This article presents an artificial intelligence (AI) architecture intended to simulate the iterative updating of the human working memory system. It features several interconnected neural networks designed to emulate the specialized modules of the cerebral cortex. These are structured hierarchically and integrated into a global workspace. They are capable of temporarily maintaining high-level representational patterns akin to the psychological items maintained in working memory. This maintenance is made possible by persistent neural activity in the form of two modalities: sustained neural firing (resulting in a focus of attention) and synaptic potentiation (resulting in a short-term store). Representations held in persistent activity are recursively replaced resulting in incremental changes to the content of the working memory system. As this content gradually evolves, successive processing states overlap and are continuous with one another. The present article will explore how this architecture can lead to iterative shift in the distribution of coactive representations, ultimately leading to mental continuity between processing states, and thus to human-like thought and cognition. Taken together, these components outline a biologically motivated route toward synthetic consciousness or artificial sentience and subjectivity.

翻译：本文提出了一种旨在模拟人类工作记忆系统迭代更新过程的人工智能架构。该架构包含多个相互连接的神经网络，这些网络被设计用于模拟大脑皮层的特定功能模块。它们以层级结构组织，并整合于一个全局工作空间中。这些网络能够暂时维持高层次的表征模式，类似于工作记忆中保持的心理项目。这种维持通过两种形式的持续神经活动实现：持续的神经放电（形成注意焦点）与突触增强（形成短时存储）。以持续活动形式保持的表征会被递归替换，从而导致工作记忆系统内容的渐进式变化。随着内容逐渐演变，连续的处理状态相互重叠并保持连续性。本文将探讨该架构如何引发协同激活表征分布的迭代转移，最终实现处理状态之间的心理连续性，从而产生类人的思维与认知。综上所述，这些组件共同勾勒出一条基于生物机理的实现合成意识或人工感知与主观体验的技术路径。