Response-based outcome predictions and confidence regulate feedback processing and learning

Influential theories emphasize the importance of predictions in learning: we learn from feedback to the extent that it is surprising, and thus conveys new information. Here, we explore the hypothesis that surprise depends not only on comparing current events to past experience, but also on online ev...

Descripción completa

Guardado en:
Detalles Bibliográficos
Autores principales: Romy Frömer, Matthew R Nassar, Rasmus Bruckner, Birgit Stürmer, Werner Sommer, Nick Yeung
Formato: article
Lenguaje:EN
Publicado: eLife Sciences Publications Ltd 2021
Materias:
R
Q
Acceso en línea:https://doaj.org/article/e68cf200493a454991ac2d0b2e114ba7
Etiquetas: Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
id oai:doaj.org-article:e68cf200493a454991ac2d0b2e114ba7
record_format dspace
spelling oai:doaj.org-article:e68cf200493a454991ac2d0b2e114ba72021-11-23T16:56:09ZResponse-based outcome predictions and confidence regulate feedback processing and learning10.7554/eLife.628252050-084Xe62825https://doaj.org/article/e68cf200493a454991ac2d0b2e114ba72021-04-01T00:00:00Zhttps://elifesciences.org/articles/62825https://doaj.org/toc/2050-084XInfluential theories emphasize the importance of predictions in learning: we learn from feedback to the extent that it is surprising, and thus conveys new information. Here, we explore the hypothesis that surprise depends not only on comparing current events to past experience, but also on online evaluation of performance via internal monitoring. Specifically, we propose that people leverage insights from response-based performance monitoring – outcome predictions and confidence – to control learning from feedback. In line with predictions from a Bayesian inference model, we find that people who are better at calibrating their confidence to the precision of their outcome predictions learn more quickly. Further in line with our proposal, EEG signatures of feedback processing are sensitive to the accuracy of, and confidence in, post-response outcome predictions. Taken together, our results suggest that online predictions and confidence serve to calibrate neural error signals to improve the efficiency of learning.Romy FrömerMatthew R NassarRasmus BrucknerBirgit StürmerWerner SommerNick YeungeLife Sciences Publications LtdarticlehumanmetacognitionlearningMedicineRScienceQBiology (General)QH301-705.5ENeLife, Vol 10 (2021)
institution DOAJ
collection DOAJ
language EN
topic human
metacognition
learning
Medicine
R
Science
Q
Biology (General)
QH301-705.5
spellingShingle human
metacognition
learning
Medicine
R
Science
Q
Biology (General)
QH301-705.5
Romy Frömer
Matthew R Nassar
Rasmus Bruckner
Birgit Stürmer
Werner Sommer
Nick Yeung
Response-based outcome predictions and confidence regulate feedback processing and learning
description Influential theories emphasize the importance of predictions in learning: we learn from feedback to the extent that it is surprising, and thus conveys new information. Here, we explore the hypothesis that surprise depends not only on comparing current events to past experience, but also on online evaluation of performance via internal monitoring. Specifically, we propose that people leverage insights from response-based performance monitoring – outcome predictions and confidence – to control learning from feedback. In line with predictions from a Bayesian inference model, we find that people who are better at calibrating their confidence to the precision of their outcome predictions learn more quickly. Further in line with our proposal, EEG signatures of feedback processing are sensitive to the accuracy of, and confidence in, post-response outcome predictions. Taken together, our results suggest that online predictions and confidence serve to calibrate neural error signals to improve the efficiency of learning.
format article
author Romy Frömer
Matthew R Nassar
Rasmus Bruckner
Birgit Stürmer
Werner Sommer
Nick Yeung
author_facet Romy Frömer
Matthew R Nassar
Rasmus Bruckner
Birgit Stürmer
Werner Sommer
Nick Yeung
author_sort Romy Frömer
title Response-based outcome predictions and confidence regulate feedback processing and learning
title_short Response-based outcome predictions and confidence regulate feedback processing and learning
title_full Response-based outcome predictions and confidence regulate feedback processing and learning
title_fullStr Response-based outcome predictions and confidence regulate feedback processing and learning
title_full_unstemmed Response-based outcome predictions and confidence regulate feedback processing and learning
title_sort response-based outcome predictions and confidence regulate feedback processing and learning
publisher eLife Sciences Publications Ltd
publishDate 2021
url https://doaj.org/article/e68cf200493a454991ac2d0b2e114ba7
work_keys_str_mv AT romyfromer responsebasedoutcomepredictionsandconfidenceregulatefeedbackprocessingandlearning
AT matthewrnassar responsebasedoutcomepredictionsandconfidenceregulatefeedbackprocessingandlearning
AT rasmusbruckner responsebasedoutcomepredictionsandconfidenceregulatefeedbackprocessingandlearning
AT birgitsturmer responsebasedoutcomepredictionsandconfidenceregulatefeedbackprocessingandlearning
AT wernersommer responsebasedoutcomepredictionsandconfidenceregulatefeedbackprocessingandlearning
AT nickyeung responsebasedoutcomepredictionsandconfidenceregulatefeedbackprocessingandlearning
_version_ 1718416246480830464