Prefrontal scaling of reward prediction error readout gates reinforcement-derived adaptive behavior in primates

TL;DR

This study reveals that differences in adaptive behavior between humans and macaques are due to the extent of prefrontal cortex recruitment during reward prediction error processing, not the encoding of RPEs themselves.

Contribution

It uncovers how prefrontal cortex scaling influences RPE readout and behavioral adaptability across primate species, integrating neuroimaging, transcriptomics, and RL modeling.

Findings

Humans outperform macaques behaviorally in reversal learning.

Prefrontal recruitment extent correlates with adaptability, not RPE encoding fidelity.

Macaque circuits encode human-like RPEs but lack effective translation into actions.

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.