SDRs have useful mathematical properties. I find them a very simple and interesting (even though not new at all) data structure (from a CS perspective).
An encoder produces an SDR (from some raw input), where each bit represents a feature of the encoded input. On the other hand, the spatial pooling algorithm produces an SDR whose bits represent (mini?)columns. However, in the BAMI book (p. 12), it’s stated
The bits in an SDR correspond to the neurons in the neocortex
SDRs should, AFAIK, represent the activity of the brain. In particular, they should represent the sparse number of neuron spikes at any point in time. In this regard, saying that the bits of an SDR correspond to neurons in the neocortex, intuitively, makes sense.
What do the bits of an SDR currently represent in the context of the HTM theory?
Of course, the bits can actually represent whatever we like, but, in the HTM theory, they, apparently, represent different things depending on the context, and, in the current HTM theory, they do not seem to represent neurons at all in any algorithm (but I’m also not an expert yet).