Multiple neuroimaging and computational reinforcement learning studies demonstrate that different neural mechanisms and asymmetric learning rates are engaged for positive versus negative feedback.
The claim is specific, empirical, and testable within cognitive neuroscience and reinforcement learning. Multiple provided papers (e.g., [0], [2], [4]) explicitly examine and confirm differences in how brains and computational models process positive versus negative feedback (asymmetric learning rates, distinct neural pathways for rewards vs. punishments/errors). Therefore, the evidence clearly supports the claim.