You two have a serious misunderstanding of what a sociopath is at their core. The number of sociopaths walking around is debatable, but what is a fact is that they ARE wired differently than what most would call "normal" people. They in fact are incapable of empathy, even on a theoretical level they just don't get it. This is a mistake I see so often, and it is quite frustrating because sociopaths know this is a common misconception and they utilize it to be better at being sociopaths. Depending on circumstance they may be more or less destructive to those around them, but from birth they simply learn to be proficient mimics of emotional states so as to appear normal to everyone else. Some times they are SO good at it you could be around one for years and not even know it.
This isn't something they learned, it was something they were BORN with. How do I know this? EEG and active MRI technology now enables anyone with the correct equipment and training to demonstrate which areas of the brain are active during specific activities designed to activate target brain areas while under observation. Now I don't think people should walk around suspecting everyone of being a sociopath, but it is important to note that by definition they try to blend in to their surroundings. Any psychologist will tell you a sociopaths worst fear is being exposed for what they are.
I don't know enough to argue particulars but most mri results published are much more questionable then they at first appear. Even moreso than most science, there are numerous steps in the process that allow researchers to introduce bias. Here is an abstract coming from the first page of a google search for "mri analysis":
Quote
Obtaining reliable data and drawing meaningful and robust inferences from diffusion MRI can be challenging and is subject to many pitfalls. The process of quantifying diffusion indices and eventually comparing them between groups of subjects and/or correlating them with other parameters starts at the acquisition of the raw data, followed by a long pipeline of image processing steps. Each one of these steps is susceptible to sources of bias, which may not only limit the accuracy and precision, but can lead to substantial errors. This article provides a detailed review of the steps along the analysis pipeline and their associated pitfalls. These are grouped into 1 pre-processing of data; 2 estimation of the tensor; 3 derivation of voxelwise quantitative parameters; 4 strategies for extracting quantitative parameters; and finally 5 intra-subject and inter-subject comparison, including region of interest, histogram, tract-specific and voxel-based analyses. The article covers important aspects of diffusion MRI analysis, such as motion correction, susceptibility and eddy current distortion correction, model fitting, region of interest placement, histogram and voxel-based analysis. We have assembled 25 pitfalls (several previously unreported) into a single article, which should serve as a useful reference for those embarking on new diffusion MRI-based studies, and as a check for those who may already be running studies but may have overlooked some important confounds. While some of these problems are well known to diffusion experts, they might not be to other researchers wishing to undertake a clinical study based on diffusion MRI.
https://www.ncbi.nlm.nih.gov/pubmed/20886566My point is that modern scientific culture systematically underestimates uncertainty, and thus anything that comes out of it should be questioned rather than taken as fact.
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