Abstract
The morphology of dendritic trees critically shapes how neurons integrate and compute synaptic inputs. Dendritic morphogenesis results from the growth and spatial organization of branches, driven by intrinsic genetic programs, extrinsic environmental signals, activity-dependent processes, and spatial mechanisms such as tiling, avoidance, and overlap. Given their intricate architecture, particularly when branches overlap, developing methods to analyze and automate the quantification of this complexity is essential. Two-dimensional (2D) neuronal cultures provide a simplified framework for studying dendritic growth patterns but remain challenging to analyze due to network complexity, overlapping branches, and imaging limitations. Existing analysis tools often require substantial manual input or computational resources, limiting accessibility. We focused on measuring parallel growth between neighboring branches, a behavior frequently observed both in vivo and in culture. To address this challenge, we developed SOA.2.0, a streamlined software platform for automated segmentation and orientation analysis of dendritic branches in 2D fluorescence images. SOA.2.0 improves the precision of morphological measurements, particularly branch parallelism, while remaining adaptable across diverse cellular and network models. Using SOA.2.0, we quantified the extent of parallel growth among dendritic branches in cultured hippocampal neurons and compared these measurements with simulated random branch distributions. Our analysis revealed that parallel growth is a prevalent and non-random phenomenon, occurring among both sister and primarily non-sister branches of all generations, with frequencies significantly exceeding those observed in simulated random distributions. This behavior was frequently observed in relatively large groups of branches, sometimes up to eight, that extended for dozens of microns. Notably, this pattern was not detected in astrocytic processes within the culture. These results indicate that parallel branch growth is a prominent feature of dendritic architecture and may contribute to shaping the structural organization of neuronal networks, offering new insights into the mechanisms underlying their development and function.