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时变突触可塑性作为簇状突触效能印痕形成的起源。

Spike timing-dependent plasticity as the origin of the formation of clustered synaptic efficacy engrams.

机构信息

Launey Research Unit for Molecular Neurocybernetics, RIKEN Brain Science Institute Wako-shi, Saitama, Japan.

出版信息

Front Comput Neurosci. 2010 Jul 14;4. doi: 10.3389/fncom.2010.00021. eCollection 2010.

Abstract

Synapse location, dendritic active properties and synaptic plasticity are all known to play some role in shaping the different input streams impinging onto a neuron. It remains unclear however, how the magnitude and spatial distribution of synaptic efficacies emerge from this interplay. Here, we investigate this interplay using a biophysically detailed neuron model of a reconstructed layer 2/3 pyramidal cell and spike timing-dependent plasticity (STDP). Specifically, we focus on the issue of how the efficacy of synapses contributed by different input streams are spatially represented in dendrites after STDP learning. We construct a simple feed forward network where a detailed model neuron receives synaptic inputs independently from multiple yet equally sized groups of afferent fibers with correlated activity, mimicking the spike activity from different neuronal populations encoding, for example, different sensory modalities. Interestingly, ensuing STDP learning, we observe that for all afferent groups, STDP leads to synaptic efficacies arranged into spatially segregated clusters effectively partitioning the dendritic tree. These segregated clusters possess a characteristic global organization in space, where they form a tessellation in which each group dominates mutually exclusive regions of the dendrite. Put simply, the dendritic imprint from different input streams left after STDP learning effectively forms what we term a "dendritic efficacy mosaic." Furthermore, we show how variations of the inputs and STDP rule affect such an organization. Our model suggests that STDP may be an important mechanism for creating a clustered plasticity engram, which shapes how different input streams are spatially represented in dendrite.

摘要

突触位置、树突活跃特性和突触可塑性都被认为在塑造传入神经元的不同输入流中发挥了一定作用。然而,目前尚不清楚突触效能的幅度和空间分布是如何从这种相互作用中产生的。在这里,我们使用一个经过重建的 2/3 层锥体神经元的详细生物物理模型和尖峰时间依赖可塑性(STDP)来研究这种相互作用。具体来说,我们关注的问题是,在 STDP 学习后,来自不同输入流的突触效能是如何在树突中空间表示的。我们构建了一个简单的前馈网络,其中一个详细的模型神经元从多个但大小相同的具有相关活动的传入纤维组独立接收突触输入,模拟来自不同神经元群体的尖峰活动,例如,不同的感觉模态。有趣的是,在进行 STDP 学习后,我们观察到对于所有传入群体,STDP 导致突触效能被排列成空间分离的簇,有效地分割了树突。这些分离的簇在空间中具有特征性的全局组织,它们形成一个镶嵌结构,其中每个簇都支配着树突的相互排斥区域。简单地说,经过 STDP 学习后,不同输入流留下的树突印记有效地形成了我们所谓的“树突效能镶嵌图”。此外,我们展示了输入和 STDP 规则的变化如何影响这种组织。我们的模型表明,STDP 可能是创建聚类可塑性记忆的重要机制,它影响了不同输入流在树突中的空间表示方式。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3235/2914531/a8bc8ed7421c/fncom-04-00021-g001.jpg

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