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Payam Piray
389 posts
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Payam Piray
@payampiray
Assistant professor @USC psychology and neuroscience. Previously @Princeton and @DondersInst. prefer the bsky: payampiray.bsky.social
Los Angeles
piraylab.com
Joined January 2018
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  • Pinned
    user avatar
    Payam Piray
    @payampiray
    Aug 12, 2025
    New paper with @nathanieldaw in Nature Communications: an RL model that builds a successor map compositionally: it plans as well as the best models, and links components of the map used for planning to neural codes in the medial entorhinal cortex. rdcu.be/eAofi
    3.3K
  • user avatar
    Payam Piray
    @payampiray
    Jun 1, 2022
    🚨Personal news: thrilled to announce that I’ll be joining the Department of Psychology @USC as an Assistant Professor in Aug 2022. Lab will focus on studying reinforcement learning and decision making in the brain.
  • user avatar
    Payam Piray
    @payampiray
    Oct 4, 2024
    📣 I'll be recruiting PhD students for Fall 2025. Take a look at the lab website and the FAQ for prospective students: piraylab.com/join Feel free to reach out if you have questions.
    33K
  • user avatar
    Payam Piray
    @payampiray
    Jul 19, 2023
    New preprint with @nathanieldaw: Humans can distinguish volatility (rate of change or diffusion noise) & moment-to-moment stochasticity (or observation noise) and adjust their learning adaptively. As theoretically expected, these have opposite effects on humans' learning rate.
    31K
  • user avatar
    Payam Piray
    @payampiray
    Oct 31, 2023
    I'll be recruiting PhD students for Fall 2024. Take a look at the lab website and the FAQ for prospective students: piraylab.com/join Feel free to reach out if you have questions.
    23K
  • user avatar
    Payam Piray
    @payampiray
    Oct 11, 2022
    I'll be recruiting PhD students for Fall 2023. Take a look at the lab website and the FAQ for prospective students: piraylab.com/join Feel free to reach out if you have questions.
  • user avatar
    Payam Piray
    @payampiray
    Jul 17, 2019
    My latest preprint with @nathanieldaw: a transparent and simple model of learning under volatility. Compared with the state of the art, the model is algorithmically simpler, computationally more accurate, and empirically more parsimonious.
    biorxiv.org
    A transparent model for learning in volatile environments
    Sound principles of statistical inference dictate that uncertainty shapes learning. In this work, we revisit the question of learning in volatile environments, in which both the first and second-or...
  • user avatar
    Payam Piray
    @payampiray
    Oct 22, 2024
    It took a while, but this paper with @nathanieldaw is now published in @NatureComms. Reviewers had many good comments, so lots of new stuff here, especially on the computational mechanisms of how people dissociate volatility from stochasticity: nature.com/articles/s4146…
    user avatar
    Payam Piray
    @payampiray
    Jul 19, 2023
    New preprint with @nathanieldaw: Humans can distinguish volatility (rate of change or diffusion noise) & moment-to-moment stochasticity (or observation noise) and adjust their learning adaptively. As theoretically expected, these have opposite effects on humans' learning rate.
    9.4K
  • user avatar
    Payam Piray
    @payampiray
    Jun 19, 2019
    Our new work, hierarchical Bayesian inference. with @AmirDezfouli, Tom Heskes, Michael Frank, @nathanieldaw just came out. we tackle two major problems of existing methods: conservative bias towards simplistic models and sensitivity against outliers. tinyurl.com/y35te3mt
  • user avatar
    Payam Piray
    @payampiray
    Nov 15, 2021
    This is a learning model based on the joint estimation of stochasticity (observation noise) and volatility (speed of change). We used the lesion models to explain pathological learning in anxiety (the stochasticity lesion model) and amygdala damage (the volatility lesion model):
    user avatar
    Nathaniel Daw
    @nathanieldaw
    Nov 15, 2021
    Another @payampiray theory manifesto out today, this one making sense of the different types of noise/uncertainty in learning, with implications for psychiatry. Yall on twitter had lots of helpful feedback on the preprint as did referees so lots new there rdcu.be/cBnIo
  • user avatar
    Payam Piray
    @payampiray
    May 21, 2024
    New preprint with @nathanieldaw: A model for planning implemented by MEC cognitive maps (e.g., grid- and object-vector- cells). It plans efficiently & flexibly by combining planning-ready (=predictive) representations of objects/goals compositionally. 1/4
    biorxiv.org
    Reconciling Flexibility and Efficiency: Medial Entorhinal Cortex Represents a Compositional...
    The influential concept of a cognitive map envisions that the brain builds mental representations of objects, barriers, and goals. This idea has been formalized in a range of computational models...
    8.7K
  • user avatar
    Payam Piray
    @payampiray
    Feb 20, 2019
    My new paper just got published: Socially anxiety disrupts optimal adjustment of learning rate and its dorsal ACC signature in threatening situations. With Verena Ly, K roelofs @EPAN_lab, R Cools @CoolsControl and I. Toni.
    jneurosci.org
    Emotionally Aversive Cues Suppress Neural Systems Underlying Optimal Learning in Socially Anxious...
    Learning and decision-making are modulated by socio-emotional processing and such modulation is implicated in clinically relevant personality traits of social anxiety. The present study elucidates...
  • user avatar
    Payam Piray
    @payampiray
    Aug 17, 2018
    The preprint of our new work, hierarchical Bayesian inference. with @AmirDezfouli, Tom Heskes, Michael Frank, @nathanieldaw: more accurate parameter estimation and model comparison. robust against outliers and not biased towards overly simplistic models. biorxiv.org/content/early/…
  • user avatar
    Payam Piray
    @payampiray
    Aug 23, 2018
    I just finished preparing the code and a tutorial manual for "hierarchical Bayesian inference". Based on our new work with @AmirDezfouli, Tom Heskes, Michael Frank, @nathanieldaw: biorxiv.org/content/early/… The manual is here: payampiray.github.io/manual.html