Structure Abstraction and Generalization in a Hippocampal-Entorhinal Inspired World Model
Humans abstract experiences into structured representations to facilitate pattern inference and knowledge transfer. While the hippocampal-entorhinal (HPC-MEC) circuit is known to represent both spatial and conceptual spaces, the mechanisms for concurrently extracting abstract structures from continuous, high-dimensional dynamics remain poorly understood. We propose a brain-inspired hierarchical model that simultaneously infers latent transitions and constructs a predictive visual world model. Our architecture employs an inverse model for structural extraction alongside an HPC-MEC coupling model that dissociates relational structures (MEC) from integrated episodic scenes (HPC). Using primi...
| Authors | Tianqiu Zhang, Muyang Lyu, Xiao Liu et al. |
|---|---|
| Primary category | cs.NE |
| Published | 15 May 2026 |
| Last updated at source | 15 May 2026 |
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