THE NETWORK CONNECTIVITY ANALYSIS AS AN EVALUATION OF THE DEVELOPMENTAL PROCESS OF NEURAL CIRCUITS ON-A-CHIP GENERATED FROM HUMAN IPS CELL-DERIVED NEURAL PROGENITOR CELLS​

The advent of human iPS cells (hiPSCs) has enabled the technologies applying these neurons are now being actively developed. It has been reported that in vitro hiPSC-derived neurons (hiPSC-neurons) forming neural circuits on-a-chip (NC-on-a-chip) can learn and exhibit sentience when embodied in a simulated game world (Kagan et al., 2022), suggesting the potential for realizing bio-intelligence using hiPSC-neurons. However, our understanding of the developmental processes of hiPSC-neurons and their network connectivity when forming NC-on-a-chip remains limited.
To address this issue, we constructed NC-on-a-chip using hiPSC-neurons and evaluated the development of their neural network activity. We generated NC-on-a-chip by differentiating hiPSC-derived neural progenitor cells under co-culture conditions with human derived primary astrocyte like cells on a high density multielectrode array (MaxOne, MaxWell), and recorded neural activities on days 56 and 60. The spike sorting algorithm (Kilosort, Pachitariu et al., 2024) was applied to the recorded data to extract spiking activities of multiple neurons. Based on the spiking activities, whether the detected neurons are excitatory or inhibitory was inferred with the widths of action potential shapes. Then synaptic connections are inferred by GLMCC (Kobayashi et al., 2019) that arrows to evaluate synaptic connections between a pair of neurons based on the pair of spike sequences.
In the NC-on-a-chip in which inhibitory neurons were the majority of neurons, fewer network bursts were observed, and the functional connectivity network derived by GLMCC remained sparse. These results suggest that controlling the proportion of inhibitory neurons is essential for maturation of synaptic connectivity and network activity.