This paper presents a comprehensive and self-consistent wiring diagram of the neuronal network in *Caenorhabditis elegans*, a nematode model organism. The authors use original data from previous studies and new electron micrographs to assemble gap junction and chemical synapse networks, which are then analyzed statistically and topologically. They propose a method to visualize the wiring diagram that reflects signal flow through the network. The network's statistical and topological properties, such as degree distributions, synaptic multiplicities, and small-world characteristics, are calculated to understand signal propagation. The study identifies key neurons and network motifs that may play central roles in information processing. Using linear systems theory, they explore how neuronal activity propagates in response to sensory or artificial stimulation, identifying several activity patterns that could underlie known behaviors. The interaction between gap junctions and chemical synapses is also analyzed, revealing that some statistical properties of the *C. elegans* network are similar to those found in mammalian neocortex, suggesting general principles of neuronal networks. The wiring diagram can help predict the effects of genetic perturbations, ablations, or stimulation on neuronal activity, advancing our understanding of the mechanistic basis of behavior.This paper presents a comprehensive and self-consistent wiring diagram of the neuronal network in *Caenorhabditis elegans*, a nematode model organism. The authors use original data from previous studies and new electron micrographs to assemble gap junction and chemical synapse networks, which are then analyzed statistically and topologically. They propose a method to visualize the wiring diagram that reflects signal flow through the network. The network's statistical and topological properties, such as degree distributions, synaptic multiplicities, and small-world characteristics, are calculated to understand signal propagation. The study identifies key neurons and network motifs that may play central roles in information processing. Using linear systems theory, they explore how neuronal activity propagates in response to sensory or artificial stimulation, identifying several activity patterns that could underlie known behaviors. The interaction between gap junctions and chemical synapses is also analyzed, revealing that some statistical properties of the *C. elegans* network are similar to those found in mammalian neocortex, suggesting general principles of neuronal networks. The wiring diagram can help predict the effects of genetic perturbations, ablations, or stimulation on neuronal activity, advancing our understanding of the mechanistic basis of behavior.