Connectomics utilizes advanced imaging and AI to map the intricate wiring of brains, creating detailed neural networks. A recent breakthrough is the complete map of the fruit fly brain, a crucial step for understanding brain function. However, mapping larger mammalian brains, like those of mice and humans, poses a far greater challenge. Google Research is developing new AI techniques to accelerate the identification, and visualization of neurons. They are working on mapping fragments of various animal brains, including a small section of the human brain. The advancement of "MoGen," a synthetic neural shape model, improves AI reconstruction. MoGen-enhanced models reduced reconstruction errors by 4.4%, a substantial gain. This improvement saves significant time, potentially equivalent to over 150 years of manual work for a mouse brain. The research team has developed several tools for connectomics over a decade. Neurons exhibit complex shapes, differing from typical spherical cells, crucial for their function. AI models like PATHFINDER are used to create detailed 3D neuron shapes from microscope images. Manual proofreading remains a bottleneck in the process, as human experts are needed to correct errors. MoGen generates synthetic neurons to augment training data for AI models like PATHFINDER, improving accuracy. MoGen transforms random point clouds into realistic neuronal shapes using AI, mimicking actual neuron morphology. Using MoGen decreased merge errors in neuron reconstructions. Human experts can't reliably distinguish between real and AI-generated neurite fragments, indicating the realism of the synthetic data. Integrating synthetic shapes significantly improves the performance of the AI model. The use of synthetic data with MoGen resulted in a 4.4% reduction in reconstruction errors, enhancing the efficiency of brain mapping. This improvement is a leap forward in the field of connectomics. This research opens opportunities for generating specific neuron types and creating synthetic images for earlier stages of reconstruction. The open-source release of MoGen promotes collaboration and further progress in neuroscience. This work ultimately aims to accelerate the mapping of complex brains, crucial for understanding neurological processes and diseases.