I have read other similar questions on here, but I am still unsure how SOM deals with the positions/locations of the neurons.
Say that the input space is N-dimensional. I initalise some weights, and then in the competition step, I find the closest neuron to the current input point using for example Euclidean distance. But I don't understand how I update the position of neurons next -- did I initialise random positions for each neuron at the beginning? In what direction do I move the neuron? I know that the position of the neuron will eventually be the 2-D space that I embed the N-dimensional data in, but I can't figure out how it works during training.