Neuron May 2010 PMID 20510862

States versus rewards: dissociable neural prediction error signals underlying model-based and model-free reinforcement learning.

Jan Gläscher, Nathaniel Daw, Peter Dayan, John P O'Doherty

Mentions

8
Peak: 2 in Aug 2021
across 3 sources since Jul 2010

Extended reach

13,380
potential audience

Total likes

2

Video views

50

Mentions per month

Jul 2010 – Oct 2025

Where it's discussed

  • X / Twitter4 posts
  • YouTube2 videos
  • News2 articles

AI synopsis

What people are saying

The overall sentiment reflects curiosity and some technical discussion, with individuals referencing the neural signals and decision strategies highlighted in the article, such as the different neural pathways for reward and state processing. Words like 'dissociable', 'neural signals', and mentions of brain regions demonstrate analytical engagement, though the tone remains largely informational rather than highly provocative or conclusive.

AgreementNeither agree nor disagree

The discussions show some acknowledgment of the scientific significance but lack strong agreement or disagreement with the findings.

InterestModerate interest

Overall curiosity is evident, especially given the mention of neural signals and decision-making processes, yet some comments appear casual or limited in depth.

EngagementModerate engagement

Participants reference specific parts of the study, such as neural pathways and the distinction between model-based and model-free learning, indicating moderate engagement.

ImpactModerate impact

The discussion suggests recognition of the study’s potential influence on understanding decision-making and neural mechanisms, but evidence of widespread or profound impact is limited.

Abstract in brief

  • This study explains how two types of reinforcement learning—model-free and model-based—use different neural signals, called reward prediction error (RPE) and state prediction error (SPE), to guide decision-making.
  • Using fMRI scans during a decision-making task, researchers identified the neural correlates of SPE in the intraparietal sulcus and lateral prefrontal cortex, alongside the RPE signal in the ventral striatum.
  • These findings suggest that humans have two separate neural pathways for learning from experiences—one directly from rewards, and another from understanding the environment’s structure—which may support different strategies for making decisions.

Top posts

Most liked on X and Bluesky
Jordan James Etem
@JordanJamesEtem · X

@Nasdaq @InvescoUS Gläscher, J.P., Daw, N.D., Dayan, P., O’Doherty, J.P.: States versus rewards: Dissociable neural prediction error signals underlying model-based and model-free reinforcement learning. Neuron 66, 585–595 (2010) $PAYX $MSFT $INTU $FISV $DLTR $ADBE $AMZN $AMGN $CTAS $CTXS

Aug 14, 2021 · 1 share · 12,636 followers View post →
Reinforcement Learning Bot
@ReinforcementB · X

RT @JordanJamesEtem: @Nasdaq @InvescoUS Gläscher, J.P., Daw, N.D., Dayan, P., O’Doherty, J.P.: States versus rewards: Dissociable neural pr…

Aug 14, 2021 · 1 share · 600 followers View post →
ENcenatur
@encenatur · X

States versus Rewards: Dissociable Neural Prediction Error Signals Underlying Model-Based and Model-Free Reinforcement Learning https://t.co/lraML90bWV

Oct 15, 2025 · 40 followers View post →
Ryo Segawa | 瀬川諒
@BrainUploading · X

States versus Rewards: Dissociable neural prediction error signals underlying model-based and model-free reinforcement learning https://t.co/RttUne8x1V

Jun 8, 2024 · 31 followers View post →

All mentions

ENcenatur
@encenatur · X

States versus Rewards: Dissociable Neural Prediction Error Signals Underlying Model-Based and Model-Free Reinforcement Learning https://t.co/lraML90bWV

Oct 15, 2025 · 40 followers View post →
Ryo Segawa | 瀬川諒
@BrainUploading · X

States versus Rewards: Dissociable neural prediction error signals underlying model-based and model-free reinforcement learning https://t.co/RttUne8x1V

Jun 8, 2024 · 31 followers View post →
Reinforcement Learning Bot
@ReinforcementB · X

RT @JordanJamesEtem: @Nasdaq @InvescoUS Gläscher, J.P., Daw, N.D., Dayan, P., O’Doherty, J.P.: States versus rewards: Dissociable neural pr…

Aug 14, 2021 · 1 share · 600 followers View post →
Jordan James Etem
@JordanJamesEtem · X

@Nasdaq @InvescoUS Gläscher, J.P., Daw, N.D., Dayan, P., O’Doherty, J.P.: States versus rewards: Dissociable neural prediction error signals underlying model-based and model-free reinforcement learning. Neuron 66, 585–595 (2010) $PAYX $MSFT $INTU $FISV $DLTR $ADBE $AMZN $AMGN $CTAS $CTXS

Aug 14, 2021 · 1 share · 12,636 followers View post →
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