Leveraging this high-resolution data we were able to identify the Somato-Cognitive Action Network in a five week old infant, the earliest this network has been shown thus far, questioning the degree of ‘maturation’ we assign to infant networks.

Our 7T data showed an increase in spatial precision using a spatial resolution more appropriately matched to infants' small head sizes and improvements in reliability compared to 3T, reducing the need for long data acquisitions.

We implemented a subject specific safety assessment to ensure safe scanning within SAR limits on the Siemens Terra system using a commercially available head coil.

For these studies we acquired up to 154 min of low motion resting state fMRI data in neonates and up to 153 min with auditory oddball paradigm in 8 week old infants.

And that babies show individual specific nuances in their BOLD response patterns towards salient stimuli.

Using both resting state and task fMRI, we show that babies brain functional architecture can be divided into cortical areas that are individual specific and distinct from other babies.

Our paper additionally describes age independent upstream enhancements to the entire NiPreps suite like the implementation of a ‘fit’ and ‘transform’ model and convergence of processing with other popular workflows (ABCD-BIDS, HCP Pipelines). So check out fMRIPrep versions 23.2.1 and later!

fMRIPrep Lifespan produces high quality outputs for structural and functional images in a wide age range which we showed in a random sample of children from 1-43 months. The scalable, modular infrastructure of fMRIPrep Lifespan will ensure adaptability to data from birth to old age.

Hello all fMRIPrep users! What if you could use the same pipeline for processing MRI data from all ages? 👶👩‍🦱👩‍🦳 Check out fMRIPrep Lifespan! Our workflow optimized for data from the first years of life and further upstream enhancements to the entire NiPreps suite www.biorxiv.org/content/10.1...

ME acquisitions allow to capture developmental changes in T2* relaxation times, which are slower and more variable in newborns. This trend makes it hard to find an optimal echo time to acquire data in young populations, which can be solved by optimally combining data from different echoes of ME data

Improvements presented here allow to boost reliability without sacrificing the spatial precision necessary for precision functional imaging.

Multi-echo (ME) data acquisition with NORDIC thermal noise removal increases tSNR and reliability in data from adults, children and newborns. This can help reduce the amount of data needed for precision functional imaging.

Precision functional brain imaging from infancy to adulthood with @ariellekeller.bsky.social, @deannajgreene.bsky.social and Chuck Lynch yesterday at Flux 2024!
So exciting to be part of the new developments in this line of work!

It was such a pleasure to discuss our novel infant ME-fMRI 7T findings today! Thank you @fitngin.bsky.social!