The synaptic organization in the Caenorhabditis elegansneural network suggests significant local compartmentalized computations br

Neurons are characterized by elaborate tree-like dendritic structures that support local computations by integrating multiple inputs from upstream presynaptic neurons. It is less clear whether simple neurons, consisting of a few or even a single neurite, may per-form local computations as well. To address this question, we focused on the compact neural network of Caenorhabditis elegansanimals for which the full wiring diagram is available, including the coordinates of individual synapses. We find that the positions of the chemical synapses along the neurites are not randomly distributed nor can they be explained by anatomical constraints. Instead, synapses tend to form clusters, an organ-ization that supports local compartmentalized computations. In mutually synapsing neurons, connections of opposite polarity cluster separately, suggesting that positive and negative feedback dynamics may be implemented in discrete compartmentalized regions along neurites. In triple-neuron circuits, the nonrandom synaptic organization may facilitate local functional roles, such as signal integration and coordinated activa-tion of functionally related downstream neurons. These clustered synaptic topologies emerge as a guiding principle in the network, presumably to facilitate distinct parallel functions along a single neurite, which effectively increase the computational capacity of the neural network

Automated summary

This study investigates whether simple neurons can perform local computations. By studying the neural network of Caenorhabditis elegans, it is found that chemical synapses are not randomly distributed, but form clusters that support local compartmentalized computations. In mutually synapsing neurons, connections of opposite polarity cluster separately, potentially implementing discrete compartmentalized feedback dynamics. In triple-neuron circuits, the nonrandom synaptic organization may facilitate local functional roles. These clustered synaptic topologies emerge as a guiding principle in the network, effectively increasing the computational capacity.