Latching chains in K-nearest-neighbor and modular small-world networks
文献类型：期刊论文
| 作者 | Song SM(宋三明) ; Yao HX(姚鸿勋); Simonov, Alexander Yurievich
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| 刊名 | NETWORK-COMPUTATION IN NEURAL SYSTEMS
 |
| 出版日期 | 2015 |
| 卷号 | 26期号:1页码:1-24 |
| 关键词 | Associative retrieval latching chain modular structure Potts network sequential activity small-world |
| ISSN号 | 0954-898X |
| 产权排序 | 1 |
| 通讯作者 | 宋三明 |
| 中文摘要 | Latching dynamics retrieve pattern sequences successively by neural adaption and pattern correlation. We have previously proposed a modular latching chain model in Song et al. (2014) to better accommodate the structured transitions in the brain. Different cortical areas have different network structures. To explore how structural parameters like rewiring probability, threshold, noise and feedback connections affect the latching dynamics, two different connection schemes, K-nearest-neighbor network and modular network both having modular structure are considered. Latching chains are measured using two proposed measures characterizing length of intra-modular latching chains and sequential inter-modular association transitions. Our main findings include: (1) With decreasing threshold coefficient and rewiring probability, both the K-nearest-neighbor network and the modular network experience quantitatively similar phase change processes. (2) The modular network exhibits selectively enhanced latching in the small-world range of connectivity. (3) The K-nearest-neighbor network is more robust to changes in rewiring probability, while the modular network is more robust to the presence of noise pattern pairs and to changes in the strength of feedback connections. According to our findings, the relationships between latching chains in K-nearest-neighbor and modular networks and different forms of cognition and information processing emerging in the brain are discussed. |
| WOS标题词 | Science & Technology ; Technology ; Life Sciences & Biomedicine |
| 类目[WOS] | Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic ; Neurosciences |
| 研究领域[WOS] | Computer Science ; Engineering ; Neurosciences & Neurology |
| 关键词[WOS] | NEURAL-NETWORKS ; ASSOCIATIVE MEMORY ; CORTICAL ACTIVITY ; FRONTAL-CORTEX ; BRAIN NETWORKS ; MODELS ; NEURONS ; LANGUAGE ; DYNAMICS |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS记录号 | WOS:000352479200001 |
| 源URL | [http://ir.sia.ac.cn/handle/173321/16129]  |
| 专题 | 沈阳自动化研究所_海洋信息技术装备中心 |
| 推荐引用方式 GB/T 7714 | Song SM,Yao HX,Simonov, Alexander Yurievich. Latching chains in K-nearest-neighbor and modular small-world networks[J]. NETWORK-COMPUTATION IN NEURAL SYSTEMS,2015,26(1):1-24. |
| APA | Song SM,Yao HX,&Simonov, Alexander Yurievich.(2015).Latching chains in K-nearest-neighbor and modular small-world networks.NETWORK-COMPUTATION IN NEURAL SYSTEMS,26(1),1-24. |
| MLA | Song SM,et al."Latching chains in K-nearest-neighbor and modular small-world networks".NETWORK-COMPUTATION IN NEURAL SYSTEMS 26.1(2015):1-24. |
入库方式： OAI收割
来源：沈阳自动化研究所
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