An experiment in decentralized collaborative neuroscience research
Joined February 2014
- Tweets 221
- Following 10
- Followers 342
- Likes 133
15 Photos and videos
studyforrest retweeted
25 Aug 2022
Fresh preprint out!
Enning combines #NLP algorithm and #naturalistic #movie watching. >53,000 time points.
Core insight: The default network dominates neural responses to evolving movie stories
biorxiv.org/content/10.1101/…
@Mila_Quebec @McGillBME @mcgillu @yaledailynews @dartmouth
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studyforrest retweeted
3 Aug 2022
We used data from 14 participants who watched Forrest Gump while their gaze was tracked (studyforrest.org/; thanks @eknahm and colleagues).
We determined phases of relatively high/low heart rate and used them as indicators of high/low arousal.
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studyforrest retweeted
20 May 2022
We used the amazing @studyforrest dataset and an in-lab Raiders dataset to assess our model. These two datasets were collected with different movies, different participants, and different scanners and scan parameters, allowing us to evaluate model performance in diverse settings.
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studyforrest retweeted
11 May 2022
Psst... We'll be at the @OHBM in Glasgow next month, and fired up a laser cutter to bring hand-crafted goodies - we just need more puns! So here's the deal: The DataLad-related pun with most likes underneath this posts wins a custom DataLad pen with their own message. Let's go!🥳
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studyforrest retweeted
26 Nov 2021
Announcing the new datalad.org website!
Take a tour with our data minions and find out how DataLad can help you manage your data.
ALT Illustration showing Minions collaborating world-wide
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studyforrest retweeted
14 Oct 2021
FAIRly big: A framework for computationally reproducible processing of large-scale data biorxiv.org/cgi/content/shor… #bioRxiv
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studyforrest retweeted
14 Oct 2021
But does the framework generalize? To demonstrate its potential for transparent sharing we adapted it to open data (@studyforrest) and open source software (#fmriprep). Thanks to @ReproNim and @yarikoptic for readily providing it in a container collection!
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studyforrest retweeted
3 Sep 2021
7 years after the first data publication of the project there is now an independent extension with full-length MEG data!
A studyforrest extension, MEG recordings while watching the audio-visual movie “Forrest Gump” biorxiv.org/content/10.1101/…
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studyforrest retweeted
3 Sep 2021
This is crazy cool! I did not have a close look at the data yet, but the possibilities are huge! Finally data to explore the temporal domain, and maybe even play with fusion approaches. I am so glad that the authors did this, and took the open path. Thank you very much!
3 Sep 2021
7 years after the first data publication of the project there is now an independent extension with full-length MEG data!
A studyforrest extension, MEG recordings while watching the audio-visual movie “Forrest Gump” biorxiv.org/content/10.1101/…
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28 Jul 2021
Initially published 7 years ago, the @studyforrest dataset is the 2nd most active dataset on @OpenNeuroOrg today (check it out on openneuro.org). Thanks y'all for the continued interest. Every day, the time spent on it in the past becomes more meaningful!
ALT Shows the "Forrest Gump" dataset as second most active with 7.3M accesses.
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studyforrest retweeted
1 Jul 2021
Just published in #JOSS_theOJ: 'DataLad: distributed system for joint management of code, data, and their relationship' doi.org/10.21105/joss.03262
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studyforrest retweeted
23 Jun 2021
I feel like everyone should leave an emoji-appreciation on the PR that did the magic, as a little bit of feedback on how much this has improved all of our experiences: github.com/sparkletown/spark…
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23 Jun 2021
Fantastic use of the dataset!
@mafeilong will present at 8pm EDT @OHBM #OHBM2021 on modeling idiosyncratic cortical functional topographies using movie data and #hyperalignment ohbm.sparkle.space/in/poster…. Watch introduction video at youtu.be/ScrDVsLZ7ss
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studyforrest retweeted
26 May 2021
And I hope that it will add a "Tell me how to contribute to your data!"
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11 May 2021
Thanks to @PsyInfOlaf low-level perceptual confound annotations are now available for the Forrest Gump movie stimulus and its audio description. 1/5 #studyforresthackathon
github.com/psychoinformatics…
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11 May 2021
The latter are like md5sums for the pixel content of a movie frame (also available), but their bitwise distances are interpretable as "magnitude of visual difference". This information can be used to quantify the visual "load" of the stimulus (e.g. to detect cuts). 4/5
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11 May 2021
If you have computed other features for the stimulus, please consider sharing them, or share the code to generate them. Thanks!
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