In reading von Uexkull's piece on umwelten, it got me thinking about the ramifications of a popular strategy in brain simulation: simulate simpler animals' brains first, then we can move up to humans. Here is a small list of some popular (if not successful) attempts at brain simulation.
The Blue Brain Project has focused on simulating a neocortical column of a rat. Bi-products of the project, however, include a simulation framework and a number of noteworthy genetic algorithms for large-scale simulation. A number of popular articles have been written on the project.
On a smaller scale we have NEURON project from Yale, which seeks to simulate single brain neurons for use in larger network-based simulations.
On a bigger scale we have a DARPA funded group at IBM who recently claimed the "largest" cortical simulation to-date.
IBM's success on the company's Blue-architecture super-computers has spawned an even larger project: SyNAPSE. SyNAPSE is more in line with the chip manufacturer's agenda in that the goal is to instantiate brain-like redundancy and generality in a marketable hardware platform.
In reading about some of these projects and thinking of our friend von Uexkull, I'm wondering at what level of complexity umwelten may emerge from any kind of simulation. Clearly brains aren't the whole story in our engagement with the word. Might simulations of cortical tissue shed light on the organisation of our larger cognitive capacities? What really intrigues me is the idea that our more general abilities (like visual, tactile, and lingual systems) may have co-evolved with our exceptionally generalised brain. Will simulations, once computationally feasible, shed light on cognition? Or, will embodiment provide the next hurdle for technologists to jump? Might simulations replace imaging in neuroscience? And the bigger question: once we understand the brain, what's left?