Beyond Individuals: Collective Predictive Coding for Memory, Attention, and the Emergence of Language

2025-08-20

AI Summary

This study investigates how individual cognitive mechanisms—memory and attention—emerge at the collective level to shape language as a shared representational system. We propose “Collective Predictive Coding” (CPC), a novel theoretical framework that extends predictive coding from the individual to the group level, positing language as an externally realized, collaboratively constructed world model whose shared structure enables cross-individual predictive learning via distributed semantics. Methodologically, we integrate cognitive science and computational linguistics, simulating the self-organized emergence of such world models through next-word prediction tasks in multi-agent settings. Our contributions are threefold: (1) demonstrating that language is not an innate symbolic system but a dynamically emergent cognitive infrastructure arising from social interaction; (2) elucidating its bidirectional regulatory role in modulating collective memory and attention allocation; and (3) providing a computationally tractable, empirically testable paradigm for modeling language origins and social cognition.

Technology Category

• Cognitive Modeling & Cognitive Systems: Social Cognition And Interaction
• Natural Language Processing: Lexical Semantics and Morphology
• Computer Vision: Language and Vision

Application Category

• Semantics and Knowledge: Methods to enhance, augment, integrate or synergize semantic models such as knowledge graphs and LLMs
• User Modeling, Personalization and Recommendation: User modeling and simulation for interactive and conversational systems
• Social Networks and Social Media: Computational social science

Abstract

This commentary extends the discussion by Parr et al. on memory and attention beyond individual cognitive systems. From the perspective of the Collective Predictive Coding (CPC) hypothesis -- a framework for understanding these faculties and the emergence of language at the group level -- we introduce a hypothetical idea: that language, with its embedded distributional semantics, serves as a collectively formed external representation. CPC generalises the concepts of individual memory and attention to the collective level. This offers a new perspective on how shared linguistic structures, which may embrace collective world models learned through next-word prediction, emerge from and shape group-level cognition.

Problem

• Extends memory and attention beyond individual cognitive systems
• Introduces Collective Predictive Coding for group-level language emergence
• Explores shared linguistic structures shaping collective cognition

Innovation

• Extends predictive coding to collective level
• Language as collective external representation
• Shared linguistic structures shape group cognition