Binocular Disparity Energy after
Chen, Wang and Qian
This binocular disparity energy (BDE) model has linear spatial filters that are
3-D Gabor functions (Gaussian times sinusoid) and varying temporal filter generating
a range of selectivities for both binocular disparity and motion direction.
This model was described by Chen et al (1990). There are 4 variants based on those shown in
their Figure 2: tuned excitatory (TE),
tuned inhibitory (TI), near (NE), and far (FA) models, which also vary in strength of
selectivity for motion direction.
- Chen Y, Wang Y, Qian N (2001) Modeling V1 Disparity Tuning to Time-Varying Stimuli.
J Neurophysiol 86:143-155.
- 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
(even filters) and fl2
filters) are also inverted, and these positive and negative filter outputs are
combined and half-squared. The four resulting signals are added to form
, the binocular disparity energy. Depending on the temporal filter
parameters, the resulting outputs vary in the strength of direction selectivity.
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.