Bernstein Center Freiburg & Faculty of Biology, University of Freiburg, Freiburg im Breisgau, Germany.
Bioengineering Department, Imperial College London, London, United Kingdom.
PLoS Comput Biol. 2022 Feb 10;18(2):e1009836. doi: 10.1371/journal.pcbi.1009836. eCollection 2022 Feb.
Brain networks store new memories using functional and structural synaptic plasticity. Memory formation is generally attributed to Hebbian plasticity, while homeostatic plasticity is thought to have an ancillary role in stabilizing network dynamics. Here we report that homeostatic plasticity alone can also lead to the formation of stable memories. We analyze this phenomenon using a new theory of network remodeling, combined with numerical simulations of recurrent spiking neural networks that exhibit structural plasticity based on firing rate homeostasis. These networks are able to store repeatedly presented patterns and recall them upon the presentation of incomplete cues. Storage is fast, governed by the homeostatic drift. In contrast, forgetting is slow, driven by a diffusion process. Joint stimulation of neurons induces the growth of associative connections between them, leading to the formation of memory engrams. These memories are stored in a distributed fashion throughout connectivity matrix, and individual synaptic connections have only a small influence. Although memory-specific connections are increased in number, the total number of inputs and outputs of neurons undergo only small changes during stimulation. We find that homeostatic structural plasticity induces a specific type of "silent memories", different from conventional attractor states.
大脑网络使用功能和结构突触可塑性来存储新的记忆。记忆的形成通常归因于赫布可塑性，而稳态可塑性被认为在稳定网络动力学方面具有辅助作用。在这里，我们报告说，稳态可塑性本身也可以导致稳定记忆的形成。我们使用网络重塑的新理论来分析这种现象，结合基于放电率稳态的递归尖峰神经网络的数值模拟。这些网络能够存储反复呈现的模式，并在呈现不完整线索时回忆它们。存储速度快，由稳态漂移控制。相比之下，遗忘速度较慢，由扩散过程驱动。神经元的联合刺激会诱导它们之间的联想连接生长，从而形成记忆印痕。这些记忆以分布式方式存储在连接矩阵中，单个突触连接的影响很小。尽管记忆特异性连接的数量增加，但在刺激过程中神经元的输入和输出总数仅发生很小的变化。我们发现，稳态结构可塑性诱导了一种特定类型的“沉默记忆”，与传统的吸引子状态不同。
