In neuroscience some people do experiments, while others just work with the data. The former are “experimentalists,” the latter are “theorists”. What do I want to be?
My first intuition was that I wanted to avoid experiments if at all possible, because on the whole I like coding and working out the equations more than I imagine I would enjoy sitting in a room with a monkey all day trying to train and coax him to do whatever it is I want him to. But almost as soon as I reached this conclusion I started hearing from others how important it is to have experimental experience even if you eventually just want to work on theory.
A fair point, I thought. But I have done some experiments (two long-enough psychophysics experiments). How do I know when I have done “enough”?
I asked Jake, a grad student, what his take on this question was. His response was to point out an even more important dichotomy in science. Or no, not even a dichotomy, come to think of it, but just a word: story.
Story, as I am beginning to realize, is everything in science. You can crank out all the experiments you want, write all the code and calculations that you want, but in the end you have to tell a story, because no one else feels like going through all the work you did if they don’t have to.
You can plot your data. That’s a story, because choosing which axes to plot your data against is not at all an objective decision. You can model your data–also a story. You can give a talk or presentation or poster on your data. You can write a paper on your data, published or not. All of these are stories.
In the end, the only way you can communicate science is with a story. There are two complications to this: 1) Your story should be memorable, and thus, not too complicated. 2) Your story should be supported by your data at every level of investigation, despite the fact that you will have to gloss over the data’s details in order to tell a story about it.
In other words, someone should be able to hear your story, understand it, and then question your simplifications and still remain satisfied as they dig deeper.
Scientists make stories at all sorts of timescales and across all sorts of mediums. Some stories take entire careers to tell, so that, in the end, fundamental reconsiderations of certain scientific problems can threaten very long, involved stories.
Anyway, story-telling is a critical aspect of doing science. To bring this point back to the theory/experiment divide, I think that typically, at least in neuroscience, experimentalists tend to be better story tellers. You design an experiment, after all, to answer a question, and to answer that question it’s pretty standard to tell a story. Theory, on the other hand, can be misleadingly self-sufficient because the theory itself offers a story but in a mathematical language.
Jake’s point, as I took it, is that if you are focusing on theory it is important to remember that different people like different sorts of stories, and if you want to tell stories about the world you need data from experiments. And to work with the data from those experiments, you have to be able to talk with the experimentalists. And to do that you need to tell a story about your methods, about your approach, in a way that is not myopic and full of spooky-sounding jargon. Focus on story, I’m guessing, and the theory/experimental distinction won’t be nearly as critical. You can straddle both sides and tell two types of stories at once.