Machamer, Darden, and Craver argue (Mechanism) that causal explanations explain effects by describing the operations of the mechanisms (systems of entities engaging in productive activities) which produce them. One of the aims of this paper is to take advantage of neglected resources of Mechanism to rethink the traditional idea (Regularism) that actual or counterfactual natural regularities are essential to the distinction between causal and non-causal co-occurrences, and that generalizations describing natural regularities are essential components of causal explanations. I think that causal productivity and regularity are by no means the same thing, and that the Regularists are mistaken about the roles generalizations play in causal explanation. Humean, logical empiricist, and other Regularist accounts of causal explanation have had the unfortunate effect of distracting philosophers from important non-explanatory scientific uses of laws and lesser generalizations which purport to describe natural regularities. My second aim is to characterize some of these uses, illustrating them with examples from neuroscientific research.