Abstract: In the Hierarchical Temporal Memory (HTM) paradigm
the effect of overlap between inputs on the activation of columns in
the spatial pooler is studied. Numerical results suggest that similar
inputs are represented by similar sets of columns and dissimilar inputs
are represented by dissimilar sets of columns. It is shown that the
spatial pooler produces these results under certain conditions for
the connectivity and proximal thresholds. Following the discussion
of the initialization of parameters for the thresholds, corresponding
qualitative arguments about the learning dynamics of the spatial
pooler are discussed.