How are you evaluating results? It makes sense that a combined model does better because HTM does find the correlations as you said.
Without topology, it means the SP is going to give every minicolumn a chance to connect anywhere in the global input space. In this case it is going to be impossible to decode from the SP. From this point on, the semantics are internal to the system. They mean something to the HTM system itself, but not to us. (For some philosophy on this, read Agency, Identity and Knowledge Transfer).
As Mark just mentioned in HTM and Reversibility, if you have topology enabled, then the SP breaks up minicolumn RFs into local chunks. In this case, if you have separated your input features to match the SP topology, you might be able to do some decoding. But AFAIK we have not tested this.