Neuroscience is currently experiencing explosive growth in detailed high-quality experimental information on neural processes underlying learning, memory and behavior. Correspondingly there has arisen a need for computational models that can manage this outpouring of information, help convert information to knowledge, and to generate novel, testable hypotheses. In this paper we describe an application of Pathway Logic, using the rewriting-logic specification system Maude, to model a neural circuit involved in feeding in a marine mollusk. This approach is intended to augment existing modeling techniques in neuroscience and has potential advantages of scalability, robustness with regard to system parameters, and easy testing of knock-outs, ‘what-if’s and other in silico experimentation. Our technique yields expressive models capable of simulating known neural circuit behaviors.
Keywords: neural circuit, executable specification, Aplysia, Maude