  Experimental results in recent years have shown that adult neurogenesis is a
significant phenomenon in the mammalian brain. Little is known, however, about
the functional role played by the generation and destruction of neurons in the
context of and adult brain. Here we propose two models where new projection
neurons are incorporated. We show that in both models, using incorporation and
removal of neurons as a computational tool, it is possible to achieve a higher
computational efficiency that in purely static, synapse-learning driven
networks. We also discuss the implication for understanding the role of adult
neurogenesis in specific brain areas.
