Caroline Charpentier

@caro_charp

Cognitive Neuroscience Postdoc after PhD , interested in how social behaviors take place in the brain & in mental health... Enthusiastic traveller.

Vrijeme pridruživanja: kolovoz 2011.

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  1. Prikvačeni tweet
    4. stu 2019.

    After close to 3 years of hard work, this is finally out today in BioRxiv, and calls for my first ever twitter thread! In this paper, we uncover how the brain decides which strategy to rely on when learning from observing others. 1/

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  2. proslijedio/la je Tweet
    13. sij

    new paper! "Improving the reliability of computational analyses: model-based planning and its relationship with compulsivity" w/Becca Price, , & Jiazhou Chen. tl;dr: model-based planning can be reliable, but methods have a big effect! 🧵:

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  3. proslijedio/la je Tweet
    7. sij

    New from Extent & drivers of gender imbalance in neuroscience reference lists . w/ , , Teich, Linn. Covering issues of bias, ethics, & social behavior vital to all fields grappling with their own visions of an equitable future.

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  4. proslijedio/la je Tweet
    7. sij

    Interested in doing a PhD on the computational neuroscience of mental health? Only few more days to apply for this fantastic PhD programme: If you fancy me as your supervisor - please get in touch.

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  5. proslijedio/la je Tweet

    What a year... I won’t even try to summarise it - but nothing would have been possible without your support. So thank you! This coming decade humanity will decide it’s future. Let’s make it the best one we can. We have to do the impossible. So let’s get started. Happy new year!

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  6. proslijedio/la je Tweet
    6. pro 2019.

    Can neurons recorded from human amygdala tell us sth about social cognition? We recorded from 202 cells: activity correlated to values received by others and the expectation of others receiving rewards! Distinct neurons seem to be doing self learning vs. observational learning!

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  7. proslijedio/la je Tweet

    3 and 4-year funded PhD positions in social decision neuroscience! come and work with me on projects using computational modelling, fMRI, lifespan and patient populations. Please RT 🙂 ESRC: BBSRC:

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  8. proslijedio/la je Tweet
    19. stu 2019.

    re: turk issues, I did a bit more digging and think it is valuable to see how the wonderful worker community themselves reacted to the NYTimes article. it is quite a bit different than you might think... a few links and a thought (thread)

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  9. 19. stu 2019.

    Groundbreaking work showing intact brain functional networks in hemispherectomy patients, from colleague and friend Dorit Kliemann (not on twitter). Link to paper:

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  10. 18. stu 2019.

    Awesome new work dissociating learning from safety and from danger in relation to psychopathology!

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

    Ever wondered what would happen if 70 different groups analyzed the same fMRI dataset? The pre-print of our project is out ! 1/9

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  12. proslijedio/la je Tweet
    10. stu 2019.

    Professor Tamar Makin from UCL PALS has published an article in eLIFE on “Ten common statistical mistakes to watch out for when writing or reviewing a manuscript”. Read here:

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  13. 4. stu 2019.

    Personal note: running a full fMRI replication is time-consuming and not easy, but ultimately it is better science and I learned a TON throughout the process, which I hope will facilitate future replication projects. Huge thanks to co-authors Kyo Iigaya & John O’Doherty! 11/

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  14. 4. stu 2019.

    Finally, we have here a concrete example of how replicability (or lack thereof) of neuroimaging data can be leveraged to inform and improve theoretical understanding of cognition in a way that would not have happened otherwise. 10/

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  15. 4. stu 2019.

    … but it is also one of the first demonstrations of the use of pre-registration in a computational fMRI study (see ) – a methodological advance and good news for establishing a high level of replicability while restricting analytical flexibility. 9/

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  16. 4. stu 2019.

    We believe this manuscript constitutes both a scientific and methodological advance. Not only do we provide a novel neuro-computational account of imitation learning, emulation learning, and the arbitration between them... 8/

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  17. 4. stu 2019.

    Arbitration signals were found in the right vlPFC (similar to arbitration between model-free and model-based learning in experiential learning), rACC and right TPJ (suggesting an additional engagement of social inference processes unique to OL). 7/

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  18. 4. stu 2019.

    We thus set out to revise (and simplify) the imitation component of our model and update the overall arbitration scheme accordingly. Not only did we find robust imitation signals across studies, but this new model also explained the behavioral data better. 6/

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  19. 4. stu 2019.

    Now, replications are never perfect, and while the pre-registered fMRI results pertaining to the emulation and arbitration signals replicated very robustly across studies, the imitation signals replicated less well. 5/

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  20. 4. stu 2019.

    In two independent fMRI datasets (the second a preregistered replication of the first), we show that behavior is best explained by a combination of imitation & emuation, confirm the predictions of our computational model, and replicate the behavioral findings. 4/

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  21. 4. stu 2019.

    Our theory was that the brain would keep track of how uncertain each strategy is in a given context, and assign control to the most reliable strategy. To test that, we designed a novel task, manipulating experimental variables to separate the reliability of each strategy. 3/

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