effects. Its effectiveness is determined by electrode geometry and location as well as adjustable stimulation parameters including pulse width, interstimulus interval, frequency, and amplitude. These parameters are often determined empirically during clinical or intraoperative programming and can be altered to an almost unlimited number of combinations. Conventional high-frequency stimulation uses a continuous high-frequency square-wave pulse (typically 130–160 Hz), but other stimulation patterns may prove efficacious, such as continuous or bursting theta-frequencies, variable frequencies, and coordinated reset stimulation. Here we summarize the current landscape and potential clinical applications for novel stimulation patterns.