Rate-Coding Bundle Memory: A Unified Model of Memory and Control for Symbolic Computation in the Brain

arXiv:2608.29189 · q-bio.NC, cs.AI, cs.CL, cs.SC · Submitted 2026-08-29 · Read on arXiv

q-bio.NC, cs.AI, cs.CL, cs.SC

Submitted: 2026-08-29

Updated: 2026-08-29

License: http://creativecommons.org/licenses/by-sa/4.0/

The gist: We propose a neurobiologically plausible model of cognition that combines the advantages of connectionist and symbolic systems, and that can explain a wide range of cognitive phenomena.

Abstract

We propose a neurobiologically plausible model of cognition that combines the advantages of connectionist and symbolic systems, and that can explain a wide range of cognitive phenomena. This model, called Rate-Coding Bundle Memory (RCBM), is based on the Symbolic Subsystem Hypothesis, which posits that the brain implements a symbolic subsystem within its fundamentally connectionist nature. RCBM is a hybrid model that uses rate coding to represent symbols in a continuous space, and it uses a bundle memory system to store and retrieve these symbols. The model is capable of solving a wide range of cognitive phenomena, including one-shot learning, pattern separation, and the binding problem. We argue that RCBM provides a promising framework for understanding the nature of cognition, and that it can be used to develop more sophisticated models of cognition in the future.

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