Hung-Tu Chen

@transedward

Graduate student at Dartmouth PBS

Hanover, NH
Vrijeme pridruživanja: srpanj 2013.

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  1. Prikvačeni tweet
    31. sij

    Thus, we think between-subject prediction is a neat analysis approach that suggests an underlying regularity in how different places are mapped in the rodent hippocampus. Preprint with and : .

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  2. 31. sij

    Surprisingly, this between-subject prediction worked better than the within-subject controls we tried, and simulations suggest simple explanations such as correlated firing rates between A and B can be ruled out. 3/

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  3. 31. sij
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  4. 31. sij

    We adapted a technique from human fMRI work (hyperalignment, inspired by ) enabling us to use how subject 1 encodes A and B (e.g. left and right arms of a maze), and how subject 2 encodes A, to predict how subject 2 encodes B. 2/

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  5. 31. sij

    Where hippocampal place cells have their fields is famously hard to predict: if you know how a given subject encodes location or environment A, that doesn't tell you much about how it encodes B. 1/

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  6. proslijedio/la je Tweet

    A common model explaining flexible decision making, grid fields and cognitive control

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  7. proslijedio/la je Tweet
    13. stu 2019.

    The present is only meaningful with respect to the past and future. Super work!

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  8. proslijedio/la je Tweet
    17. lis 2019.

    These two papers from and et al. are truly beautiful. A great example of how theory and experiment can enhance each other with all contributions properly acknowledged.

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  9. proslijedio/la je Tweet
    25. ruj 2019.

    Excited to share that I’m teaching a *new course* on multi-task & meta-learning! Topics incl. optimization-based meta-learning, lifelong learning, meta-RL
, etc Slides & assignments being posted. Lecture videos to be publicly released after the course.

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  10. proslijedio/la je Tweet
    22. kol 2019.

    Hippocampal Remapping as Hidden State Inference joint work with and Matt Wilson

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  11. proslijedio/la je Tweet
    5. kol 2019.

    Our newest! "Anxiety, avoidance, and sequential evaluation" Computational psychiatry project with (1st) & . When agent's predictions about outcomes of actions are pessimistic ==> avoidance, aversive pruning, freezing behavior.

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  12. proslijedio/la je Tweet
    6. srp 2019.

    I'm updating the syllabus for my "Debugging the brain" class. What do you think are the most important computational psychiatry papers of the last few years?

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  13. proslijedio/la je Tweet
    4. srp 2019.

    Super thrilled to share our years of work on human replay with the world, now out in Cell , with my amazing supervisors: and Ray Dolan. (1/16)

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  14. proslijedio/la je Tweet
    24. tra 2019.

    We are looking for lab techs, grad students and postdocs to join our collaborative BRAIN initiative project on the neural basis of directional orientation and decision-making! With Kathy Cullen, Jim Knierim, Jeff Taube & Kechen Zhang, featuring behavior, ephys/imaging & models.

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  15. proslijedio/la je Tweet
    11. tra 2019.

    Everyone should be watching this TED talk from her in 2016. It is so clear and full of the wonders of doing science.

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  16. proslijedio/la je Tweet
    22. lis 2018.

    This is a really beautiful paper. It is exactly what theory should be. A clear concise formal argument to explain a wealth of seemingly disparate data. Very pretty

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  17. proslijedio/la je Tweet
    17. lis 2018.

    A natural history of dopamine; a thread on paper : Dopamine is critical for novel learning. Pioneering work developed methods to record from dopamine neurons. However, recordings come from animals re-learning, rather than learning anew. Why?

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  18. proslijedio/la je Tweet
    31. sij 2019.

    Question for neuro Twitter: what's the best place/way to release a large behavioral dataset? anything similar to Neurodata Without Borders, or ? We'd like to make a HUGE dataset of rat and human Parametric Working Memory publicly available, including learning period!

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  19. proslijedio/la je Tweet
    22. lis 2018.

    Excited to share our new preprint with Marc Howard, "Predicting the future with multi-scale successor representations". Mathy, but we've tried to give intuitive explanations of equations. Would love to hear thoughts!

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  20. proslijedio/la je Tweet
    22. kol 2018.

    Our preprint reporting a paradoxical relationship between motivational shifts and hippocampal replay content is now available! We found that when rats were hungry, replay was biased toward the water arm of a T-maze; when thirsty, toward the food arm ().

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