iModel
Related models

DoG


Variations

DoG.0
DoG.0.a
DoG.0.b
DoG.1
DoG.2

DoG
Difference of Gaussians, Integrate-and-Fire
Summary

This difference of Gaussian (DoG) model consists of a linear filter followed by a conductance-driven integrate-and-fire unit. The surround Gaussian is delayed relative to the center, and each Gaussian has a separable temporal filter.


Results

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References
  • Rodieck RW, Stone J (1965) Analysis of receptive fields of cat retinal ganglion cells. J Neurophysiol 28:833--849.

  • Enroth-Cugell C, Robson JG, Schweitzer-Tong DE, Watson AB (1983) Spatio-temporal interactions in cat retinal ganglion cells showing linear spatial summation. J Physiol 341:279--307.

  • Derrington AM, Lennie P (1984) Spatial and temporal contrast sensitivities of neurones in lateral geniculate nucleus of macaque. J Physiol 357:219--240.

  • Levitt JB, Schumer RA, Sherman SM, Spear PD, Movshon JA (2001) Visual response properties of neurons in the LGN of normally-reared and visually-deprived macaque monkeys. J Neurophysiol 85:2111--2129.
DoG.0

The visual stimulus is convolved with a 3D spatiotemporal linear filter that is constructed from the components shown above. The filter is the difference between a narrow center filter and a wider surround filter. The center and surround filters are each the product of a 2D Gaussian and a biphasic temporal function.

The output of the linear filter is scaled and offset and taken as the excitatory conductance input to a leaky integrate and fire spiking model. Gaussian filtered Gaussian white noise is added to this conductance.