Prefrontal scaling of reward prediction error readout gates reinforcement-derived adaptive behavior in primates
Abstract
Reinforcement learning (RL) enables adaptive behavior across species via reward prediction errors (RPEs), but the neural origins of species-specific adaptability remain unknown. Integrating RL modeling, transcriptomics, and neuroimaging during reversal learning, we discovered convergent RPE signatures - shared monoaminergic/synaptic gene upregulation and neuroanatomical representations, yet humans outperformed macaques behaviorally. Single-trial decoding showed RPEs guided choices similarly in both species, but humans disproportionately recruited dorsal anterior cingulate (dACC) and dorsolateral prefrontal cortex (dlPFC). Cross-species alignment uncovered that macaque prefrontal circuits encode human-like optimal RPEs yet fail to translate them into action. Adaptability scaled not with RPE encoding fidelity, but with the areal extent of dACC/dlPFC recruitment governing RPE-to-action transformation. These findings resolve an evolutionary puzzle: behavioral performance gaps arise from executive cortical readout efficiency, not encoding capacity.
Keywords
Cite
@article{arxiv.2512.09761,
title = {Prefrontal scaling of reward prediction error readout gates reinforcement-derived adaptive behavior in primates},
author = {Tian Sang and Yichun Huang and Fangwei Zhong and Miao Wang and Shiqi Yu and Jiahui Li and Yuanjing Feng and Yizhou Wang and Kwok Sze Chai and Ravi S. Menon and Meiyun Wang and Fang Fang and Zheng Wang},
journal= {arXiv preprint arXiv:2512.09761},
year = {2025}
}
Comments
24 pages, 5 figures