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Mesolimbic confidence signals guide perceptual learning in the absence of external feedback

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Mesolimbic confidence signals guide perceptual learning in the absence of external feedback. / Guggenmos, Matthias; Wilbertz, Gregor; Hebart, Martin N; Sterzer, Philipp.

in: ELIFE, Jahrgang 5, 29.03.2016.

Publikationen: SCORING: Beitrag in Fachzeitschrift/Zeitung › SCORING: Zeitschriftenaufsatz › Forschung › Begutachtung

Harvard

Guggenmos, M, Wilbertz, G, Hebart, MN & Sterzer, P 2016, 'Mesolimbic confidence signals guide perceptual learning in the absence of external feedback', ELIFE, Jg. 5. https://doi.org/10.7554/eLife.13388

APA

Guggenmos, M., Wilbertz, G., Hebart, M. N., & Sterzer, P. (2016). Mesolimbic confidence signals guide perceptual learning in the absence of external feedback. ELIFE, 5. https://doi.org/10.7554/eLife.13388

Vancouver

Guggenmos M, Wilbertz G, Hebart MN, Sterzer P. Mesolimbic confidence signals guide perceptual learning in the absence of external feedback. ELIFE. 2016 Mär 29;5. https://doi.org/10.7554/eLife.13388

Bibtex

@article{2037843fd280434584107698058ed7d6,
title = "Mesolimbic confidence signals guide perceptual learning in the absence of external feedback",
abstract = "It is well established that learning can occur without external feedback, yet normative reinforcement learning theories have difficulties explaining such instances of learning. Here, we propose that human observers are capable of generating their own feedback signals by monitoring internal decision variables. We investigated this hypothesis in a visual perceptual learning task using fMRI and confidence reports as a measure for this monitoring process. Employing a novel computational model in which learning is guided by confidence-based reinforcement signals, we found that mesolimbic brain areas encoded both anticipation and prediction error of confidence-in remarkable similarity to previous findings for external reward-based feedback. We demonstrate that the model accounts for choice and confidence reports and show that the mesolimbic confidence prediction error modulation derived through the model predicts individual learning success. These results provide a mechanistic neurobiological explanation for learning without external feedback by augmenting reinforcement models with confidence-based feedback.",
keywords = "Adult, Anticipation, Psychological, Computer Simulation, Feedback, Female, Humans, Learning, Limbic System, Magnetic Resonance Imaging, Models, Neurological, Reinforcement (Psychology), Young Adult, Journal Article, Research Support, Non-U.S. Gov't",
author = "Matthias Guggenmos and Gregor Wilbertz and Hebart, {Martin N} and Philipp Sterzer",
year = "2016",
month = mar,
day = "29",
doi = "10.7554/eLife.13388",
language = "English",
volume = "5",
journal = "ELIFE",
issn = "2050-084X",
publisher = "eLife Sciences Publications",

}

RIS

TY - JOUR

T1 - Mesolimbic confidence signals guide perceptual learning in the absence of external feedback

AU - Guggenmos, Matthias

AU - Wilbertz, Gregor

AU - Hebart, Martin N

AU - Sterzer, Philipp

PY - 2016/3/29

Y1 - 2016/3/29

N2 - It is well established that learning can occur without external feedback, yet normative reinforcement learning theories have difficulties explaining such instances of learning. Here, we propose that human observers are capable of generating their own feedback signals by monitoring internal decision variables. We investigated this hypothesis in a visual perceptual learning task using fMRI and confidence reports as a measure for this monitoring process. Employing a novel computational model in which learning is guided by confidence-based reinforcement signals, we found that mesolimbic brain areas encoded both anticipation and prediction error of confidence-in remarkable similarity to previous findings for external reward-based feedback. We demonstrate that the model accounts for choice and confidence reports and show that the mesolimbic confidence prediction error modulation derived through the model predicts individual learning success. These results provide a mechanistic neurobiological explanation for learning without external feedback by augmenting reinforcement models with confidence-based feedback.

AB - It is well established that learning can occur without external feedback, yet normative reinforcement learning theories have difficulties explaining such instances of learning. Here, we propose that human observers are capable of generating their own feedback signals by monitoring internal decision variables. We investigated this hypothesis in a visual perceptual learning task using fMRI and confidence reports as a measure for this monitoring process. Employing a novel computational model in which learning is guided by confidence-based reinforcement signals, we found that mesolimbic brain areas encoded both anticipation and prediction error of confidence-in remarkable similarity to previous findings for external reward-based feedback. We demonstrate that the model accounts for choice and confidence reports and show that the mesolimbic confidence prediction error modulation derived through the model predicts individual learning success. These results provide a mechanistic neurobiological explanation for learning without external feedback by augmenting reinforcement models with confidence-based feedback.

KW - Adult

KW - Anticipation, Psychological

KW - Computer Simulation

KW - Feedback

KW - Female

KW - Humans

KW - Learning

KW - Limbic System

KW - Magnetic Resonance Imaging

KW - Models, Neurological

KW - Reinforcement (Psychology)

KW - Young Adult

KW - Journal Article

KW - Research Support, Non-U.S. Gov't

U2 - 10.7554/eLife.13388

DO - 10.7554/eLife.13388

M3 - SCORING: Journal article

C2 - 27021283

VL - 5

JO - ELIFE

JF - ELIFE

SN - 2050-084X

ER -