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Ted Satterthwaite Profile
Ted Satterthwaite

@sattertt

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McLure II Associate Professor | University of Pennsylvania | Director, PennLINC | neuroimaging, neurodevelopment, neuroinformatics, & mental health

Philadelphia, PA
Joined April 2017
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@sattertt
Ted Satterthwaite
8 months
Ecstatic to see the RBC paper out!! MAJOR congrats to all-star first-author @goliashf. RBC has been an amazing collab between #pennlinc & @childmindinst, led with the inimitable @MilhamMichael. So many thx to the many many many collabs that made RBC happen.
@goliashf
Golia Shafiei
8 months
(1/17) Now out on bioRxiv‼️Reproducible Brain Charts: An open data resource for mapping brain development and its associations with mental health | https://t.co/ZSymcPIJ7c Funded by @NIMHgov
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@sattertt
Ted Satterthwaite
12 days
massive congrats @JonahPadawer + all-- super important work!!!! so happy to see it out!!!!
@JonahPadawer
Jonah Padawer-Curry
13 days
🚨 New science alert! Our cross-species study, now in Nature Neuroscience, demonstrates psychedelics distort how we should interpret functional brain imaging. 👇🧵 https://t.co/x3KbEcEawP #Neuroscience #Psychedelics #BrainImaging
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@JunhaoWen
Junhao (Hao) Wen
5 months
Trained as a computer scientist and bioengineer, I am over the moon to publish our paper (Neuroimaging endophenotypes reveal underlying mechanisms and genetic factors contributing to progression and development of four brain disorders) at @NatureBME: https://t.co/LLdX1RA5Al.
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nature.com
Nature Biomedical Engineering - Nine AI-derived dimensional neuroimaging endophenotypes can identify high-risk individuals within the general population prone to developing four major brain disorders.
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@sattertt
Ted Satterthwaite
5 months
Phenomenal work -- must read -- bravo!!
@XieYapei
Yapei Xie
5 months
(1/10) How do brain networks and cognition co-evolve as children enter adolescence? While valuable, cross-sectional studies offer only a single snapshot of brain–cognition relationships, missing the dynamic changes that longitudinal designs can reveal. We hypothesize that
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@sattertt
Ted Satterthwaite
8 months
CONGRATS CAROLINA!!!!!! WOOO!!!
@carolinamak15
Carolina Makowski
8 months
Since good news feels rare these days, excited to share a win - My R00 was awarded! Will be looking for a postdoc soon to help uncover biological 🧠🧬 & behavioral prospective 📈factors for adolescent eating disorders 🍽️ @UCSDHealth @UCSD_EDC @PsychiatryUcsd
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@dipymri
dipy
8 months
Tissue segmentation just got easier! DIPY 1.10 introduces Directional Average Maps (DAM) – a novel approach to extracting tissue properties directly from DWI with no extra modeling. Fast, intuitive, and insightful! 🔬⚡ #DIPY #Neuroimaging #mri
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@sattertt
Ted Satterthwaite
8 months
We love using @CircleCI for all our software (inc QSIPrep, XCP-D) but they are ghosting us on a basic billing issue despite multiple tickets. Anyone know how to get something more than an auto-reply?
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@EikoFried
Eiko Fried
9 months
1/3 Tutorial on exploring ecological momentary data is online at AMPPS, with: -Accessible ways to visualize data for better understanding -Models to get some first insights -Further reading boxes for more advanced topics -Reproducible pipeline you can run over your own data
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@kurtschilling5
kurt.schilling
9 months
Our latest study on head motion in diffusion MRI: https://t.co/ZFouHhKeBm we (1) describe typical head motion (2) show that modern preprocessing pipelines effectively mitigate motion/biases (3) no differences in microstructure between "movers" and "non-movers".
@ViljamiSairanen
Viljami Sairanen
9 months
Fresh from the press! Head Motion in Diffusion Magnetic Resonance Imaging: Quantification, Mitigation, and Structural Associations in Large, Cross-Sectional Datasets Across the Lifespan Thanks @kurtschilling5 et al. for including me! https://t.co/oK79amjAQt #dMRI
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@DavidRen555
Jianxun Ren (find me here @jianxunren.bsky.social)
9 months
So excited to share that DeepPrep is now online in @naturemethods! 🚀 It’s 10× faster than the SOTA pipeline and more robust in handling clinical cases. We’ve just released v25.1.0 with a concise GUI and support for both Win and Linux. Give it a try! 📷 https://t.co/So57Nvu7JC
@DavidRen555
Jianxun Ren (find me here @jianxunren.bsky.social)
2 years
🚀Excited to share our #preprint on DeepPrep: a high-speed, scalable preprocessing pipeline for s/fMRI, empowered by SOTA #deeplearning algorithms. What takes #fMRIPrep 7 hrs, DeepPrep achieves in just 40 mins! Dive into the details🧵 @hesheng3 @sattertt https://t.co/f77plQ9hn3
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@Bowers_WBHI
The Ann S. Bowers Women's Brain Health Initiative
9 months
Advancing Inclusive AI in Women’s Brain Health 🧠✨ We are thrilled to announce a $1.5M award from the Chan Zuckerberg Initiative to support the Women’s Brain Health Initiative in advancing inclusive AI through multi-modal biomedical datasets.
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@Go3than
Ethan Goldberg
9 months
Job Alert! Technical Director to lead the Behavioral Evaluation of Advanced Model Systems (BEAMS) Hub of the BRIDGE Center https://t.co/tq5qR9VCpr at Children's Hosp of Philadelphia. Great for a senior postdoc or research associate w/ expertise in behavior
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research.chop.edu
The Center for Brain Research in Development, Genetics and Engineering (BRIDGE) applies innovative technology and advanced model systems to understand basic mechanisms of brain development and...
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@bttyeo
Thomas Yeo
9 months
Thanks to everyone's feedback, we have updated our calculator to optimize sample size N & scan time T for fMRI studies. The first new feature is that users can explore how different N & T leads to different accuracy, e.g., N=1000 & T=30min => 81% accuracy.🧵
@bttyeo
Thomas Yeo
1 year
Here's a preliminary release of our calculator to explore sample size and scan time to maximize individual-level prediction accuracy: https://t.co/s0VTYdtaCm Let us know if anything is unclear or if there's bugs. Your feedback is welcome. If you find this calculator helpful for
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@MagdaMartinezGa
Magdalena Martínez-García PhD🦋
9 months
After 5 years of data collection (179 first-time mothers + controls), and 2 years of data analyses and article writing, the first @BeMotherProject paper is out! We uncovered a U-shaped trajectory in maternal GM volume, resolving a long-standing puzzle in the maternal brain field.
@Camila_SerBar
Camila Servin Barthet
9 months
Can’t believe our new @NatureComms paper is out! ✨🧠🤰 We tracked a cohort of 179 women before, during, and post-pregnancy, revealing a U-shaped trajectory in the mother’s brain structure linked to steroid hormone fluctuations and maternal attachment. #ParentalBrain 🧵👇
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@amykooz
Amy Kuceyeski | @[email protected]
10 months
At the Ann S. Bowers Women’s Brain Health Initiative, we want women in data science to flourish. We thus launch the #WiDSDatathon Global challenge, open to all levels now on Kaggle! Entrants will predict ADHD via fMRI, keeping sex differences in mind.
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@chrisdav66
Christos Davatzikos
10 months
Please consider helping us by providing feedback for our NiChart standalone and cloud-based software in the two very short surveys at https://t.co/nBsrr5uZpW. What do you like /would you like to see? This will also help us meet the requirements of our Brain Initiative program.
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@ndosenbach
Nico Dosenbach
10 months
In the action-mode, arousal is heightened, attention focused externally, and plans are converted to goal-directed movements and updated based on feedback, such as pain. The brain’s action-mode is created by a dedicated action-mode network (AMN) https://t.co/kxBcRiV0eh. In the
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@DoriFloris
Dorothea Floris
10 months
Thrilled to share our latest publication in @NatMentHealth 🚨 We explored the multimodal neural signature of face processing in autism using normative modeling and linked ICA in the EU-AIMS dataset. Read more here:
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@TylerMoore1981
Tyler Moore
10 months
For anyone interested in how well large language models can generate quantitative data for analysis: https://t.co/qWUNFpbhgU #AI #psychometrics #LLM #taxonomy #Statistics
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@sattertt
Ted Satterthwaite
11 months
this is truly awesome work — congrats @ZPRosenthal
@Go3than
Ethan Goldberg
1 year
Rising star @ZPRosenthal PGY-3 Resident @PennPsych uses a novel mouse model of electroconvulsive therapy (ECT) and DCS/FD-DOS in humans to show that: ECT generates a hidden wave - CSD - after seizure
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