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Thanks, Peter Bandettini! Effective articulation is certainly not my strength, but I’m all for advancing reproducibility in fMRI analysis by minimizing information waste.

Relying solely on single studies for certainty is rarely effective. Promoting information integrity and transparency, rather than black-and-white thinking through stringent gatekeeping, is key to fostering reproducibility.

A friend sent me this article: biorxiv.org/content/10.110… on "Decisions and pitfalls of covariate selection, by Chen etal. I am glad to see these considerations penetrate the scientific circles around the National Institute of Mental Health,

Got FMRI data? Got QC? A 🧵about quality control tools in AFNI, including both quantitative/scriptable and qualitative/visual ones, now described here: biorxiv.org/content/10.110… Fun work with Gang Chen, 🥂𝔹𝕠𝕓 ℂ𝕠𝕩🧠, Taylor Hanayik, PhD, Dylan Nielson, C Rorden, J Rajendra, D Glen & R Reynolds!

Something seems awry in statistics education? A group of investigators pinpointed the largest group difference as A - C, followed by A - B, and then A - D, all based on their p-values. The issue of fixating solely on statistical evidence appears not limited to neuroimaging?

ABBA - I Have a Dream (Neuroimaging Edition) I have a dream, an HRF to estimate, To help me cope with decoding fate. If you see the trick, of a magic tool, You can shape the future, even if you fail.

(1/5) The final version of our review on approaches to #subthreshold effects in #fMRI is now available in Clin Neuroradiol: doi.org/10.1007/s00062…. Briefly, we introduce the risk of selective interpretation of #neuroimaging maps, potentially leading to a localizationist #bias...

Started in 2006 for generating FMRI processing pipelines, AFNI's afni_proc.py has never had a methods paper describing it in detail. Until now: arxiv.org/abs/2406.05248 A brief 🧵.

Nature, culture, science, ...

Multiple comparisons in neuroimaging are like an uninvited party crasher who overstays! Are we just depleting our arsenal of methodological treats? Is this intense focus on rigor in one particular aspect causing the field to miss the forest for the trees? ln.run/snpmf

How correct are the common methods for multiple comparisons in neuroimaging? Contrary to popular claims, could stringent thresholding be causing more reproducibility problems than flexible pipelines? The NARPS project might have just spilled the beans! ln.run/snpmf

Was the lack of stringency in multiple comparison adjustment a "cluster failure" in neuroimaging, or just a challenge in recognizing data hierarchies? Perhaps slapping a Band-Aid on a multiplicity wound post hoc isn't as efficient as proactive modeling! ln.run/snpmf

Can't resist the siren call of cluster boundaries? Small regions in multiple comparison adjustments get penalized for their size, even with comparable or larger effects. This raises a neurological justice issue: Is such outright discrimination justifiable? ln.run/snpmf

Ever noticed how neuroimaging papers love flaunting t, Z, or p values with color bars and tables but rarely show actual effect magnitudes? It’s like physicists talking about the speed of light and just giving a p-value—great for keeping things mysterious! ln.run/snpmf

Pleased to announce an AFNI Bootcamp Oct 28-30. It will be virtual, see here: discuss.afni.nimh.nih.gov/t/afni-bootcam… This is Part 1 of the typical course. It will cover FMRI visualization and single subject processing, including discussions of alignment, templates, ROIs and quality control.

Science is about uncovering how causes create effects. Covariate selection may seem like a small step in model building—but it can spark big chaos if mishandled. Glad to share the lesson we learned: don’t let your model wag the science; let science lead the way in model building.

Programming: where failure lurks around every corner, and debugging feels like trudging through a minefield. Yet, there's magic in the madness—when the code finally works and offers a generic solution, it's like wielding a Swiss Army knife with a triumphant smile.

Maybe slightly odd timing, but we'd like to announce: A new AFNI Bootcamp for FMRI/MRI, Jan 29-31, 2025. This part will focus on group analysis, statistics, surface analyses, results reporting and more. This event will be virtual. Please see here: discuss.afni.nimh.nih.gov/t/afni-bootcam…