Author Correction: Natural behaviour is learned through dopamine-mediated reinforcement

Nature

by Jonathan Kasdin

February 20, 2026

AI-Generated Deep Dive Summary

Nature has published an author correction for the article titled "Natural behaviour is learned through dopamine-mediated reinforcement," addressing a data preprocessing error in the study. The error occurred during the conversion of audio signals from .dat to .wav file formats, where values exceeding 1 were capped at 1 and those below -1 were set to -1. This adjustment affected approximately 15.9% of the audio data. Despite this, all analyses, figures, and conclusions remain unaffected, as the corrected data aligns with the original findings. The study originally investigated how dopamine mediates reinforcement learning in natural behaviors, highlighting its role in shaping adaptive behaviors through reward signals. The research utilized high-quality audio recordings to analyze neural activity patterns associated with dopamine signaling during various tasks. Although the preprocessing error impacted a significant portion of the data, the updated figures and amended text ensure the integrity of the study's methodology and results. This correction underscores the importance of rigorous data validation in scientific research. While the overall conclusions remain robust, the authors emphasize the need for meticulous attention to detail in handling datasets. The study's findings contribute to our understanding of dopamine's role in learning and decision-making processes, offering insights into potential applications in treating neurological disorders and enhancing artificial intelligence algorithms. For readers interested in neuroscience and reinforcement learning, this correction highlights the dynamic nature of scientific research. It demonstrates how even minor errors can be addressed without compromising the validity of a study's outcomes, while also reinforcing the critical role of transparency and reproducibility in scientific publishing. The updated version ensures that future researchers can build on this foundational work with confidence in its methodology and conclusions.

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Originally published on Nature on 2/20/2026