A defined human-specific platform for modeling neuronal network stimulation in vitro and in silico

Area of Science:

• Neuroscience
• Stem Cell Biology
• Computational Biology

Background:

• Transcription factor-based forward programming efficiently generates forebrain excitatory and inhibitory neurons from human pluripotent stem cells (hPSCs).
• This method allows for the creation of highly defined neuronal networks in a controlled in vitro environment for studying stimulation-response patterns.

Purpose of the Study:

• To generate defined ratios of excitatory and inhibitory neurons using forward programming of genome-edited hPSCs.
• To analyze population responses to distinct spatial and temporal stimulation patterns on multi-electrode arrays (MEAs).
• To develop in silico network models to explore mechanisms underlying experimental observations.

Main Methods:

• Genome-edited hPSCs were forward programmed using inducible transcription factors (NGN2 for excitatory, ASCL1/DLX2 for inhibitory neurons).
• Generated neuronal populations were cultured on MEAs for electrophysiological recordings.
• In silico network models were developed using parameters from in vitro cultures.

Main Results:

• Neuronal cultures exhibited synchronized network bursts (NBs) responsive to synaptic modulators.
• Low-frequency (≤0.2 Hz) local electrical stimulation reliably elicited NBs, while high-frequency (≥1 Hz) stimulation resulted in sporadic NBs.
• Multi-site stimulation at high frequencies robustly elicited NBs, suggesting functional paralysis with local high-frequency stimulation.

Conclusions:

• Forward-programmed neurons enable the creation of highly customizable neuronal networks compared to small molecule-derived neurons.
• In silico simulations can validate mechanistic hypotheses for observed network dynamics.
• iPSC technology combined with in silico modeling offers a platform for personalized in vitro studies of human neuronal networks and their responses to electrical stimuli.