Contextual modulation of value signals in reward and punishment learning.

Stefano Palminteri, Mehdi Khamassi, Mateus Joffily, Giorgio Coricelli

August 2015

Synopsis of Social media discussions

Discussions reflect strong interest, with posters referencing specific neural and behavioral findings, such as the shift of neural activity from the anterior insula to ventral striatum and effects on gain/loss framing, often using technical language and personal enthusiasm that underscores their deep engagement and acknowledgment of the study's significance.

A
Agreement
 Moderate agreement

Most discussions support the significance of context-dependent learning and neural mechanisms, indicating general agreement about the importance of the research findings.

I
Interest
 High level of interest

The use of personal enthusiasm and mentions of related past studies demonstrate high interest among the posters.

E
Engagement
 High engagement

Posts delve into detailed analysis of methodologies like fMRI data, reinforcement learning biases, and previous related papers, showing deep engagement.

I
Impact
 Moderate level of impact

The emphasis on potential implications for neuroeconomics and understanding of human learning highlights moderate perceived impact.

Social Mentions

YouTube

2 Videos

Facebook

2 Posts

Twitter

8 Posts

Blogs

8 Articles

News

8 Articles

Metrics

Video Views

14

Total Likes

5

Extended Reach

25,130

Social Features

28

Timeline: Posts about article

Top Social Media Posts

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  • Reinforcement Learning Bot
    @ReinforcementB (Twitter)

    RT @StePalminteri: In a first study, we tested if reference point-dependence affects the way outcomes are encoded in human reinforcement le…
    view full post

    June 7, 2021

    1

  • Stefano Palminteri (@stepalminteri.bsky.social)
    @StePalminteri (Twitter)

    In a first study, we tested if reference point-dependence affects the way outcomes are encoded in human reinforcement learning. The behavioural paradigm joins a learning phase with a transfer phase https://t.co/4hHxjW21zQ https://t.co/JSjQ5nz8xZ
    view full post

    June 7, 2021

    1

  • Reinforcement Learning Bot
    @ReinforcementB (Twitter)

    RT @mael_lebreton: with @StePalminteri's own little pet obsession(s), namely reinforcement learning (RL) biases – and specifically context-…
    view full post

    May 5, 2021

    1

  • Mael Lebreton
    @mael_lebreton (Twitter)

    with @StePalminteri's own little pet obsession(s), namely reinforcement learning (RL) biases – and specifically context-dependence and confirmatory updating. https://t.co/wJMJ9R1d32 https://t.co/QJLo1uz21j 3/11
    view full post

    May 5, 2021

    3

    1

  • Stefano Palminteri (@stepalminteri.bsky.social)
    @StePalminteri (Twitter)

    First of all, let me start by mentioning that this (value context-dependence in RL) is a topic I have been kind of obsessed with for few years. These are links to papers previously published on similar topics by the team https://t.co/TatsKmkM17 https://t.co/hFuFHwFzRm
    view full post

    April 5, 2021

    1

  • Stefano Palminteri (@stepalminteri.bsky.social)
    @StePalminteri (Twitter)

    In the first paper, we investigated reference-point dependence in a pretty standard task featuring a gain and a loss frame. We found that in loss contexts neutral outcomes are reframed as positive ones. This has both positive and negative effects (https://t.co/4hHxjW21zQ) https://t.co/MasqWC0UmS
    view full post

    July 28, 2020

  • Doris Pischedda
    @DorisPischedda (Twitter)

    I analyzed #fMRI data from a previous #neuroeconomics study by @StePalminteri, Khamassi, Joffily and @GioCoricelli on Contextual modulation of value signals in reward and punishment learning https://t.co/OEIbJNhv3A. 3/
    view full post

    April 15, 2020

    1

  • Stefano Palminteri (@stepalminteri.bsky.social)
    @StePalminteri (Twitter)

    To address these questions Doris re-analysed with uni- and multi-variate techniques data from our 2015 paper about context-dependent RL, involving factual and counterfactual rewards and punishments. https://t.co/4hHxjW21zQ https://t.co/7EipDaEJHD
    view full post

    January 10, 2020

Abstract Synopsis

  • The study investigates how humans learn to avoid punishment compared to seeking rewards, using computational models and fMRI scans, showing that relative context-based learning helps adjust option values.
  • When individuals are aware of the outcomes of avoided options (counterfactual info), their sense of value is more influenced by context, leading to stronger learning effects.
  • Neural activity shifts from the anterior insula to the ventral striatum depending on the context, indicating that value contextualization simplifies the brain's punishment learning process.]