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题名: Spike Pattern Structure Influences Synaptic Efficacy Variability under STDP and Synaptic Homeostasis. II: Spike Shuffling Methods on LIF Networks
作者: Bi, ZD ;  Zhou, CS
刊名: FRONTIERS IN COMPUTATIONAL NEUROSCIENCE
出版日期: 2016
卷号: 10, 页码:83
关键词: spike pattern structure ;  synaptic plasticity ;  efficacy variability ;  STDP ;  synaptic homeostasis ;  spike shuffling methods
学科分类: Mathematical & Computational Biology; Neurosciences & Neurology
DOI: http://dx.doi.org/10.3389/fncom.2016.00083
通讯作者: Bi, ZD (reprint author), Chinese Acad Sci, Inst Theoret Phys, State Key Lab Theoret Phys, Beijing, Peoples R China. ;  Bi, ZD ;  Zhou, CS (reprint author), Hong Kong Baptist Univ, Dept Phys, Kowloon Tong, Hong Kong, Peoples R China. ;  Zhou, CS (reprint author), Hong Kong Baptist Univ, Beijing Hong Kong Singapore Joint Ctr Nonlinear &, Ctr Nonlinear Studies, Inst Computat & Theoret Studies, Kowloon Tong, Hong Kong, Peoples R China. ;  Zhou, CS (reprint author), Beijing Computat Sci Res Ctr, Beijing, Peoples R China. ;  Zhou, CS (reprint author), Hong Kong Baptist Univ, Res Ctr, Inst Res & Continuing Educ, Shenzhen, Peoples R China.
文章类型: Article
英文摘要: Synapses may undergo variable changes during plasticity because of the variability of spike patterns such as temporal stochasticity and spatial randomness. Here, we call the variability of synaptic weight changes during plasticity to be efficacy variability. In this paper, we investigate how four aspects of spike pattern statistics (i.e., synchronous firing, burstiness/regularity, heterogeneity of rates and heterogeneity of cross-correlations) influence the efficacy variability under pair-wise additive spike-timing dependent plasticity (STDP) and synaptic homeostasis (the mean strength of plastic synapses into a neuron is bounded), by implementing spike shuffling methods onto spike patterns self-organized by a network of excitatory and inhibitory leaky integrate-and-fire (LIF) neurons. With the increase of the decay time scale of the inhibitory synaptic currents, the LIF network undergoes a transition from asynchronous state to weak synchronous state and then to synchronous bursting state. We first shuffle these spike patterns using a variety of methods, each designed to evidently change a specific pattern statistics; and then investigate the change of efficacy variability of the synapses under STDP and synaptic homeostasis, when the neurons in the network fire according to the spike patterns before and after being treated by a shuffling method. In this way, we can understand how the change of pattern statistics may cause the change of efficacy variability. Our results are consistent with those of our previous study which implements spike-generating models on converging motifs. We also find that burstiness/regularity is important to determine the efficacy variability under asynchronous states, while heterogeneity of cross-correlations is the main factor to cause efficacy variability when the network moves into synchronous bursting states (the states observed in epilepsy).
类目[WOS]: Mathematical & Computational Biology ;  Neurosciences
关键词[WOS]: TIMING-DEPENDENT PLASTICITY ;  GAMMA-OSCILLATIONS ;  NEURAL-NETWORKS ;  WORKING-MEMORY ;  VISUAL-CORTEX ;  FIRING RATES ;  GABAERGIC INTERNEURONS ;  CORTICAL NETWORKS ;  CROSS-CORRELATION ;  NEURONAL-ACTIVITY
收录类别: SCI
项目资助者: Hong Kong Baptist University (HKBU) Strategic Development Fund ;  NSFC-RGC Joint Research Scheme [HKUST/NSFC/12-13/01] ;  NSFC [11275027]
语种: 英语
Citation statistics: 
内容类型: 期刊论文
URI标识: http://ir.itp.ac.cn/handle/311006/21567
Appears in Collections:理论物理所2016年知识产出_期刊论文

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Recommended Citation:
Bi, ZD,Zhou, CS. Spike Pattern Structure Influences Synaptic Efficacy Variability under STDP and Synaptic Homeostasis. II: Spike Shuffling Methods on LIF Networks[J]. FRONTIERS IN COMPUTATIONAL NEUROSCIENCE,2016,10:83.
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