Computational roles of intrinsic synaptic dynamics
Computational roles of intrinsic synaptic dynamics
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DOI：
10.1016/j.conb.2021.06.002
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发表时间：
2021-04
影响因子：
5.7
通讯作者：
Genki Shimizu;Kensuke Yoshida;H. Kasai;Taro Toyoizumi
中科院分区：
文献类型：
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作者：
Genki Shimizu;Kensuke Yoshida;H. Kasai;Taro Toyoizumi
传统理论认为，大脑中的长期信息存储是通过修改突触效能来实现的。最近的实验结果挑战了这一观点，证明树突棘的大小，或其相应的突触重量，即使在没有神经活动的情况下也是高度不稳定的。在这里，我们回顾以前的计算工作的作用，这些内在的突触动力学。我们首先提出了神经元网络在它们存在的情况下维持稳定性能的可能性，然后我们假设内在动力学可能不仅仅是要承受的噪音，而是它们可能会改善大脑中的信息处理。
Conventional theories assume that long-term information storage in the brain is implemented by modifying synaptic efficacy. Recent experimental findings challenge this view by demonstrating that dendritic spine sizes, or their corresponding synaptic weights, are highly volatile even in the absence of neural activity. Here, we review previous computational works on the roles of these intrinsic synaptic dynamics. We first present the possibility for neuronal networks to sustain stable performance in their presence, and we then hypothesize that intrinsic dynamics could be more than mere noise to withstand, but they may improve information processing in the brain.