ABSTRACT. In this work, a type of developmental brain-inspired computational network is presented and evaluated. It is based on the idea of evolving programs that build a computational neural structure. This thesis describes an artificial model of the brain based on evolutionary computation and neurodevelopmental techniques. This model is more biologically plausible than earlier techniques and demonstrates that adding more biological plausibility can enhance the computational power of the neural systems. The thesis demonstrates the capabilities of this brain inspired system on two different learning problems.