Peter Kraemer

@PMKraemer

PhD student in Decision Neuroscience . Tweets about Memory & Decision Making | EEG | Cognitive Modeling | Bayesian Statistics. Own opinions.

Vrijeme pridruživanja: siječanj 2017.

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  1. proslijedio/la je Tweet
    3. velj

    Decisions between >2 options are tricky. In our newest work, we could not replicate a previous “divisive normalization” or “distractor effect” in decisions btw 3 food snacks. But we found remarkable dynamic interactions between valuation & attention: (1/6)

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

    Happy to see our paper being published in CBB. We show that different speed-accuracy trade-off operationalizations map onto different components of the . Thank you Leendert and Guy for your support and guidance throughout this process

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  4. 25. sij

    👉 Nice intro to the neural network in . Main takeaway: "if two words have similar contexts, then our network is motivated to learn similar word vectors for these two words"

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  5. proslijedio/la je Tweet
    23. sij

    I'm proud in to introduce evidently, a python package for simulating from evidence accumulation models. Unlike other packages, it focuses on the time course of these models, and should be particularly useful for looking at their EEG correlates!

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  6. proslijedio/la je Tweet
    21. sij

    Let me say the cliche: I am very happy that our paper is out. It addresses our ability to interact with others: Thanks to colleagues for the tremendous support, especially Peter Thier 🙏

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  7. proslijedio/la je Tweet
    20. sij

    Finally out. Out timing mega-study: comparing a range of experiment generators, both lab-based and online You can now see the preprint and view the data Audio, visual and response timing, on many packages, OSs and browsers 1/4

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  8. proslijedio/la je Tweet
    17. sij

    Got a new paper out in (w/ ) showing that algorithmically optimizing associative learning experiments may substantially increase inference accuracy. Similar approach could be used in other learning/decision making exp. paradigms.

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  9. proslijedio/la je Tweet
    16. sij

    Excited to share what and I have been working on recently! We unify and generalize statistical models of neural dynamics during decision-making using switching state-space models

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  10. proslijedio/la je Tweet
    16. sij

    New preprint out from our group (with Regina Weilbaecher and ) showing that one reason why memories bias value-based decisions is the uncertainty that (poor) memory entails. . Predictions preregistered (). One more sentence...

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  11. 9. sij

    I love good papers 🤩 Thanks to et al. (2017) for this wonderful piece of research, comparing different models with human behavior.

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  12. proslijedio/la je Tweet
    29. pro 2019.

    I just published the first release of Altair Viewer – this lets you easily view Altair charts without a web connection & in any development environment – no notebook required! Give it a spin:

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  13. proslijedio/la je Tweet
    25. pro 2019.

    I got my favorite gift of a new release, to 0.6.0! Try pip install --upgrade arviz for the latest in Bayesian plotting and diagnostics, including integration with to make your favorite plots interactive:

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  14. 4. pro 2019.

    Just found this great presentation by on word2vec and GloVe. 👏👏

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  15. proslijedio/la je Tweet
    22. stu 2019.
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  16. 13. stu 2019.

    need a little refresh on how to calculate critical statistical values? Find it here👇

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  17. 13. stu 2019.
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  18. 2. stu 2019.
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  19. 27. lis 2019.

    Can absolutely confirm that. Was a wonderful time. Thanks so much for having us & ! See you next time 👋

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  20. proslijedio/la je Tweet
    23. lis 2019.

    Check out release V1.0.0 of openEyeTrack, our open source high-speed, multi-threaded eye-tracker. openEyeTrack can provide eye tracking at ~700 frames/sec for < 1000 dollars. We are currently validating it in behavioral experiments.

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