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).