Mark Thornton

@Mark_A_Thornton

I study how people predict other people. Social neuro postdoc . Studies . Asst prof & Director starting July 2020

Vrijeme pridruživanja: rujan 2012.

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  1. Prikvačeni tweet
    4. pro 2019.

    New preprint from me and ! "People accurately predict the transition probabilities between actions" Online at here:

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  2. proslijedio/la je Tweet
    3. velj
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  3. proslijedio/la je Tweet
    1. velj

    New opinion piece on the organization of the ventral temporal cortex with Jim Haxby and

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  4. proslijedio/la je Tweet
    1. velj

    Our new paper on the synchronization of collective beliefs in social networks is out today -

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  5. proslijedio/la je Tweet
    1. velj

    Our lab’s latest: prediction of (re)mapping in place cells of one rat based on data from another rat. How? Why? And does it work? Read the story below!

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    We are very excited to announce the 2nd CompSAN preconference on the morning of May 7th 2020 in Santa Barbara CA. Details and registration here: We have an awesome set of speakers, including Jessy Lauer &

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  7. proslijedio/la je Tweet
    28. sij

    I get asked how to extract facial features (action units, gaze) from face videos but most solutions involve some technical setup (Docker, SDKs). Now, this Colab notebook extracts them from any Youtube video and you don't need to install a single thing on your laptop.

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    + 3D mind model and the 6D action model (ACT-FAST) predict representations of current and future actions! Great talk by , works w/ &

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  9. proslijedio/la je Tweet
    23. sij

    Q-learning is difficult to apply when the number of available actions is large. We show that a simple extension based on amortized stochastic search allows Q-learning to scale to high-dimensional discrete, continuous or hybrid action spaces:

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  10. proslijedio/la je Tweet
    22. sij

    The is hiring for two new positions, each ideal for folks int'd in deepening their research experience in psych / cognitive neuroscience. Please SHARE WIDELY, and if you're int'd, let us know! (1/3)

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  11. proslijedio/la je Tweet
    19. sij

    First Nautiyal Lab paper! If a reward is worth more to you, is it harder or easier to wait for it? V excited to report results from our comprehensive behavioral analysis showing that incr reward sensitivity may be a cause for incr impulsivity in a mouse lacking 5-HT1B.

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  12. proslijedio/la je Tweet
    17. sij

    New paper out today with Hilary Richardson, measuring brain responses during Theory of Mind in 125 children (including 29 diagnosed with Autism). Truly heroic data collection effort, lasting more than eight years!

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  13. proslijedio/la je Tweet
    14. sij

    New blog post alert: I used Wasserstein distances to analyze some fMRI data, and found it to be a really useful and intriguing tool: 1/7

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  14. proslijedio/la je Tweet
    9. sij
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  15. 9. sij

    Data and code supporting the present publication are freely available online : . Thanks to & Ryan Murray for organizing the special issue on "Understanding Others" at Cortex, of which is article is a part.

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  16. 9. sij

    In papers we are currently writing, we examine whether the 3d Mind Model generalizes to other geographically, linguistically, and historically distinct cultures, and examine the computational origins and functions of rationality, social impact, and valence.

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  17. 9. sij

    Together, the results suggested in this paper suggest that the 3d Mind Model is a robust, comprehensive, and generalizable account of our shared concepts of mental states.

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  18. 9. sij

    Results indicated that the 3d Mind Model did successfully generalize, with rationality, social impact, and valence each significantly predicting both similarity judgements and text semantics.

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  19. 9. sij

    Additionally, in both cases we examined a larger set of 166 mental state terms, rather than the smaller sets of 60 or less used in the fMRI studies.

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  20. 9. sij

    The latter data came from the English-language fastText word embedding of the : . The populations underlying both these measures were quite different from the college student and MTurk samples we'd used previously.

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  21. 9. sij

    The former data came from volunteer on , my online research platform (), participating in this experiment:

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