Artificial neural networks that have been so popular in recent years, are inspired from biological neural networks in the nature. The aim of this work is to study the properties of biological neural networks to find out what is actually happening in these networks. To do so, we study on Caenrohibditis elegans neural network, which is the simplest and the only biological neural network that is fully mapped. We implemented the sub-circuit of C.elegans neural network that is associated with the sensation of aversive stimuli which results in forward and backward locomotion, and we found out that some of its neurons are ineffective in developing considered outputs. However, removing these neurons together has considerable effect on these outputs.