Brain simulation

There is ongoing work in the field of brain simulation, that is, creation of computer-run model of bran neuron connections, including partial and whole simulations of some animals. For example, the brains of the roundworm C. elegans, fruit fly drosophila melanogaster, mouse and rat have all been simulated to various degrees.

The connectivity of the neural circuit for touch sensitivity of the simple C. elegans nematode (roundworm) was mapped in 1985, and partly simulated in 1993. Several software simulation models of the complete neural and muscular system, and to some extent the worm's physical environment, have been presented since 2004, and are in some cases available for downloading. However, we still lack understanding of how the neurons and the connections between them generate the surprisingly complex range of behaviors that are observed in this relatively simple organism.

The brain belonging to the fruit fly Drosophila is also thoroughly studied, and a simplified model simulated.

Between 1995 and 2005, Henry Markram mapped the types of neurons and their connections in such a column.

The Blue Brain project, completed in December 2006, aimed at the simulation of a rat neocortical column, which can be considered the smallest functional unit of the neocortex (the part of the brain thought to be responsible for higher functions such as conscious thought), containing 10,000 neurons (and 10⁸synapses). In November 2007, the project reported the end of the first phase, delivering a data-driven process for creating, validating, and researching the neocortical column.

An artificial neural network described as being "as big and as complex as half of a mouse brain" was run on an IBM blue gene supercomputer by a University of Nevada research team in 2007. A simulated time of one second took ten seconds of computer time. The researchers said they had seen "biologically consistent" nerve impulses flowed through the virtual cortex. However, the simulation lacked the structures seen in real mice brains, and they intend to improve the accuracy of the neuron model.

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