学习和组织记忆的演变模式
Learning and organization of memory for evolving patterns
摘要：
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，并建立分布式记忆，一旦再次接触，就可以恢复。相比之下，免疫系统通过识别大量进化病原体的不同受体编码专门的记忆。尽管嗅觉和免疫记忆之间存在机制差异，但这些系统仍然可以被视为不同的信息编码策略。在这里，我们提出了一个理论框架与人工神经网络的静态和动态（不断发展）的模式，以表征最佳的记忆策略。我们的方法是基于能量的Hopfield模型的推广，在该模型中，记忆被存储为网络的能量最小值。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。为了遵循不断发展的模式，我们证明了分布式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，狭窄的连接路径之间出现的记忆吸引，导致错误分类的演变模式。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编码集中记忆的原因，而不是与静态气味混合物相互作用的嗅觉皮层中使用的分布式记忆。
英文摘要：
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 distributed memory that can be retrieved upon re-exposure. In contrast, the immune system encodes specialized memory by diverse receptors that recognize a multitude of evolving pathogens. Despite the mechanistic differences between the olfactory and the immune memory, these systems can still be viewed as different information encoding strategies. Here, we present a theoretical framework with artificial neural networks to characterize optimal memory strategies for both static and dynamic (evolving) patterns. Our approach is a generalization of the energy-based Hopfield model in which memory is stored as a network's energy minima. 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 distributed network should use a higher learning rate, which in turn, can distort the energy landscape associated with the stored memory attractors. Specifically, narrow connecting paths emerge between memory attractors, leading 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 encoded a focused memory, in contrast to the distributed memory used in the olfactory cortex that interacts with mixtures of static odors.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
