The purpose of descriptive modelling is to summarize experimental data compactly in a mathematical form. An example of such model is the Difference-of-Gaussians (DoG) model which is traditionally used for analysing data to study the spatial receptive field organization of retinal and geniculate cells. In this model the response of a cell, with its receptive field centre at \( \mathbf{r}_{c} \), is approximated by

\begin{equation} R( \mathbf{r}_{c}, t) = R_{0} +\displaystyle \int_{\tau} \iint_\mathbf{r} W ( \mathbf{r}_{c} - \mathbf{r} , \tau ) S( \mathbf{r},t- \tau ) \mathrm{d}^2 \mathbf{r} \mathrm{d}\tau, \end{equation}

where the spatial part of the impulse response function, \( W \), is described by a DoG function

\begin{equation} G(x,y) = \frac{A}{\pi a^2}e^{-(x^2+y^2)/a^2} -\frac{B}{\pi b^2}e^{-(x^2+y^2)/b^2}, \end{equation}

with its parameters being fitted with respect to experimental data. This procedure provides estimates for receptive field centre (\(A\)) and surround (\(B\)) weights as well as the corresponding width parameters (\(a\)) and (\(b\)). With this approach, however, limited insight is gained on how the geniculate circuit modifies the receptive field structure of cells in the early part of the visual system. To address this question a mechanistic model is needed.