Brain simulation
Various simulations from around the world have been fully or partially released as open source software, such as C. elegans,[4] and the Blue Brain Project Showcase.
[8] Highly detailed simulations may precisely model the electrophysiology of each individual neuron, potentially even their metabolome and proteome, and the state of their protein complexes.
The connectivity of the neural circuit for touch sensitivity of the simple C. elegans nematode (roundworm) was mapped in 1985[10] and partly simulated in 1993.
[12][4] However, there is still a lack of understanding of how the neurons and the connections between them generate the surprisingly complex range of behaviors that are observed in the relatively simple organism.
[13][14] This contrast between the apparent simplicity of how the mapped neurons interact with their neighbours, and exceeding complexity of the overall brain function, is an example of an emergent property.
[15] This kind of emergent property is paralleled within artificial neural networks, the neurons of which are exceedingly simple compared to their often complex, abstract outputs.
[17] In 2006, the Blue Brain Project, led by Henry Markram, made its first model of a neocortical column with simplified neurons.
However, the simulation lacked the structures seen in real mice brains, and they intend to improve the accuracy of the neuron and synapse models.
[23] By 2009, the researchers were able to ramp up the numbers to 1.6 billion neurons and 9 trillion synapses, saturating entire 144 TB of supercomputer RAM.
He also mentioned that the model had become too heavy on the supercomputers they were using at the time, and that they were consequently exploring methods in which every neuron could be represented as a neural network (see citation for details).
The project seeks to eventually reveal insights into human cognition and various psychiatric disorders caused by malfunctioning neurons, such as autism, and to understand how pharmacological agents affect network behavior.
