A recognition model which defines a measure of shape similarity on the direct output of multiscale and multiorientation Gabor filters does not manifest qualitative aspects of human object recognition of contour-deleted images in that: (a) it recognises recoverable and nonrecoverable contour-deleted images equally well, whereas humans recognise recoverable images much better; (b) it distinguishes complementary feature-deleted images whereas humans do not. Adding some of the known connectivity patterns of the primary visual cortex to the model in the form of extension fields (connections between collinear and curvilinear units) among filters (a) increased the overall recognition performance of the model, (b) boosted the recognition rate of the recoverable images far more than of the nonrecoverable ones, (c) increased the similarity of complementary feature-deleted images, but not part-deleted ones. These correspond more closely to human psychophysical results. Interestingly, performance was approximately equivalent for narrow (±15 deg) and broad (±90 deg) extension fields.