Whole-brain hierarchical modeling used to feel impossible under the Bayesian framework. It’s become within reach.
@mandymejia.bsky.social’s group demonstrated computational feasibility on the cortical surface and showed major gains in inferential efficiency.
www.sciencedirect.com/science/arti...
Next up: bringing this to everyday analysis.
AFNI’s new program SIMBA is in development and aims to make full whole-brain voxel-level hierarchical modeling accessible to users, hopefully within the next few months.
PhD students: Do you have experience with structural or fMRI data analysis? Are you interested in data harmonization, open science, and cognitive aging? 🧠📊 💻 If yes, this post-doc position in my lab is perfect for you!
Please share with your networks!
jobs-ca.silkroad.com/Baycrest/Car...
Postdoc position to work on neuroimaging methods with @fmri-today.bsky.social (and me) fim.nimh.nih.gov/positions-av...
Gang Chen
Gang Chen
Want to learn about FMRI visualization, processing and group analysis? Join us for the next AFNI Bootcamp (Jan. 27-29, 2026) for a fun few days of theory and interactive practicals.
Details+registration for this virtual course:
afni.nimh.nih.gov/bootcamp
Is the “standard workflow” holding back fMRI analysis?
Mass-univariate analysis is still the bread-and-butter: intuitive, fast… and chronically overfitted. Add harsh multiple-comparison penalties, and we patch the workflow with statistical band-aids. No wonder the stringency debates never die.
New AFNI Academy playlist!
This tutorial presents afni_proc.py's quality control HTML for single subject FMRI.
The APQC HTML has systematic views of data and useful derived quantities. Users can instantly rate, comment and query the fully processed subject data.
www.youtube.com/watch?v=hD9z...
What if multiple comparisons weren’t an afterthought?
Hierarchical modeling at the group level bakes the adjustment into the model. Even early demos, despite brutal computational demands, already showed clear gains when applied to a set of regions.
link.springer.com/content/pdf/...
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
Gang Chen
Rosanna Olsen
Bayesian spatial modeling provides a flexible framework for whole-brain fMRI analysis by explicitly incorporating spatial dependencies, overcoming the limitations of traditional massive univariate app...
