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The nervous system of the nematode soil worm Caenorhabditis elegans exhibitsremarkable complexity despite the worm's small size. A general challenge is tobetter understand the relationship between neural organization and neuralactivity at the system level, including the functional roles of inhibitoryconnections. Here we implemented an abstract simulation model of the C. elegansconnectome that approximates the neurotransmitter identity of each neuron, andwe explored the functional role of these physiological differences for neuralactivity. In particular, we created a Hopfield neural network in which all ofthe worm's neurons characterized by inhibitory neurotransmitters are assignedinhibitory outgoing connections. Then, we created a control condition in whichthe same number of inhibitory connections are arbitrarily distributed acrossthe network. A comparison of these two conditions revealed that the biologicaldistribution of inhibitory connections facilitates the self-optimization ofcoordinated neural activity compared with an arbitrary distribution ofinhibitory connections.

The distribution of inhibitory neurons in the C. elegans connectome facilitates self-optimization of coordinated neural activity