Binocular Disparity Energy (BDE) models



V1 is the first stage where neurons receive inputs from both left and right eyes. This gives rise to a novel type of response property, binocular disparity selectivity.

The classical model of binocular disparity selectivity is a spatiotemporal filter model much like the V1 ME model that you have already been introduced to. This is called the binocular disparity energy (BDE) model. This classical version of this model is available on the iModel website as BDE_Gabor. Instead of combining signals from subunits with RFs that differ in spatial RF phase, signals are combined from subunits that are in different eyes. These subunits may have a spatial phase difference, giving rise to different types of disparity selectivity.

Open the model parameter file from the BDE_Gabor model homepage linked above. There are three additional parameters used with model type binoc_filter for generating disparity selective units:

   phase_shift   0        # Spatial phase difference between input to each eye.
   phase_1       0        # Spatial phase of the cosine for first left-eye Gabor 
                          # filter
   binoc_nonlin  halfsq   # Type of output nonlinearity -- squaring or 
                          # half-squaring

The three additional parameters right_sign, simp_rect and simp_thresh are used in a modified disparity energy model proposed by Read et al. that will not be covered in this exercise.