iiinova — where your digital self keeps evolving

Reposted by Greg Kiar, PhD

Child Mind Institute @childmindinstitute.bsky.social · 14/01/2026

How do you design data science competitions that yield real breakthroughs in mental health research? New recommendations in peer-reviewed journal Nature Mental Health from researchers at the Child Mind Institute, plus a free checklist for organizers. @gkiar.bsky.social @ariannazuanazzi.bsky.social

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Reposted by Greg Kiar, PhD

Golia Shafiei @goliashf.bsky.social · 27/02/2025

(1/18) Now out on BioRxiv‼️ Reproducible Brain Charts: An open data resource for mapping brain development and its associations with mental health | doi.org/10.1101/2025... Funded by National Institute of Mental Health (NIMH)

doi.org

Reproducible Brain Charts: An open data resource for mapping brain development and its associations with mental health

Major mental disorders are increasingly understood as disorders of brain development. Large and heterogeneous samples are required to define generalizable links between brain development and psychopat...

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Greg Kiar, PhD @gkiar.bsky.social · 14/11/2024

🧠 Overall, we argue for a paradigm shift in neuroimaging research: Moving beyond mere reproducibility towards replicability, generalizability, and robustness. 7/8

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Greg Kiar, PhD @gkiar.bsky.social · 14/11/2024

✅ We’ve made a checklist that we share through the #NMIND website to help researchers incorporate and report variability analysis in their studies. This simple tool aims to standardize and encourage these practices. nmind.org/variability-... 6/8

nmind.org

Variability Capture Checklist

NMIND (this Neuroimaging Method Is Not Duplicated) is a collaborative dedicated to accelerating scientific discovery in neuroimaging research that was formed in 2020 as a grassroots initiative- resp...

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Greg Kiar, PhD @gkiar.bsky.social · 14/11/2024

While there are challenges like increased costs and complexity, these can be mitigated through open science practices and shared resources 🤝. The long-term benefits outweigh the initial hurdles. #CollaborativeScience 5/8

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Greg Kiar, PhD @gkiar.bsky.social · 14/11/2024

💡 Embracing variation offers several benefits: It improves transparency, enhances generalizability, reduces the risk of p-hacking, and allows for quantification of result stability. This leads to more robust scientific findings 🦾. #ReproducibleScience 4/8

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Greg Kiar, PhD @gkiar.bsky.social · 14/11/2024

🔍 Each of these can significantly impact results, so our perspective is this As much as possible, we should avoid making these decisions, and instead explore the multiverse-of-methods. 3/8

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Greg Kiar, PhD @gkiar.bsky.social · 14/11/2024

🛠️ When you’re constructing a study, there are many decisions you make: What data to use, experts to include, analytic options to explore, tools to use, systems to run on, and perturbations/contrasts to introduce. 2/8

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Greg Kiar, PhD @gkiar.bsky.social · 14/11/2024

🚨New paper alert!🚨 Does the sheer number of available analysis workflows (and their potential for conflicting results!!) keep you up at night? Our new 📄🔽 in Nature Comms explores how embracing this variability may actually improve generalizability of results. 1/8 🧵

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Greg Kiar, PhD @gkiar.bsky.social · 14/11/2024

Seems like a good time to make the move over to #bsky?! Hi, all! 👋 You'll mostly find me hanging out and seeing what the rest of you are talking about, with some occasional chiming in to talk about transparency and rigor in computational medicine & neuro research... (... or sports)

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