Noise and Synchronization Analysis of the Cold-Receptor Neuronal Network Model
This paper analyzes the dynamics of the cold receptor neural network model. First, it examines noise effects on neuronal stimulus in the model. From ISI plots, it is shown that there are considerable differences between purely deterministic simulations and noisy ones. The ISI-distance is used to mea...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Wiley
2014-01-01
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| Series: | Discrete Dynamics in Nature and Society |
| Online Access: | http://dx.doi.org/10.1155/2014/173894 |
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| _version_ | 1832558799443984384 |
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| author | Ying Du Rubin Wang Jingyi Qu |
| author_facet | Ying Du Rubin Wang Jingyi Qu |
| author_sort | Ying Du |
| collection | DOAJ |
| description | This paper analyzes the dynamics of the cold receptor neural network model. First, it examines noise effects on neuronal stimulus in the model. From ISI plots, it is shown that there are considerable differences between purely deterministic simulations and noisy ones. The ISI-distance is used to measure the noise effects on spike trains quantitatively. It is found that spike trains observed in neural models can be more strongly affected by noise for different temperatures in some aspects; meanwhile, spike train has greater variability with the noise intensity increasing. The synchronization of neuronal network with different connectivity patterns is also studied. It is shown that chaotic and high period patterns are more difficult to get complete synchronization than the situation in single spike and low period patterns. The neuronal network will exhibit various patterns of firing synchronization by varying some key parameters such as the coupling strength. Different types of firing synchronization are diagnosed by a correlation coefficient and the ISI-distance method. The simulations show that the synchronization status of neurons is related to the network connectivity patterns. |
| format | Article |
| id | doaj-art-5f41e1cd4d9646f29832692baa4cce80 |
| institution | Kabale University |
| issn | 1026-0226 1607-887X |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Discrete Dynamics in Nature and Society |
| spelling | doaj-art-5f41e1cd4d9646f29832692baa4cce802025-02-03T01:31:32ZengWileyDiscrete Dynamics in Nature and Society1026-02261607-887X2014-01-01201410.1155/2014/173894173894Noise and Synchronization Analysis of the Cold-Receptor Neuronal Network ModelYing Du0Rubin Wang1Jingyi Qu2Institute for Cognitive Neurodynamics, School of Science, East China University of Science and Technology, Shanghai 200237, ChinaInstitute for Cognitive Neurodynamics, School of Science, East China University of Science and Technology, Shanghai 200237, ChinaSchool of Information Science and Technology, Civil Aviation University of China, Tianjin 300300, ChinaThis paper analyzes the dynamics of the cold receptor neural network model. First, it examines noise effects on neuronal stimulus in the model. From ISI plots, it is shown that there are considerable differences between purely deterministic simulations and noisy ones. The ISI-distance is used to measure the noise effects on spike trains quantitatively. It is found that spike trains observed in neural models can be more strongly affected by noise for different temperatures in some aspects; meanwhile, spike train has greater variability with the noise intensity increasing. The synchronization of neuronal network with different connectivity patterns is also studied. It is shown that chaotic and high period patterns are more difficult to get complete synchronization than the situation in single spike and low period patterns. The neuronal network will exhibit various patterns of firing synchronization by varying some key parameters such as the coupling strength. Different types of firing synchronization are diagnosed by a correlation coefficient and the ISI-distance method. The simulations show that the synchronization status of neurons is related to the network connectivity patterns.http://dx.doi.org/10.1155/2014/173894 |
| spellingShingle | Ying Du Rubin Wang Jingyi Qu Noise and Synchronization Analysis of the Cold-Receptor Neuronal Network Model Discrete Dynamics in Nature and Society |
| title | Noise and Synchronization Analysis of the Cold-Receptor Neuronal Network Model |
| title_full | Noise and Synchronization Analysis of the Cold-Receptor Neuronal Network Model |
| title_fullStr | Noise and Synchronization Analysis of the Cold-Receptor Neuronal Network Model |
| title_full_unstemmed | Noise and Synchronization Analysis of the Cold-Receptor Neuronal Network Model |
| title_short | Noise and Synchronization Analysis of the Cold-Receptor Neuronal Network Model |
| title_sort | noise and synchronization analysis of the cold receptor neuronal network model |
| url | http://dx.doi.org/10.1155/2014/173894 |
| work_keys_str_mv | AT yingdu noiseandsynchronizationanalysisofthecoldreceptorneuronalnetworkmodel AT rubinwang noiseandsynchronizationanalysisofthecoldreceptorneuronalnetworkmodel AT jingyiqu noiseandsynchronizationanalysisofthecoldreceptorneuronalnetworkmodel |