Human brains are way too complicated with billions of neurons and hundreds and even thousands of trillion connections that are still not completely understood. Because of this, studying a smaller “brain” permits one to better understand how the brain and the neural network influences the behavior of a creature. The C. elegans’ connectome is the ideal network to research because of its simplicity (only consisting of 302 neurons and the fact that it has been completely mapped out. In this project, I strive to find the most important connections within different C. elegan sub-neural networks (chemical forward, gap junction forward, chemical backward, and gap-junction backward neural networks) using the symmetrized neural sub-networks. I randomly break the symmetry and use stochastic binary simulations to approximate its dynamics. My study focuses mainly on the locomotion neural circuits of C. elegans. These neurons are categorized as forward or backward, controlling the forward and backward motion of the C. elegans, respectively. The forward and backward neural networks are further broken down into the gap-junction and chemical circuits where the gap junction circuit connections carry information that travels to and from the neurons connected (bi-directional) while the chemical synapse connections carry information that travels only in one direction (uni-directional). The locomotion circuit consists of two main functional classes of neurons called command interneurons and motor neurons. Command interneurons function as information processors as they receive input from sensory neurons (not studied) and pass on information and decisions to motor neurons or other interneurons.

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• Biology
• Mathematics