Self-organizing models develop realistic cortical structures when given approximations of the visual environment as in-put, and are an effective way to model the development of face recognition abilities. However, environment-driven self-organization alone cannot account for the fact that newborn human infants will preferentially attend to face-like stimuli even immediately after birth. Recently it has been proposed that internally generated input patterns, such as those found in the developing retina and in PGO waves during REM sleep, may have the same effect on self-organization as does the external environment. Internal pattern generators constitute an efficient way to specify, develop, and maintain function-ally appropriate perceptual organization. They may help exppress complex structures from minimal genetic information, and retain this genetic structure within a highly plastic sys-tem. Simulations with the CRF-LISSOM model show that such providing a computational framework for examining how genetic influences interact with experience to construct a complex system.
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