Hard to digest: The challenges of modeling the dynamics of the C. elegans pharynx

The last decade has brought us riches of connectomes from several species. Even though these detailed snapshots provide substantial insight into structure, composition and connectivity of neural networks, they fall short of explaining the dynamics they support. This stems from the difficulty to derive cellular model parameters, e.g., cell type and synaptic strengths, from fixed tissue. Additionally, neural systems are often governed by so-called ‘wireless’ connectivity, i.e., neuromodulation, controlling network state by way of volumetrically dispensed transmitters. What we can learn from a connectome about its computational abilities remains unsolved. Here we investigate the relationship between the connectome and the dynamics of the C. elegans pharynx, a fully described subnetwork of 20 neurons.Using connectivity data we built a model that lends itself to stability analysis and yields insight into the network dynamics the pharynx may support. We used observed chemical and electrical synaptic parameters as a starting point for tuning the connectivity matrix W. We first show that the known connectivity alone does not suffice to explain stability or functionality of the system. Next, we use stability constraints to identify network states that allow for information flow, autonomous (central) pattern generation, and amplified responses to external inputs. Using such analytical methods, we can identify the roles of individual cells and describe cell-specific targets of neuromodulation to achieve desired network dynamics, thus making experimentally testable predictions to expand our understanding of pharynx behavior in its various operational modes.