Comparison and Regulation of Neuronal Synchronization for Various STDP Rules
We discuss effects of various experimentally supported STDP learning rules on frequency synchronization of two unidirectional coupled neurons systematically. First, we show that synchronization windows for all STDP rules cannot be enhanced compared to constant connection under the same model. Then,...
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| Format: | Article |
| Language: | English |
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Wiley
2009-01-01
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| Series: | Neural Plasticity |
| Online Access: | http://dx.doi.org/10.1155/2009/704075 |
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| _version_ | 1832566854315409408 |
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| author | Yanhua Ruan Gang Zhao |
| author_facet | Yanhua Ruan Gang Zhao |
| author_sort | Yanhua Ruan |
| collection | DOAJ |
| description | We discuss effects of various experimentally supported STDP learning rules on frequency synchronization of two unidirectional coupled neurons systematically. First, we show that synchronization windows for all STDP rules cannot be enhanced compared to constant connection under the same model. Then, we explore the influence of learning parameters on synchronization window and find optimal parameters that lead to the widest window. Our findings indicate that synchronization strongly depends on the specific shape and the parameters of the STDP update rules. Thus, we give some explanations by analyzing the synchronization mechanisms for various STDP rules finally. |
| format | Article |
| id | doaj-art-c1c5841828794e8d8066253cad59752e |
| institution | Kabale University |
| issn | 2090-5904 1687-5443 |
| language | English |
| publishDate | 2009-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Neural Plasticity |
| spelling | doaj-art-c1c5841828794e8d8066253cad59752e2025-02-03T01:03:01ZengWileyNeural Plasticity2090-59041687-54432009-01-01200910.1155/2009/704075704075Comparison and Regulation of Neuronal Synchronization for Various STDP RulesYanhua Ruan0Gang Zhao1Institute of Complex Bio-dynamics, Jiangxi Blue Sky University, Nanchang, Jiangxi 330098, ChinaInstitute of Complex Bio-dynamics, Jiangxi Blue Sky University, Nanchang, Jiangxi 330098, ChinaWe discuss effects of various experimentally supported STDP learning rules on frequency synchronization of two unidirectional coupled neurons systematically. First, we show that synchronization windows for all STDP rules cannot be enhanced compared to constant connection under the same model. Then, we explore the influence of learning parameters on synchronization window and find optimal parameters that lead to the widest window. Our findings indicate that synchronization strongly depends on the specific shape and the parameters of the STDP update rules. Thus, we give some explanations by analyzing the synchronization mechanisms for various STDP rules finally.http://dx.doi.org/10.1155/2009/704075 |
| spellingShingle | Yanhua Ruan Gang Zhao Comparison and Regulation of Neuronal Synchronization for Various STDP Rules Neural Plasticity |
| title | Comparison and Regulation of Neuronal Synchronization for Various STDP Rules |
| title_full | Comparison and Regulation of Neuronal Synchronization for Various STDP Rules |
| title_fullStr | Comparison and Regulation of Neuronal Synchronization for Various STDP Rules |
| title_full_unstemmed | Comparison and Regulation of Neuronal Synchronization for Various STDP Rules |
| title_short | Comparison and Regulation of Neuronal Synchronization for Various STDP Rules |
| title_sort | comparison and regulation of neuronal synchronization for various stdp rules |
| url | http://dx.doi.org/10.1155/2009/704075 |
| work_keys_str_mv | AT yanhuaruan comparisonandregulationofneuronalsynchronizationforvariousstdprules AT gangzhao comparisonandregulationofneuronalsynchronizationforvariousstdprules |