Blue brain project

The basic structural unit of the human cerebral cortex is the neural column . One such column contains about 10 ³ -10 ⁴ neurons, whose dendrites pass through the entire height of the column. The new crust and each column consists of 6 layers ^[1] . The thickness of each layer is approximately equal to the thickness of the credit card .

The project uses the Blue Gene supercomputer to model speakers. At the end of 2006, we managed to model one column of a new bark of a young rat. In this case, one Blue Gene computer was used and 8192 processors were used to simulate 10,000 neurons. That is, almost one processor modeled one neuron. To connect neurons, about 3⋅10 ⁷ synapses were modeled.

Currently, the team is working on a “real-time mode,” in which 1 second of real-time brain work is modeled by processors in 1 second.

Phase I

On November 26, 2007 , the completion of Phase I of the Blue Brain project was announced. The results of this phase are:

1. A new model of the grid structure , which automatically, upon request, generates a neural network based on the biological data provided.
2. The new process of simulation and self-regulation , which automatically systematically checks and calibrates the model before each release, to more accurately match the biological nature.
3. The first model of the column of the new bark of the cellular level , based exclusively on biological data

Phase II

On October 8, 2015, in the reviewed journal Cell, an article was published in which the project team described in detail its modeling approach, described a model of several microcolumns, and made a number of predictions about the structure of the microcontour and the behavior of neurons depending on changes in input parameters. ^[2]

3D visualization

The simulation process produces a huge amount of data (hundreds of gigabytes of information per second), which are extremely hard to analyze. Therefore, in addition to parallel processing of outgoing data, a 3D column visualization interface was developed. The mesh object of the rendered column (10,000 neurons) contains about 1 billion triangles and has a volume of 100 GB. The model of the column with the display of electrical activity has a volume of about 150 GB. This interface allows you to visually analyze the information of electrical activity and identify the most interesting zones. It also allows you to compare the results obtained by modeling with experimental results, which are obtained by measuring the microelectroencephalogram of the column. Model calibration by comparison with a real biological column will be carried out in the “Phase II” of the project.

Modeling Consciousness

Researchers do not set themselves the task of modeling consciousness . ^[3]

If consciousness arises from a critical mass of interactions, then it may be possible. But we really do not understand what consciousness is , therefore it is difficult to talk about it.

Original Text (Eng.)

If it’s possible, it can be possible. It is difficult to say.

• Professor Henry Markram - project director. Director of the Center for Neuroscience & Technology.
• Dr Robert Bishop - chairman.
• Dr Ronald Cicurel - chairman.
• Dr Felix Schürmann - Project Manager. He is also engaged in research at the Brain Mind Institute (EPFL). His job is to find alternative methods of computing.
• Dr Sean Hill - Project Manager. He used to be a member of the Biometaphorical Computing Group at the IBM TJ Watson Research Center. His field of research is large-scale models of real biological activity. Investigates the plasticity of synapses, the structure of the neural network, the expansion of the model from one column to a full brain with sleep and wakefulness modes
• Dr Eric Kronstadt - IBM representative. Member of the Academy of Technology IBM. He was twice awarded by IBM for outstanding research. He has three patents in the field of microprocessor structure.

• Markram, H., 2006. The blue brain project. Nat Rev Neurosci . 7, 153-160.
• Kozloski, J. et al., Identifying, tabulating, and analyzing contacts between branded neuron morphologies, IBM Journal of Research and Development, Vol 52, Number 1/2, 2008
• Druckmann, S. et al., A Novel Multiple Objective Optimization Framework for Constraining Conductance-Based Modeling by Experimental Data, Frontiers in Neuroscience, Vol. 1, Issue 1, 2007
• Anwar, H. et al., Capturing neuron mophological diversity. In Computational modeling methods for neuroscientists. E. De Schutter (ed.), MIT Press
• Hines, M. et al., 2008. Neuron splitting in compute-bound parallel network simulations enables runtime scaling with many as many processors, J. Comput. Neurosci.
• Hines, M. et al., 2008. Fully Implicit Parallel Simulation of Single Neurons, J. Comput. Neurosci.

When will the artificial brain be created?

Blue Brain Project: Communication and Chaos

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