Disclaimer: I'm looking for a bit of help as I'm only a simple neuroscientist and even working out what to google in this area is a tricky prospect. Here goes:
I have a set of data (3d positions in the brain). This can be allocated to known brain areas. What I want to know is - do these positions cluster nicely in to previously described brain regions, or not?
As an analogy: Imagine you have the longitude and latitude of every home in Europe. You want to understand where people live. You can simply look up the country or state/county/district within a country in which any given home is located.
If you run a cluster analysis, you'll find clusters like London that correspond entirely to one country - UK - but to multiple counties within the country - Essex, Hertfordshire etc. The city of Basel is nominally a Swiss city, but with suburbs in France and Germany. So in these cases, the cluster (the city) won't correspond well to a single classification (the country). In contrast, a city such as Bath is located in the UK, and also entirely within one subregion - Somerset
I'm looking for a way to quantify this discordance. To be clear, I don't want to train a supervised ML algorithm to recapitulate the classification, but rather to find out how an unsupervised clustering matches up.