Engineered three-dimensional (3D) neural constructs hold significant promise for repairing neural tissue damage and recapitulating the human brain in vitro for disease modeling and drug screening applications. However, most current 3D neural models, including freestanding organoids and dense bioprinted neural constructs, lack the architectural and functional organization required to emulate the cerebral cortex, which comprises grey matter regions rich in neuronal cell bodies and white matter tracts formed by long-range axonal projections. This architectural mismatch limits the models' ability to support functional connectivity analysis, predict in vivo behavior, and achieve effective integration with host tissue. In this study, we present an extruded droplet-on-demand (X-DoD) bioprinting technique that enables deterministic spatial patterning of droplets containing human induced pluripotent stem cells (iPSCs) encapsulated within an extracellular matrix (ECM)-based hydrogel and embedded in a permissive, low-concentration hydrogel bulk that supports diffusion. Using a 5×5 droplet array pattern, we demonstrate that after 30 days of differentiation into cortical neurons and formation of 3D neuronal networks, the micron-scale, cell-body-dense droplets (microtissues) remain localized at their initial droplet sites and are interconnected by millimeter-scale neurite projections. This defined grey-white matter-like organization enables functional analysis via calcium imaging and seamless integration with custom electronic devices for advanced neurophysiological interrogation. Calcium imaging and electrical recordings revealed temporally preserved, propagating network activity, with network excitability dynamically modulated by treatment with GABA antagonist bicuculline. Altogether, the X-DoD bioprinting platform offers a powerful and adaptable approach for engineering spatially organized 3D neural networks with tunable connectivity, providing a robust tool for studying brain function, disease modeling, and future therapeutic applications.
Riska et al. (2026) studied this question.