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Intrinsic Spine Dynamics Are Critical for Recurrent Network Learning in Models With and Without Autism Spectrum Disorder

机译:对于有或没有自闭症谱系障碍的模型,内在脊柱动力学对于循环网络学习至关重要

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摘要

It is often assumed that Hebbian synaptic plasticity forms a cell assembly, a mutually interacting group of neurons that encodes memory. However, in recurrently connected networks with pure Hebbian plasticity, cell assemblies typically diverge or fade under ongoing changes of synaptic strength. Previously assumed mechanisms that stabilize cell assemblies do not robustly reproduce the experimentally reported unimodal and long-tailed distribution of synaptic strengths. Here, we show that augmenting Hebbian plasticity with experimentally observed intrinsic spine dynamics can stabilize cell assemblies and reproduce the distribution of synaptic strengths. Moreover, we posit that strong intrinsic spine dynamics impair learning performance. Our theory explains how excessively strong spine dynamics, experimentally observed in several animal models of autism spectrum disorder, impair learning associations in the brain.
机译:通常认为,希伯来突触可塑性形成了一个细胞组装体,这是一个相互交互的编码记忆的神经元。但是,在具有纯Hebbian可塑性的循环连接网络中,细胞组件通常在突触强度不断变化的情况下发散或褪色。以前假定的稳定细胞装配的机制不能可靠地重现实验报告的单峰和突触强度的长尾分布。在这里,我们表明,通过实验观察到的内在脊柱动力学增强Hebbian可塑性,可以稳定细胞装配并重现突触强度的分布。此外,我们认为强大的内在脊柱动力学会损害学习性能。我们的理论解释了在几种自闭症谱系障碍动物模型中通过实验观察到的过强的脊柱动力学会如何损害大脑的学习联想。

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