I wouldn't consider myself a very visual person otherwise.
With no offence meant to your self knowledge, and with the understanding that you were probably not one of those tested and that our (meaning their, I guess) understanding of the workings of the brain is imperfect, I think that the point of brain imaging software is in large part so that we don't have to rely on "I'm pretty sure", and indeed can have confidence even in unintuitive conclusions.
Self-knowledge is not a good way to divine the functioning of the brain. However, one could say fMRI is not a good way either, at the very least studies based solely on fMRI data should be taken with a boatload of salt. See for example: http://www.pnas.org/content/113/28/7900.full
> Functional MRI (fMRI) is 25 years old, yet surprisingly its most common statistical methods have not been validated using real data. Here, we used resting-state fMRI data from 499 healthy controls to conduct 3 million task group analyses. Using this null data with different experimental designs, we estimate the incidence of significant results. In theory, we should find 5% false positives (for a significance threshold of 5%), but instead we found that the most common software packages for fMRI analysis (SPM, FSL, AFNI) can result in false-positive rates of up to 70%. These results question the validity of a number of fMRI studies and may have a large impact on the interpretation of weakly significant neuroimaging results.
I agree completely. I still remember the feeling I got when I was able to visualize differential equations in relation to "normal" calculus. It completely changed the way I thought about math.
It would follow that it is possible that they could then be rejoined as well.
I tend to agree with the premise of the article, which is brain areas can be reapportioned for different tasks.