The investigators propose to a) develop tools for electrophysiologically realistic simulations of large areas of mammalian cortex using modern computers with many thousands of (hetero- or homogeneous) processors b) use genetic programming techniques to evolve models of primary and secondary visual cortical areas to solve difficult image processing tasks, namely image segmentation, c)understand the structure of computations performed by the brain (that is, its computational primitives) and discover the level of biological detail necessary and sufficient for these computations.
A distinguishing trait of the proposed approach is that physiological realism is not the goal, and it will be attempted only to the extent that it is needed for understanding the neural computation and for solving complex information processing tasks. That is, functional performance will be the means of bridging over gaps in the existing knowledge. Thus the resulting cortical models fall between the traditional (and oversimplified) Artificial Neural Networks and biomedically-inspired cellular and molecular descriptions.
