BDE_RPC
Binocular Disparity Energy after
Read, Parker and Cumming
Summary
This binocular disparity energy (BDE) model has linear spatial filters as in the
BDE_Gabor model, but with the modification that the
monocular outputs of each initial stage filter are rectified before being binocularly
combined as described by Read et al (2002). There are 4 variants based on those some of
thise shown in their Figure 8: tuned excitatory (TE),
tuned inhibitory (TI), near (NE), and far (FA) models.
Results
Data Browser
References
- Read JCA, Parker AJ, Cumming BG (2002) A simple model accounts for the
response of disparity-tuned V1 neurons to anticorrelated images. Vis Neurosci 19:735-753.
- Ohzawa I, DeAngelis GA, Freeman RD (1990) Stereoscopic Depth Discrimination
in the Visual Cortex: Neurons Ideally Suited as Disparity Detectors. Science 239:1047-1051.
The visual stimulus is processed (convolved) by four linear Gabor
filters. The icons on the top row show x-t slices of the 3D filters, while the
bottom row shows x-y slices for each subunit. The signals from the left and right
eyes
fl1 and
fr1 (even filters) and
fl2 and
fr2 (odd
filters) are also inverted, and these positive and negative filter outputs are
then half-wave rectified before being combined via addition or subtraction, and
half-squared. The four resulting signals are then added to generate
bde, the binocular disparity energy.
The raw signal (bde) is then offset, scaled and half-wave rectified
(although the signal is typically already non-zero unless the scaling
or offset has introduced negative values), and it is used to drive a
Poisson spiking mechanism. The spikes are time shifted to simulate a
neurobiological latency. See the model (.moo) files for the
parameters that govern these computations.