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Brain dynamics for confidence-weighted learning

Learning in a changing and uncertain environment is a difficult problem. A popular solution is to predict future observations and then use surprising outcomes to update those predictions. However, humans also have a sense of confidence that characterizes the precision of their predictions. Bayesian... Full description

Journal Title: BioRxiv Sep 14, 2019
Main Author: Meyniel, Florent
Format: Electronic Article Electronic Article
Language: English
Subjects:
EEG
Quelle: © ProQuest LLC All rights reserved
ID: DOI: 10.1101/769315
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recordid: proquest2290163466
title: Brain dynamics for confidence-weighted learning
format: Article
creator:
  • Meyniel, Florent
subjects:
  • Oscillations
  • Learning
  • Bayesian Analysis
  • EEG
  • Mathematical Models
  • Probability Learning
  • Arousal
ispartof: BioRxiv, Sep 14, 2019
description: Learning in a changing and uncertain environment is a difficult problem. A popular solution is to predict future observations and then use surprising outcomes to update those predictions. However, humans also have a sense of confidence that characterizes the precision of their predictions. Bayesian models...
language: eng
source: © ProQuest LLC All rights reserved
identifier: DOI: 10.1101/769315
fulltext: fulltext_linktorsrc
url: Link


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titleBrain dynamics for confidence-weighted learning
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identifierDOI: 10.1101/769315
subjectOscillations ; Learning ; Bayesian Analysis ; EEG ; Mathematical Models ; Probability Learning ; Arousal
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titleBrain dynamics for confidence-weighted learning
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abstractLearning in a changing and uncertain environment is a difficult problem. A popular solution is to predict future observations and then use surprising outcomes to update those predictions. However, humans also have a sense of confidence that characterizes the precision of their predictions. Bayesian models...
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