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. Author manuscript; available in PMC: 2015 Oct 15.
Published in final edited form as: Vision Res. 2009 Dec 23;50(22):2223–2232. doi: 10.1016/j.visres.2009.12.007

Fig 8.

Fig 8

Normalized minimum energy for curves of various lengths as a function of dimension. The reason for the normalization is that the number of “beads” used in the simulations increase with the length of the curve, so as to maintain a good spatial resolution. We thus normalized the data to the energy for a dimension of 3. The longer the curve the more we gain (in terms of reducing the relative energy) by adding extra dimensions (neurons) in the encoding. Yet, for any given curve length there is a dimension after which no further gains are attainable (shaded regions).