I once took an economics class where the professor, a theorist, spent most of time harping on whether a given theory had “empirical content.” That is, he wanted to know whether a theory was falsifiable. After all, if we want to say something is scientific then it must be falsifiable.
Let’s remember, too, that this isn’t purely something that theorists should be concerned about. Any time that an experimentalist suggests a working model for how something works, they are proposing a theory, whether that theory contains moving mathematical parts or not.
This came up when we were discussing a theory paper last night. This paper suggested that populations of neurons can use excitatory feedback to reduce noise without worrying about runaway excitation. Interesting, but when I asked how we would falsify these people were a bit stumped. The lack of clarity on what are the exact assumptions and when it breaks down are common in theoretical papers in neuroscience. Does adding in an additional (biologically-plausible) set of recurrent connections break the model? Does this require a gaussian distribution of connections? And in many models: does this come from a specific set of parameters and is there anything the model could not fit?
The problem with theories lacking empirical content is that they cannot be tested. And if they cannot be tested, why listen to them?
As part of a great series of posts, Dynamic Ecology tries to answer whether ecological theory is useful for solving practical problems and whether the ecological literature is ‘idea free’ (ie, whether experiments are driven by a desire to test theoretical predictions.) If neuroscience had to face that test, I think it would do decently on the first question but horrifically on the second. How often do you read papers that are directly responding to theoretical predictions?
Of course a theory doesn’t have to be correct to be useful. It could carry its utility by propagating interesting ideas and concepts that are later included in other theories. But a lot of theory in neuroscience seems to be in the vein of ‘this is possible’. How do we convert that into a community that says, ‘this is probable?’