How to explain degenerate mechanisms

Degeneracy, the ability of structurally different elements to perform the same function and give rise to the same phenomenon, is believed to be ubiquitous at all levels of mechanisms in neurobiology. Given its biological salience, degeneracy has become an emerging topic in recent scientific literature. In this paper, I will present a new strategy for researchers to offer mechanistic explanations for degenerate mechanisms in the nervous system as complementary to the received new mechanist account. Specifically, I argue that, due to degeneracy, exemplar mechanistic models built using averaging techniques are sometimes beset by the ‘failure of averaging’ problem. To avoid this problem, many researchers opt for an alternative strategy – which is to offer what I call the population-based mechanistic explanations. According to this strategy, a large population of models instead of single exemplar models are generated to capture the real-life variability of biological mechanisms. By examining an example from cellular neuroscience, I offer an account of population-based mechanistic explanations and show that they differ from the ‘ordinary,’ exemplar-based mechanistic explanations by providing different explanatory information. Finally, I argue that the use of population-based mechanistic explanations has implications for the new mechanist philosophy. Specifically, I suggest that the notion ‘how-actually mechanistic models’ needs to be reassessed when degeneracy is taken into account.