There is a clear need for novel in vitro models, especially for neuronal applications. Development of in vitro models is a multiparameter task consisting of cell‐, biomaterial‐, and environment‐related parameters. Here, three different human origin neuronal cell sources are studied and cultured in various hydrogel 3D scaffolds. For the efficient evaluation of complex results, an indexing method for data is developed and used in principal component analysis (PCA). It is found that no single hydrogel is superior to other hydrogels, and collagen I (Col1) and hyaluronan–poly(vinyl alcohol) (HA1‐PVA) gels are combined into an interpenetrating network (IPN) hydrogel. The IPN gel combines cell supportiveness of the collagen gel and stability of the HA1‐PVA gel. Moreover, cell adhesion is studied in particular and it is found that adhesion of neurons differs from that observed for fibroblasts. In conclusion, the HA1‐PVA‐col1 hydrogel is a suitable scaffold for neuronal cells and supports adhesion formation in 3D.

To obtain commensurate numerical data of neuronal network morphology in vitro, network analysis needs to follow consistent guidelines. Important factors in successful analysis are sample uniformity, suitability of the analysis method for extracting relevant data and the use of established metrics. However, for the analysis of 3D neuronal cultures, there is little coherence in the analysis methods and metrics used in different studies. Here, we present a framework for the analysis of neuronal networks in 3D. First, we selected a hydrogel that supported the growth of human pluripotent stem cell-derived cortical neurons. Second, we tested and compared two software programs for tracing multi-neuron images in three dimensions and optimized a workflow for neuronal analysis using software that was considered highly suitable for this purpose. Third, as a proof of concept, we exposed 3D neuronal networks to oxygen-glucose deprivation- and ionomycin-induced damage and showed morphological differences between the damaged networks and control samples utilizing the proposed analysis workflow. With the optimized workflow, we present a protocol for preparing, challenging, imaging and analysing 3D human neuronal cultures.