{"id":"doi:10.1038/s42003-021-02426-1","kind":"article","title":"Single-trial modeling separates multiple overlapping prediction errors during reward processing in human EEG","authors":["Colin W. Hoy","Sheila C. Steiner","Robert Thomas Knight"],"author_count":3,"year":2021,"published":"2021-07-23","venue":"Communications Biology","cited_by":54,"doi":"10.1038/s42003-021-02426-1","arxiv_id":null,"nct_id":null,"source_url":"https://doi.org/10.1038/s42003-021-02426-1","archive_url":"https://space-kitty.com/papers/doi:10.1038/s42003-021-02426-1","updated":null,"pmid":"34302057","pmcid":null,"openalex_id":"W3184097151","pdf_url":"https://www.nature.com/articles/s42003-021-02426-1.pdf","abstract":"Learning signals during reinforcement learning and cognitive control rely on valenced reward prediction errors (RPEs) and non-valenced salience prediction errors (PEs) driven by surprise magnitude. A core debate in reward learning focuses on whether valenced and non-valenced PEs can be isolated in the human electroencephalogram (EEG). We combine behavioral modeling and single-trial EEG regression to disentangle sequential PEs in an interval timing task dissociating outcome valence, magnitude, and probability. Multiple regression across temporal, spatial, and frequency dimensions characterized a spatio-tempo-spectral cascade from early valenced RPE value to non-valenced RPE magnitude, followed by outcome probability indexed by a late frontal positivity. Separating negative and positive outcomes revealed the valenced RPE value effect is an artifact of overlap between two non-valenced RPE magnitude responses: frontal theta feedback-related negativity on losses and posterior delta reward positivity on wins. These results reconcile longstanding debates on the sequence of components representing reward and salience PEs in the human EEG.","abstract_license":"CC-BY (publisher license, via OpenAlex)","license":"cc-by","is_open_access":true,"retracted":false,"peer_reviewed":null,"categories":["Neural and Behavioral Psychology Studies"],"details":null,"provenance":"openalex","attribution":"Abstract of \"Single-trial modeling separates multiple overlapping prediction errors during reward processing in human EEG\" by Colin W. Hoy, Sheila C. Steiner, Robert Thomas Knight, https://doi.org/10.1038/s42003-021-02426-1, used under its Creative Commons Attribution license (CC-BY); markup removed, otherwise unmodified.","topics":[{"slug":"alignment-safety","name":"AI Alignment & Safety","domain_slug":"ai"}],"cited_in_dossiers":[]}