Domain-specific schema reuse supports flexible learning to learn in the primate brain
Prior knowledge accelerates subsequent learning of similarly structured problems - a phenomenon termed learning to learn - by forming generalizable neural representations called neural correlates of schema (NCS). However, how the brain exploits stable NCS while remaining flexible towards changes (the stability-plasticity dilemma) remains unclear. Here, we show that the primate brain addresses this dilemma by representing the stable NCS and task-unique changes in a near-orthogonal manner. We analyzed neural activities in the dorsolateral premotor cortex of three male macaques trained to perform a series of visuomotor mapping tasks. By delineating decision and stimulus-related subspaces, we identified NCS within the decision subspace, whose reuse facilitated subsequent learning. In addition, the decision subspace exhibited a near-orthogonal relationship with the stimulus-related subspace, minimizing cross-domain interference. Our results reveal that restricting NCS to specific functional domains can preserve useful knowledge while maintaining near-orthogonality with other subspaces, enabling flexible adaptation to new environments, thereby resolving the stability-plasticity dilemma.
Authors
- Kuan Tian (ORCID: https://orcid.org/0000-0003-3138-3262)
- Shixun Cao (ORCID: https://orcid.org/0000-0002-3915-2621)
- Jianwen Gu
- Zhiping Zhao
- Ningling Ge
- Shan Yu
- Xinyong Han
- Yang Chen
Institutions
- Jilin University (CN)
- Chinese Academy of Sciences (CN)
- Chinese PLA General Hospital (CN)
- Center for Excellence in Brain Science and Intelligence Technology (CN)
- Beijing Academy of Artificial Intelligence (CN)
- Institute of Automation (CN)
- First Hospital of Jilin University (CN)
- University of Chinese Academy of Sciences (CN)
Publication Details
- Journal
- Nature Communications
- Published
- 2026-01-29
- DOI
- https://doi.org/10.1038/s41467-026-68692-x
- Primary Topic
- Face Recognition and Perception
- Type
- article
- Field-Weighted Citation Impact
- 0.00