Mapping the human brain's 86 billion neurons requires unprecedented scalability, resolution, and multimodal integration. Using CNN-optimized Flood-Filling Networks (mesoscale) and diffusion MRI (macroscale), we present a multi-scale AI framework that combines CNNs and active learning with crowdsourced synaptic disambiguation. In silico electrophysiology verifies network dynamics, and transformers align nanoscale connectomes with fMRI and PET. Our method offers a revolutionary pipeline for connecting synaptic-to-circuit mapping in neuroscience and clinical applications, exhibiting high precision, scalability, and functional correlation.

Keyword: Flood-Filling Networks, active learning, CNN, silico electrophysiology, connectomes microscopy