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Related Experiment Video

Updated: Oct 10, 2025

Using the Threat Probability Task to Assess Anxiety and Fear During Uncertain and Certain Threat

Using the Threat Probability Task to Assess Anxiety and Fear During Uncertain and Certain Threat

Published on: September 12, 2014

Task Learnability Modulates Surprise but Not Valence Processing for Reinforcement Learning in Probabilistic Choice

Franz Wurm^1,2,3, Wioleta Walentowska^4,5, Benjamin Ernst¹

¹Catholic University of Eichstätt-Ingolstadt, Germany.

Journal of Cognitive Neuroscience

|December 8, 2021

Summary

This summary is machine-generated.

Task learnability impacts temporal difference (TD) reinforcement learning by suppressing surprise processing, not valence. This selective suppression affects decision-making adaptation based on a flexible cost-benefit analysis.

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Last Updated: Oct 10, 2025

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Published on: June 30, 2020

Area of Science:

Neuroscience
Cognitive Science
Computational Neuroscience

Background:

Temporal difference (TD) reinforcement learning aims to optimize decision-making by using prediction error (PE), which comprises valence and surprise.
In non-learnable tasks like gambling, decision-making improvement is impossible, raising questions about how PE components are affected.

Purpose of the Study:

To investigate how task learnability influences the processing of valence and surprise within the prediction error signal in reinforcement learning.
To determine whether the lack of learnability in gambling tasks selectively affects valence or surprise processing compared to learnable tasks.

Main Methods:

A two-armed bandit task was employed, with matched outcome sequences across a learning variant and a gambling variant.
Behavioral data and electroencephalography (ERPs) were recorded, followed by a model-based analysis to isolate neural signatures of valence and surprise.
Participants were informed about the learnability of each task variant.

Main Results:

Task learnability was found to modulate reinforcement learning by suppressing surprise processing, while valence processing remained unaffected.
Model-based ERP analysis revealed distinct neural footprints for valence and surprise, with surprise processing being diminished in the non-learnable gambling task.

Conclusions:

Task learnability selectively suppresses surprise processing in temporal difference learning, without affecting valence processing.
This mechanism allows for flexible cost-benefit arbitration, enabling the suppression of learning in non-learnable scenarios and influencing behavioral adaptation.