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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.


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  • 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 eyes fl1 and fr1 (even filters) and fl2 and fr2 (odd filters) are also inverted, and these positive and negative filter outputs are combined and half-squared. The four resulting signals are added to form bde, 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.