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. Author manuscript; available in PMC: 2014 Jul 1.
Published in final edited form as: Neural Comput. 2013 Apr 22;25(7):1870–1890. doi: 10.1162/NECO_a_00465

Figure 2.

Figure 2

Translationally invariant model cell. The computation performed by the model is a logical OR operation on a center-surround feature, shifted to the four corners of the receptive field (A). The STC basis (B) and the maximum likelihood OR functional basis (C) both span the same space, but are much different in their appearance and interpretation. A maximum likelihood AND fit (D) finds four identical features, which does not match any of the model features. (E) Comparing the model spike probabilities generated from repeated presentations of a stimulus sequence to the predicted spike probabilities shows the logical OR fit outperforms the logical AND fit significantly, with correlation coefficients of r = 0.97 and r = 0.77 respectively. (F) The average log likelihood per time bin for logical AND and OR models with different number of functional basis vectors. (G) The transformation matrix from the STC to the functional bases (here, each vector was normalized to length one for presentation purposes).