Our current projects involve designing artificial evolutionary systems inspired by biological genetic and neural networks. We have previously used these systems to obtain, using artificial evolution, genetic networks that control the development of artificial embryos robust to the removal of cells and noisy gene expression. We are now working on evolving small artificial spiking neural networks for temporal pattern recognition, robotic control, and other simple cognitive tasks. We are also starting a new project that will involve using modeling approaches to optimize cryopreservation of neural tissue.
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