Paul Taylor

@afni-pt.bsky.social

Brain imaging methods at SSCC/NIMH/NIH, working in C/Python/tcsh, some astrophysics in world line, programming/processing lecturer at AIMS. All views my own.

𝗛𝗼𝘄 𝘁𝗼 𝘁𝗵𝗶𝗻𝗸 𝗼𝗳 𝗯𝗿𝗮𝗶𝗻 𝗺𝗮𝗽𝘀? It seems like a boring visualization change but quite important! fMRI maps have been thresholded for 3+ decades so as to emphasize peaks of activation. This paper argues for a different approach. rdcu.be/B4tikBETdQZa

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This is a really nice way forward for #fmri and other neuroimaging analyses, now at the voxelwise level! Great ideas, math and implementation by @gangchen6.bsky.social, Yuan Zhong and Jian Kang. Oh, and it even has a fun acronym, too: SIMBA -> Scalable Image Modeling using a Bayesian Approach

Gang Chen@gangchen6.bsky.social · 10mo ago

And the next step? Full voxel-level modeling. Recent numerical advances cracked the scalability barrier. Voxel-level hierarchical modeling is now feasible, revealing just how punishing traditional multiple-comparison adjustments really are. arxiv.org/abs/2511.12825

Cool work, and particularly after some recent discussions at OHBM, it is really nice to see all of transparent threshold, beta-weight overlay coloration and two-tailed tests used together in the results reporting. Helps me (and maybe others) see the whole picture clearly.

Elisa Baek@elisabaek.bsky.social · last yr.

Excited to ✨share✨ that our paper on ✨sharing✨ is published! Across 3 studies that build on one another, we show that perceived alignment with one's peers increases the likelihood of information sharing. www.nature.com/articles/s41...

Looking forward to #OHBM2025 in Brisbane next week! My lab is recruiting a postdoc & neuroimaging analyst/developer to support our NIH funded work in fMRI-based Alzheimer's biomarker development (NIA R01AG083919). Email or DM if you want to meet up in Brisbane! www.statmindlab.com/join-us

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What can we do with functional MRI data? For many years, fMRI has been used to discover population-level patterns of brain function, organization and connectivity, and to understand differences in t...

statmindlab.com

The result of a large (42 authors!) collaboration: "Go Figure: Transparency in neuroscience images preserves context and clarifies interpretation" arxiv.org/abs/2504.07824 TL;DR: The FMRI world can (and should) improve results interpretation and reproducibility *today*, via transparent thresholding.

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