Presynaptic mechanism of epileptiform activities in forward-programmed human excitatory neuronal networks

Epilepsy is one of the most common neurological disorders, yet the mechanisms controlling seizure termination remain poorly understood. In particular, why rhythmic spike-wave discharges decelerate before stopping is unexplained. Here, using human iPSC-derived excitatory neurons differentiated via targeted forward-programming, we report a similar deceleration phenomenon in cultured neuronal networks. These networks exhibit glutamate-dependent, epileptiform super-bursts with a slowing rhythm from [~]4 Hz to [~]2 Hz. Combining in silico simulations and in vitro experiments, we correlate this activity pattern with the hierarchical organization of presynaptic vesicle pools. Nested bursts link to the recycling pool (RP), and sub-bursts associate with the readily releasable pool (RRP). Decelerating RP-to-RRP vesicle translocation shortened the super-bursts, indicating that epileptiform dynamics depend heavily on this translocation process. These findings depict human neuronal networks derived from forward-programmed cells as a model for epileptology, revealing a presynaptic framework for rhythmic discharges in excitatory networks. HighlightsO_LIHuman iPSC-derived glutamatergic networks exhibit epileptiform super-bursts C_LIO_LISuper-burst dynamics are governed by a two-pool presynaptic vesicle hierarchy C_LIO_LICytochalasin-D disrupts RP-to-RRP translocation and attenuates super-bursts C_LIO_LIExcitatory networks show intrinsic tonic-clonic bi-stability via RRP dynamics C_LI eTOC blurbBrustle and colleagues use forward-programmed human iPSC-derived glutamatergic networks to model epileptiform activity. Combining multi-electrode array recordings with computational simulations, they demonstrate that epileptiform super-burst dynamics are governed by a hierarchical two-pool presynaptic vesicle system, and reveal an intrinsic tonic-clonic bi-stability in excitatory networks driven by RRP recovery kinetics.