Brain simulation

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Short description: Concept of creating a functioning computer model of a brain or part of a brain

Brain simulation is the concept of creating a functioning computer model of a brain or part of a brain.[1] Brain simulation projects intend to contribute to a complete understanding of the brain, and eventually also assist the process of treating and diagnosing brain diseases.[2][3]

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.[5] In 2013 the Human Brain Project, which has utilized techniques used by the Blue Brain Project and built upon them,[6] created a Brain Simulation Platform (BSP), an internet-accessible collaborative platform designed for the simulation of brain models.

Methods

Modelling a brain (or brain subsystem) involves modelling neurons' electrical and bulk chemical properties (e.g. extracellular serotonin gradients). A model of the neural connectome of the target organism is also required. The connectome is extremely complex, and its detailed wiring is not yet understood; thus it is presently being modeled empirically in smaller mammals by projects like the Blue Brain Project.[citation needed]

The Blue Brain Project intends to create a computer simulation of a mammalian cortical column down to the molecular level.[7] By one estimate, a full reconstruction of the human connectome using the methodology of the Blue Brain Project would require a zettabyte of data storage.[citation needed]

Examples

Caenorhabditis elegans (roundworm)

Brain map of the C. elegans roundworm 302 neurons, interconnected by 5000 synapses

The connectivity of the neural circuit for touch sensitivity of the simple C. elegans nematode (roundworm) was mapped in 1985[8] and partly simulated in 1993.[9] Since 2004, many software simulations of the complete neural and muscular system have been developed, including simulation of the worm's physical environment. Some of these models including source code have been made available for download.[10][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.[11][12] 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. [13] 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.

Drosophila neural system

Further information: Insect brain

The brain of the fruit fly, Drosophila, has also been thoroughly studied. A simulated model of the fruit fly's brain offers a unique model of sibling neurons.[14] Like the roundworm, this has been made available as open-source software.[15]

Mouse brain mapping and simulation

Henry Markram mapped the types of neurons within the mouse brain and their connections between 1995 and 2005.[citation needed]

In December 2006,[16] the Blue Brain project completed a simulation of a rat's neocortical column. The neocortical column is considered the smallest functional unit of the neocortex. The neocortex is the part of the brain thought to be responsible for higher-order functions like conscious thought, and contains 10,000 neurons in the rat brain (and 108 synapses). In November 2007,[17] the project reported the end of its 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"[18] with 8 million of neurons and 6300 synapses per neuron was run on an IBM Blue Gene supercomputer by the University of Nevada's research team and IBM Almaden in 2007.[19] Each second of simulated time took ten seconds of computer time. The researchers claimed to observe "biologically consistent" nerve impulses that 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 and synapse models.[20] IBM later in the same year increased the number of neurons to 16 million and 8000 synapses per neuron, 5 seconds of which was modelled in 265 s of real time.[21] 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.[22]

In 2019, Idan Segev, one of the computational neuroscientists working on the Blue Brain Project, gave a talk titled: "Brain in the computer: what did I learn from simulating the brain." In his talk, he mentioned that the whole cortex for the mouse brain was complete and virtual EEG experiments would begin soon. 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).[23]

Blue Brain and the rat

Blue Brain is a project that was launched in May 2005 by IBM and the Swiss Federal Institute of Technology in Lausanne. The intention of the project was to create a computer simulation of a mammalian cortical column down to the molecular level.[7] The project uses a supercomputer based on IBM's Blue Gene design to simulate the electrical behavior of neurons based upon their synaptic connectivity and ion permeability. 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.

K computer and human brain

In late 2013, researchers in Japan and Germany used the K computer, then 4th fastest supercomputer, and the simulation software NEST to simulate 1% of the human brain. The simulation modeled a network consisting of 1.73 billion nerve cells connected by 10.4 trillion synapses. To realize this feat, the program recruited 82,944 processors of the K Computer. The process took 40 minutes, to complete the simulation of 1 second of neuronal network activity in real, biological, time.[24][25]

Human Brain Project

The Human Brain Project (HBP) is a 10-year program of research funded by the European Union. It began in 2013 and employs around 500 scientists across Europe. It includes 6 platforms:

  • Neuroinformatics (shared databases),
  • Brain Simulation
  • High-Performance Analytics and Computing
  • Medical informatics (patient database)
  • Neuromorphic computing (brain-inspired computing)
  • Neurorobotics (robotic simulations).

The Brain Simulation Platform (BSP) is a device for internet-accessible tools, which allows investigations that are not possible in the laboratory. They are applying Blue Brain techniques to other brain regions, such as the cerebellum, hippocampus, and the basal ganglia.[26]

Open source brain simulation

Various models of the brain have been released as open-source software (OSS) and are available on sites such as GitHub, including the C. elegans roundworm,[4] the Drosophila fruit fly,[15] and the human brain models Elysia[27] and Spaun,[28] which is the world's largest functional brain model and is based on the NENGO software architecture.[29] The Blue Brain Project Showcase likewise illustrates how models and data from the Blue Brain Project can be converted to NeuroML and PyNN (Python neuronal network models).[5]

The Brain Simulation Platform (BSP) is an internet-accessible open collaboration platform for brain simulation, created by the Human Brain Project.[26]

See also

References

  1. ↑ Fan, Xue; Markram, Henry (7 May 2019). "A Brief History of Simulation Neuroscience". Frontiers in Neuroinformatics 13: 32. doi:10.3389/fninf.2019.00032. PMID 31133838. 
  2. ↑ "Neuroinformatics and The Blue Brain Project". Informatics from Technology Networks. https://www.technologynetworks.com/informatics/articles/neuroinformatics-and-the-blue-brain-project-part-1-295850. 
  3. ↑ Colombo, Matteo (4 March 2017). "Why build a virtual brain? Large-scale neural simulations as jump start for cognitive computing". Journal of Experimental & Theoretical Artificial Intelligence 29 (2): 361–370. doi:10.1080/0952813X.2016.1148076. Bibcode: 2017JETAI..29..361C. 
  4. ↑ 4.0 4.1 4.2 C. Elegans simulation, Open source software project at Github
  5. ↑ 5.0 5.1 "Overview - Blue Brain Project Showcase - Open Source Brain". http://opensourcebrain.org/projects/blue-brain-project-showcase. Retrieved May 5, 2020. 
  6. ↑ Human Brain Project, Framework Partnership Agreement https://www.humanbrainproject.eu/documents/10180/538356/FPA++Annex+1+Part+B/41c4da2e-0e69-4295-8e98-3484677d661f
  7. ↑ 7.0 7.1 Herper, Matthew (June 6, 2005). "IBM Aims To Simulate A Brain". Forbes. https://www.forbes.com/technology/sciences/2005/06/06/cx_mh_0606ibm.html. Retrieved 2006-05-19. 
  8. ↑ Chalfie M; Sulston JE; White JG; Southgate E; Thomson JN et al. (April 1985). "The neural circuit for touch sensitivity in Caenorhabditis elegans". The Journal of Neuroscience 5 (4): 956–64. doi:10.1523/JNEUROSCI.05-04-00956.1985. PMID 3981252. 
  9. ↑ Niebur E; Erdös P (November 1993). "Theory of the locomotion of nematodes: control of the somatic motor neurons by interneurons". Mathematical Biosciences 118 (1): 51–82. doi:10.1016/0025-5564(93)90033-7. PMID 8260760. 
  10. ↑ Bryden, J.; Cohen, N. (2004). "A simulation model of the locomotion controllers for the nematodode Caenorhabditis elegans". in Schaal, S.; Ijspeert, A.; Billard, A. et al.. From Animals to Animats 8: Proceedings of the eighth international conference on the Simulation of Adaptive Behaviour. pp. 183–92. http://eprints.whiterose.ac.uk/7961/. 
  11. ↑ Mark Wakabayashi , with links to MuCoW simulation software, a demo video and the doctoral thesis Computational Plausibility of Stretch Receptors as the Basis for Motor Control in C. elegans, 2006.
  12. ↑ Mailler, R.; Avery, J.; Graves, J.; Willy, N. (7–13 March 2010). "A Biologically Accurate 3D Model of the Locomotion of Caenorhabditis Elegans". 2010 International Conference on Biosciences. pp. 84–90. doi:10.1109/BioSciencesWorld.2010.18. ISBN 978-1-4244-5929-2. http://www.personal.utulsa.edu/~roger-mailler/publications/BIOSYSCOM2010.pdf. Retrieved 14 October 2015. 
  13. ↑ "How does complex behavior spontaneously emerge in the brain?". https://phys.org/news/2013-08-complex-behavior-spontaneously-emerge-brain.html. 
  14. ↑ Arena, P.; Patane, L.; Termini, P.S.; An insect brain computational model inspired by Drosophila melanogaster: Simulation results, The 2010 International Joint Conference on Neural Networks (IJCNN).
  15. ↑ 15.0 15.1 [1], Neurokernel open-source fruit fly brain simulation
  16. ↑ "Project Milestones". Blue Brain. http://bluebrain.epfl.ch/Jahia/site/bluebrain/op/edit/pid/19085. Retrieved 2008-08-11. 
  17. ↑ "News and Media information". Blue Brain. Archived from the original on 2008-09-19. https://web.archive.org/web/20080919051656/http://bluebrain.epfl.ch/page18700.html. Retrieved 2008-08-11. 
  18. ↑ "Supercomputer Mimics Mouse's Brain" (in en-US). Huffington Post. 2008-03-28. https://www.huffingtonpost.com/2007/04/28/supercomputer-mimics-mous_n_47135.html. 
  19. ↑ IBM research report IBM
  20. ↑ "Mouse brain simulated on computer". BBC News. 27 April 2007. http://news.bbc.co.uk/1/hi/technology/6600965.stm. 
  21. ↑ Ananthanarayanan, Rajagopal; Modha, Dharmendra S (July 2007). "Scaling, stability and synchronization in mouse-sized (and larger) cortical simulations". BMC Neuroscience 8 (S2): P187. doi:10.1186/1471-2202-8-S2-P187. 
  22. ↑ Ananthanarayanan, Rajagopal; Esser, Steven K.; Simon, Horst D.; Modha, Dharmendra S. (14 November 2009). The cat is out of the bag: cortical simulations with 10 9 neurons, 10 13 synapses. pp. 1–12. doi:10.1145/1654059.1654124. 
  23. ↑ "Brain in the computer: What did I learn from simulating the brain - Idan Segev". https://www.youtube.com/watch?v=sEiDxti0opE. 
  24. ↑ "Largest neuronal network simulation to date achieved using Japanese supercomputer". ScienceDaily. August 2, 2013. https://www.sciencedaily.com/releases/2013/08/130802080237.htm. Retrieved 2020-11-25. 
  25. ↑ "Largest neuronal network simulation to date achieved using Japanese supercomputer". Jülich Forschungszentrum. August 2, 2013. https://www.fz-juelich.de/SharedDocs/Pressemitteilungen/UK/EN/2013/13-08-02LargestSimulation.html. Retrieved 2020-11-25. 
  26. ↑ 26.0 26.1 "Brain Simulation Platform". https://www.humanbrainproject.eu/en/brain-simulation/brain-simulation-platform/. Retrieved 20 January 2018. 
  27. ↑ "elysia/elysia". 8 November 2023. https://github.com/elysia/elysia. Retrieved 22 November 2023. 
  28. ↑ [2], spaun2.0 brain simulation
  29. ↑ Eliasmith, Chris; Stewart, Terrence C.; Choo, Xuan; Bekolay, Trevor; DeWolf, Travis; Tang, Yichuan; Rasmussen, Daniel (30 November 2012). "A Large-Scale Model of the Functioning Brain". Science 338 (6111): 1202–1205. doi:10.1126/science.1225266. PMID 23197532. Bibcode: 2012Sci...338.1202E. 



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