Electrical stimulation of stem cell-derived human neural networks for evaluating anti-seizure medications.

Objective: Current preclinical epilepsy drug screening relies on animal models that poorly reflect human neurophysiology, leading to high failure rates in clinical translation. We aimed to establish a human in vitro model using human-induced pluripotent stem cell (hiPSC)-derived cortical neurons cultured on multielectrode arrays (MEAs), capable of generating precisely controlled after-discharges (ADs) through electrical stimulation. We optimized stimulation parameters to evoke epileptiform-like hypersynchronous events and validated the model using six approved antiseizure medications (ASMs).

Methods: hiPSCs were rapidly differentiated into NGN2 cortical neurons and co-cultured with astrocytes on a 12-electrode, 24-well MEA. Network activity was tracked weekly. Upon maturation, biphasic voltage stimuli (400-2000 mV, 10 pulses at 100 Hz, 100 μs phase width) were applied in 100 ms trains to induce ADs. Stimulation intensity was increased until a maximum spike count per burst was reached. The timing of the stimulating inter-burst interval (IBI) was shortened from 10 to 1 s. We tested six ASMs with distinct mechanisms of action for their ability to attenuate induced ADs, as measured by the area under the curve (AUC) of spikes within bursts.

Results: A ±1000 mV stimulus was sufficient to evoke robust ADs; higher voltages caused network instability without enhancing response strength. The maximum hypersynchronous bursting rate was observed with 2 s IBIs, whereas attempts to induce more frequent events using 1 s IBIs led to desynchronization and a reduction in burst frequency below baseline. Phenytoin, perampanel, clonazepam, and lamotrigine significantly reduced AUC within 5 min in a concentration-dependent manner. Vigabatrin and levetiracetam required longer pre-incubations: AUC was reduced after 6 h for levetiracetam and at 24 h for vigabatrin.

Significance: We present a novel hiPSC-derived, electrically induced in vitro model for screening ASM candidates. This approach captures human-relevant epileptiform dynamics, allows fine control over stimulation parameters, and enables testing of diverse drug mechanisms. Its compatibility with high-throughput platforms makes it a promising tool for ASM discovery and personalized treatment strategies.