P277 Relation of metaplasticity with Hebbian, structural and homeostatic plasticities in recurrent neural networks
Muhammad Abdul-Amir Shamkhi Al-Shalah1,3, Neda Khalili Sabet2,3, Delaram Eslimi Esfahani3* 1-Department of Secondary Education, Ministry of Education, Babylon Governorate, Iraq 2- Institute of Biology, University ofFreiburg, Freiburg im Breisgau, Germany 3-Department of Animal Biology, Faculty of Biological Sciences, Kharazmi University, Tehran, Iran
Email*:eslimi@khu.ac.ir Introduction
The Brain plasticites rolling the brain tissues and coordinate its action have different form like hebbian, structural, homeostatic and metaplasticity , Each type of plasticity affects rewiring and influence flow in the brain in neural and circuit level. Furthermore, these different plasticities have relation & interaction between them, the previous studies did not fully cover the relation between all these plasticities.
The objective of this study is to examine and analyses the relation between these plasticity focusing on metaplasticity interaction with hebbain, structural and homeoplasticity. Methods This study uses computer simulation and neural networks to explore the relation between structural plasticity, Hebbian, homeostatic, and metaplasticity. We used artificial neural networks in this study. In our neural network, we modelled neurons as nodes, synapses as edges, and different types of plasticity as network features. We have chosen Python as the programming language to implement our model, and we use the Nest library, one of the most specialised and advanced tools for computational neuroscience research. Our model contains 500 neurons; hence it has 500 layers. This prevents neuronal supremacy while building or deleting connections. We used the LIF (leaky integrate and fire) neural model or a more specific gif cond. exp. (generalized integrate-and-fire neuron with multiple synaptic time constants). Results The result of this study when we examine the different types of plasticity and interaction between them, the metaplasticity caused the growth of synaptic surpluses, which it depends on the amount of receiving stimuli from inside and outside the network. While Structural plasticity causes the use of these excesses in rewiring the network and changing its connections. TheHebbianplasticity from another hand causes the increase or decrease of connections when receiving stimulations and reducing them, Discussion finally, in conclusion, homeostatic plasticity shows control on the network in all phases and that lead to regain the network to its original frequency when the stimulation ended.
Acknowledgements We must express our appreciation to the Vice Chancellor for Research at Kharazmi University for supporting our research. References 1-doi: 10.1093/nsr/nwaa129. 2-DOI:10.13140/RG.2.2.18527.48803 3-DOI:10.1007/s13194-012-0056-8 4-doi: 10.1111/j.1365-2923.2010.03708.x. 5-doi.org/10.3390/brainsci11040487
