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Exponential distance distribution of connected neurons in simulations of two-dimensional in vitro neural network development |
Zhi-Song Lv1,Chen-Ping Zhu1,2( ),Pei Nie1,Jing Zhao3,Hui-Jie Yang2,Yan-Jun Wang4,Chin-Kun Hu5,6 |
1. Department of Physics in Science College, Nanjing University of Aeronautics and Astronautics, Nanjing 210016
2. Research Center of Complex Systems Science, University of Shanghai for Science and Technology, Shanghai 200093
3. Department of Mathematics, College of Logistic Engineering of PLA, Nanjing 210016
4. College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 210016
5. Institute of Physics, Academia Sinica, Nankang, Taipei 11529
6. National Center for Theoretical Sciences, Tsing Hua University, Hsinchu 30013 |
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Abstract The distribution of the geometric distances of connected neurons is a practical factor underlying neural networks in the brain. It can affect the brain’s dynamic properties at the ground level. Karbowski derived a power-law decay distribution that has not yet been verified by experiment. In this work, we check its validity using simulations with a phenomenological model. Based on the in vitro twodimensional development of neural networks in culture vessels by Ito, we match the synapse number saturation time to obtain suitable parameters for the development process, then determine the distribution of distances between connected neurons under such conditions. Our simulations obtain a clear exponential distribution instead of a power-law one, which indicates that Karbowski’s conclusion is invalid, at least for the case of in vitro neural network development in two-dimensional culture vessels.
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| Keywords
distance distribution
connected neurons
development
exponential
power-law
neural networks
complex systems
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Corresponding Author(s):
Chen-Ping Zhu
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Issue Date: 17 March 2017
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