Why use SOM for clustering?
I disagree with the assertion that SOM are frequently used. IMHO they are difficult to use and rather obscure.

Nevertheless they have some interesting properties, although I'd rather call them a visualization than a clustering technique.

What you are ignoring is the"map" property. Neurons aren't independent but connected in a particular layout. Without this, the method is useless AFAICT. You need nodes to usually not be empty, but rather the average of many points, and thus M&lt;