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Fig. 9.6. Effect of prenatal and postnatal training on orientation maps. The different rows illustrate how the prenatal training phase affects the final selforganized maps. The state of each network at iteration 1000 is shown on the left half, and the final state at iteration 10,000 on the right half. In the "ND+Nature" simulation (the same as in Figures 9.1 and 9.3), postnatal training makes more neurons sensitive to horizontal and vertical contours and more selective in general. However, the overall map shape remains similar, as found experimentally in animals (Chapman et al. 1996; compare individual orientation patches between pairs of maps on the top row). However, even without any prenatal training (bottom row), or when the network is trained with natural images also prenatally (third row), HLISSOM develops a qualitatively similar final map. In these cases, its organization depends only on the properties of the natural images, not on the internally generated patterns under genetic control. Conversely, even when natural images are replaced by internally generated ones in postnatal training (second row), orientation maps still develop. However, they are not a good match to the visual environment: For example, the orientation histogram is essentially flat. These results suggests that prenatal training is useful mostly because it allows animals to have a functional visual system already at birth, forming a robust starting point for further development. Postnatal training, on the other hand, allows the animal to adapt to the actual visual environment.