Before revision:  We found that models with  complex sparse code prior are significantly better than models with classical Gabor and/or Laplacian of Gaussian filter priors for modeling and predicting the activities of neurons that have been earlier identified to exhibit higher-order (HO) complex pattern selectivity but not better for modeling neurons that preferred orientation bars or grating (OT) .
After revision:  We found that models with complex sparse code prior are significantly better than models with classical Gabor and/or Laplacian of Gaussian filter priors for modeling and predicting the activities of neurons that have been found to exhibit complex pattern selectivity but not better for modeling neurons that preferred orientation bars or grating (OT) .