ABSTRACT
In computational neuroscience the term ‘model’ is often used to capture simulations as well, but simulations have distinct features, and distinct epistemic uses. Models are static representations of a system, while simulations are dynamic: I follow Parker’s (2009) definition of a simulation as “a time-ordered sequence of states that serves as a representation of some other time-ordered sequence of states [e.g. of the target system]” (p. 486). Simulations can be used to track the state of a system over time, where from a starting state at t 0 , a program calculates the state of the system at t 1 , and given these values, the program can calculate the next state of the system at t 2 , and so on.
