Sharing resources pertaining to naturalistic data analysis
Hanover, NH USA
Joined May 2020
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naturalistic-data retweeted
If you've ever wanted guidance on how to choose a "naturalistic" stimulus for a psych study (neuroimaging and/or behavior), this one's for you! @claregrall drops some wisdom from media studies that is both theoretically interesting and practically useful ⬇️
✨🚨Preprint w/@esfinn!
With naturalistic stimuli, we're overlooking something: Media like film & TV *are not natural* & THATs what makes them useful!
Here, we bring a media perspective to the psych/neuro table to answer “how do I use media for science?” psyarxiv.com/c8z9t
naturalistic-data retweeted
Movie-watching outperforms rest for functional connectivity-based prediction of behavior biorxiv.org/cgi/content/shor… #biorxiv_neursci
naturalistic-data retweeted
I am SO EXCITED to announce a new research tool we've been developing. This "TotTag" device (part of the SociTrack system) allows researchers to study proximity with high accuracy (including between children and caregivers). psyarxiv.com/h2fy6/ @salovphd /1
We're also hosting a second session on Thurs at 8pm US Eastern / Fri 2am Paris / Fri 8am Beijing if you can't make it today!
Join us in a little over an hour (2pm US Eastern time) to chat about analysis methods for naturalistic data! Message me for Zoom link #OHBM2020 naturalistic-data.org @lukejchang @jeremyRmanning @elneurozorro @ChrisBaldassano @JuhaLahnakoski
naturalistic-data retweeted
Our #OHBM2020 ed course, Analysis Methods for Naturalistic Data, is live at naturalistic-data.org/! We cover some of the most exciting tools for analyzing brain responses to movies and stories. Browse tutorials and videos online, or grab the code and try it on your own data!
naturalistic-data retweeted
Learn how to analyze brain responses to naturalistic stimuli from our @OHBM educational course organized by @lukejchang @esfinn @torwager @jeremyRmanning and featuring awesome tutorials and content from a growing list of 🤩 scientists! naturalistic-data.org/
naturalistic-data retweeted
We'll be hosting two Q&A and discussion sessions this week: 1) Weds 15 July at 2pm US Eastern time (via official OHBM platform), and 2) Thurs 16 July at 8pm US Eastern time (message me for Zoom link). Please join us if you can!
naturalistic-data retweeted
Our 'Naturalistic Neuroimaging Database' (NNDb v1) is ready to use. Eighty-six people did a battery of behavioural tests and watched one of 10 full-length #movies during #fMRI. That's 46,249,600,000 voxels or 6.69 days worth of data to play with. 🥳
See: biorxiv.org/content/10.1101/…
naturalistic-data retweeted
New preprint out! Causal understanding of narratives, and the dynamic reconfiguration of the brain using network graphs, predictive models, and hidden Markov latent state analysis
work with @BoyongPark1, Hyunjin Park, and my advisor @ShimMok
biorxiv.org/content/10.1101/…
Watch videos providing tutorials and applications of naturalistic data analysis on our youtube channel shorturl.at/ervHV by @yaarayeshurun @parkinsoncm @ChrisBaldassano @Lindageerligs @LucyLongOwen @haxbylab @jeremyRmanning @elneurozorro @esfinn
Access preprocessed Sherlock and Paranoia naturalistic neuroimaging datasets shared by @kanileke and @esfinn using @datalad shorturl.at/gsAK6
Learn how to visualize high dimensional naturalistic data using hypertools toolbox by @jeremyRmanning shorturl.at/aT056
Learn how automate feature extraction of naturalistic data using Pliers toolbox by @elneurozorro and @talyarkoni shorturl.at/shortener.php
Learn how to model dynamic functional connectivity using Hidden Semi-Markov Models in #RStats by Heather Shappell shorturl.at/fixV2
Learn how to model the dynamics of naturalistic time series data using timecorr toolbox by @jeremyRmanning shorturl.at/mwBO9
Learn how to decode the representation of natural language from fMRI using Python and naturalistic data by Jiwoong Park @ShimMok @HayoungSong5 shorturl.at/mrsy2
Learn how to apply Intersubject Correlation analysis to neuroimaging data using the Python nltools toolbox by @JuhaLahnakoski & @lukejchang shorturl.at/ghMY9
Learn how to apply event segmentation and alignment in fMRI data using Hidden Markov Models and Greedy State Boundary Search using @UseBrainIAK and statesegmentation toolbox by @ChrisBaldassano & @Lindageerligs shorturl.at/bsuW1
Learn how to apply Inter-Subject Representational Similarity Analysis to naturalistic neuroimaging data using Python by @esfinn & @lukejchang shorturl.at/osIR2
Introducing naturalistic-data.org an open access educational resource for analyzing naturalistic neuroimaging studies. Includes short talks introducing analytic techniques and interactive @ProjectJupyter notebooks that provide hands on tutorials using real data.