practiCal fMRI

Rapid decoding of neural information representation from ultra-fast functional magnetic resonance imaging signals High spatio-temporal resolution is crucial for neuroimaging techniques to improve our understanding of human brain function. While the fMRI signal is slow and shows a spread in latencies over space, t...

Nice work by @yoichimiyawaki.bsky.social showing the fMRI hemodynamic response contains enough info to decode stimulus type within 2sec. Happy to have helped with this project.
www.biorxiv.org/content/10.1...

We’re hiring! Pls share widely:

In conjunction w/ the @bowers-wbhi.bsky.social, my team is recruiting a full-time clinical research coordinator to assist with research efforts at UC Santa Barbara. 1-2 yrs experience in MRI data collection preferred.

Submit apps to: recruit.ap.ucsb.edu/JPF02974

Rapid decoding of neural information representation from ultra-fast functional magnetic resonance imaging signals https://www.biorxiv.org/content/10.1101/2025.07.21.665938v1

fMRI Course Instructors

Online #fMRI course coming up August 6-8!
3-day intensive with lectures and hands-on analysis for all skill levels. #SPM, #ICA, #DataScience with @vcalhoun.bsky.social and Kent Kiehl. We love teaching this course and meeting students from all areas! Info+Reg here:
sites.google.com/dartmouth.ed...

But those are not data in the strict sense. I mean additional non-fMRI data about which one can make inferences about brain changes. I just wish people would measure more than just the fMRI. They may surprise themselves with the explanatory power!

Agreed. What role do ancillary measures have, esp. pulse oximetry, chest motion (or expired gases), arousal (such as eye-tracking) and other data that can explain what’s going on in the brain whatever the scan duration? Surely these affect power somehow.

I've always wanted to explore fMRI time series as a smooth, real-time movie. Now I can with LayNii IDA. Plus, with voxel-wise correlations on the fly.

Fast, intuitive, and surprisingly insightful.

40 ms TR fMRI data from @practicalfmri.bsky.social !

@layerfmri.bsky.social @afni-pt.bsky.social

One of the fun things about publishing a corrigendum is that you’ll then get loads of spam invites to conferences and special issues because they were “…truly impressed by your work titled Corrigendum to blah blah blah…” Really? I wonder what part of the incorrect sedative dose impressed them most.

Quality of scientific papers questioned as academics ‘overwhelmed’ by the millions published Widespread mockery of AI-generated rat with giant penis in one paper brings problem to public attention

www.theguardian.com/science/2025...

We're looking for an MRI Physicist to support our (honestly, really cool and exciting) clinical trial work at our London site. Details and application at the link. Please share, tell your friends, post on other networks if you can, etc. etc. Thanks!
www.linkedin.com/jobs/view/42...

Ha! No worries. Besides, you got me thinking again about sat bands and inflow effects.

PS these were collected with a printed head case. Definitely the way to go with this sort of expt. Next time I would collect pulse oximetry & chest motion, too.

All I did to get down to TR=40 ms single slice was to set 6/8ths partial Fourier and min TE=17 ms. Could shave another few ms with fatsat off, at the expense of N/2 ghosts of course! And if inflow is an issue, sat bands above/below likely add ~15 ms.

Nope, sorry! But it's really easy to set up and collect if you need complex data.

Incoming via email....

Nice. Happy to send you the .mov files and/or the raw data (120 sec, 3000 volumes apiece) if you’d like, too!

Single slice EPI to visualize brain pulsations

practicalfmri.blogspot.com/2025/06/sing...

Yep, that’s usually my experience, too. At which point I usually stop reading/listening. It’s just stories from then on.

And I always want to know what they did for motion and systemic physiology, including how mitigation steps are limited and what’s left in the data before interpretation.

There have never been any to this point - gerrymandering is but one piece of evidence - so you are invariably correct.

They want a clean sweep in Nov 2026 midterms vs Trump. Whether they find a way to mess that up (again) is the real question!

On modeling - PubMed Mapping tissue microstructure with MRI holds great promise as a noninvasive window into tissue organization at the cellular level. Having originated within the realm of diffusion NMR in the late 1970s...

If you do neuroimaging of almost any kind and you haven’t read this paper, do it. Soon.

pubmed.ncbi.nlm.nih.gov/29493816/

I tend to think of sub-voxel motion as like a sound barrier we don’t yet know how to penetrate.

PS if you do the arithmetic, a single slice TR of 40 ms isn’t really all that impressive. That’s a whole brain coverage TR of 1600 ms for 40 slices 3 mm thick.

Ha! Yeah I couldn’t quickly make a shorter segment of video for upload so resorted to the iPhone! I did at least remove the extraneous BBC news coverage of bombings in the Middle East from the sound track ;-)

And then there’s that sub-voxel tissue motion. That’s the real limit!!!

The fluctuations in sulcal CSF are even more concerning!

Sure! It’s from 2018 so I need to track it down. Will add it to a link in an upcoming blog post on it, so all the details are in one public place. Btw it was collected with a printed head case so whole head motion is teeny. (Shifts in PE axis from chest motion will remain.)

In a sagittal view you can even see the pulsations transmitted into superior sagittal sinus. Loads of pulsation in midbrain. Note also the evident non-linearity.

So you do “physio correction” in your “de-noising” pipeline, eh? This is a single EPI slice acquired at 25 fps. Lots of dynamics just from the arterial blood pressure wave! How well does your “de-noising” really do, do you think?