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This chapter considers the issue of network growth. We review a wealth of data from neuroscience providing evidence for learning-directed architectural brain changes throughout the lifespan. We also consider the computational implications of having a learning mechanism that becomes substantially more powerful as it grows. Auditory localization in the barn owl is an important example of activity-dependent network growth underlying the ability to learn. Modeling children’s cognitive development with constructive neural networks also indicates the importance of growth stimulated by pressure to learn. After drawing conclusions, we identify areas of future research and open research questions.
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