Neural network model to generate head swing in locomotion of Caenorhabditis elegans.

Abstract

Computer simulation of the neural network composed of the head neurons of Caenorhabditis elegans was performed to reconstruct the realistic changes in the membrane potential of motoneurons in swinging the head for coordinated forward locomotion. The model neuron had ion channels for calcium and potassium, whose parameters were obtained by fitting the experimental data. Transmission properties of the chemical synapses were set as graded. The neural network involved in forward movement was extracted by tracing the neuronal activity flow upstream from the motoneurons connected to the head muscles. Simulations were performed with datasets, which included all combinations of the excitatory and inhibitory properties of the neurons. In this model, a pulse input entered only from motoneuron VB1, and activation of the stretch receptors on SAA neurons was necessary for the periodic bending. The synaptic output property of each neuron was estimated for the alternate contraction of the dorsal and ventral muscles. The AIB neuron was excitatory, RIV and SMD neurons seemed to be excitatory and RMD and SAA neurons seemed to be inhibitory. With datasets violating Dale's principle for the SMB neuron, AIB neuron was excitatory and RMD neuron was inhibitory. RIA, RIV and SMD neurons seemed to be excitatory.