COMPREHENSIVE SINGLE-CELL IDENTIFICATION OF EXCITATORY AND INHIBITORY NEURONS IN CULTURED NEURAL NETWORKS USING HIGH-DENSITY MICROELECTRODE ARRAYS

Maintaining an appropriate excitation-inhibition (E/I) balance is fundamental for precise information processing in neural networks, and its disruption is a primary pathogenic factor in various neurological disorders. Despite its significance, few studies have observed the spatiotemporal interactions between excitatory and inhibitory populations within a network at single-cell resolution. In this study, we aimed to simultaneously record the activity of every individual excitatory and inhibitory neuron constituting the entire cultured network. We constructed small-scale neural networks consisting of several hundred cells on a high-density microelectrode array (HD-MEA) capable of simultaneous recording from over 200,000 electrodes, enabling high-spatial-resolution activity mapping of the entire network. By cross-referencing the estimated signal source positions with GABAergic neurons labeled via immunofluorescence staining, we assigned excitatory or inhibitory identities to individual recorded activities. Our analysis of the classified activities revealed that during network bursts, initial burst-like activity from excitatory neurons was subsequently attenuated by sustained feedback from inhibitory neurons. Furthermore, pharmacological blockade of inhibitory synapses using bicuculline, a GABA(A) receptor antagonist, disrupted this inhibitory feedback, leading to a significantly accelerated propagation of burst-like activity across the entire network. These results suggest that our approach can elucidate the mechanisms of neurological disorders arising from E/I imbalance, such as epilepsy, by linking network-level dysfunction to single-cell functional impairments. This platform provides a powerful tool for investigating the cellular basis of neural network dynamics and their pathological deviations.