Genuine curiosity here. What's wrong with making an experiment, and when the results clearly contradict your initial assumptions (so much that the opposite is confirmed) then publishing the found results?
The opposite hypothesis is the null hypothesis which is "gene X is NOT important in disease Y" or "priming DOESN'T affect outcome Z".
Since we assume that most interventions will not affect most outcomes, these are much less surprising and interesting results. They are seen as "water is wet" type of findings and are thus hard to publish because no one is interested.
Now if your hypothesis is something like "X will cause Y to go up" and you actually find it causes Y to go down, that IS publishable. It is only when X has no effect on Y that you will have problems.
This is assuming predeclaring ever becomes the norm.