Learning and Organization of Memory for Evolving Patterns
Learning and Organization of Memory for Evolving Patterns
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进化模式的记忆学习和组织
DOI：
10.1103/physrevx.12.021063
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发表时间：
2022
影响因子：
12.5
通讯作者：
Nourmohammad, Armita
中科院分区：
文献类型：
--
作者：
Schnaack, Oskar H.;Peliti, Luca;Nourmohammad, Armita
为分子识别储存记忆是对外部刺激做出反应的有效策略。生物过程使用不同的策略来存储记忆。在嗅觉皮层中，当受到气味刺激时，突触连接形成，并建立一种关联的分布式记忆，这种记忆可以在再次暴露于相同的气味时恢复。相比之下，免疫系统通过不同的受体编码专门的记忆，这些受体可以识别大量进化的病原体。尽管嗅觉系统和免疫系统的记忆存储机制存在差异，但这些过程仍然可以被视为不同的信息编码策略。在这里，我们开发了一个广义Hopfield网络的分析和数值技术，以探测不同的内存策略对静态和动态（不断发展）模式的效用。我们发现，虽然经典的Hopfield网络与分布式存储器可以有效地编码的静态模式的记忆，他们是不够的，对不断变化的模式。为了遵循一个不断发展的模式，我们证明了Hopfield网络应该使用更高的学习率，这反过来会扭曲与存储的记忆吸引子相关的能量景观。具体来说，我们观察到内存吸引子之间的狭窄连接路径的出现，导致错误分类的发展模式。我们证明了具有专门子网络的分区网络是存储不断发展的模式的最佳解决方案。我们假设，病原体的进化可能是免疫系统被编码在集中记忆中的原因，与嗅觉皮层中使用的与静态气味混合物相互作用的分布式记忆相反。我们的方法提供了一个原则性的框架，研究学习和记忆检索的非平衡动力系统。
Storing memory for molecular recognition is an efficient strategy for responding to external stimuli. Biological processes use different strategies to store memory. In the olfactory cortex, synaptic connections form when stimulated by an odor and establish an associative distributed memory that can be retrieved upon reexposure to the same odors. In contrast, the immune system encodes specialized memory by diverse receptors that can recognize a multitude of evolving pathogens. Despite the mechanistic differences between memory storage in the olfactory system and the immune system, these processes can still be viewed as different information encoding strategies. Here, we develop analytical and numerical techniques for a generalized Hopfield network to probe the utility of distinct memory strategies against both static and dynamic (evolving) patterns. We find that while classical Hopfield networks with distributed memory can efficiently encode a memory of static patterns, they are inadequate against evolving patterns. To follow an evolving pattern, we show that a Hopfield network should use a higher learning rate, which can in turn distort the energy landscape associated with the stored memory attractors. Specifically, we observe the emergence of narrow connecting paths between memory attractors that lead to misclassification of evolving patterns. We demonstrate that compartmentalized networks with specialized subnetworks are the optimal solutions to memory storage for evolving patterns. We postulate that evolution of pathogens may be the reason for the immune system to be encoded in a focused memory, in contrast to the distributed memory used in the olfactory cortex that interacts with mixtures of static odors. Our approach offers a principled framework to study learning and memory retrieval in out-of-equilibrium dynamical systems.