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Fig. 6.4. Effect of ON/OFF channels on orientation maps. The two rows show the results for two LISSOM networks trained with the same stream of Gaussian inputs. The top network is the LISSOM OR map from Section 5.3, and the bottom network is the reduced LISSOM model of Figure 6.3. As in Figure 5.13, each row includes a sample retinal activation, the LGN response (for the ON/OFF LISSOM network), the final receptive fields of sample neurons, their inhibitory lateral connections, the orientation preference and selectivity map, and the histogram and the Fourier transform of the orientation preferences. For the ON/OFF model, the inputs consisted of photograph-like images of Gaussians such as those used in Chapters 4 and 5, shown in gray scale from black to white (low to high), with medium gray representing background activation. In contrast, the reduced LISSOM inputs were similar to the activations in the ON channel, i.e. gray scale from white to black (low to high), with white background. The reduced LISSOM RFs are shown in gray scale like ON weights from white to black (low to high), whereas the ON/OFF LISSOM RFs are combined by subtracting the OFF weights from the ON, as e.g. in Figure 4.6. The RF orientations, lateral connections, and map organization are almost identical in the two models. The RFs on the ON/OFF channels have multiple ON and OFF lobes, and become slightly more oriented. As a result, the ON/OFF map is somewhat more selective. The histogram of each orientation map is nearly flat for both networks, because the inputs were uniformly distributed. These results show that as long as the maps are trained with the same stream of Gaussian inputs, functionally similar maps develop with or without the LGN. However, Figure 6.5 will show that the ON/OFF channels of the LGN are necessary for processing natural images.