@layerfmri.bsky.social

I try to collect talks, papers, and news regarding layer-fMRI. Focusing on acquisition. https://researchers.mgh.harvard.edu/profile/42655591/Renzo-Huber

Clinical 7T gradients can go fast — but peripheral nerve stimulation (PNS) stops you at high-res fMRI. ⚡ Meet POPE 🌍: we reshape EPI pulses to dodge PNS exactly when it spikes → robust 0.3mm fMRI, seeing intracortical veins. 🧠 w/ @SiemensHealth 👉 doi.org/10.64898/202...

New LayNii v2.10.0 is out! github.com/layerfMRI/LA... 🚀 LN2_FRISGO: This program mitigates the Fuzzy Ripple artifacts in dual polarity 3D-EPI fMRI data. 💾 Big data ready: Now handling >5GB NIFTIs to support the mesoscopic shift toward high-res, whole-brain images. @layerfmri.bsky.social

Release LayNii v2.10.0 · layerfMRI/LAYNII

New programs LN2_FRISGO: This program corrects/mitigates the Fuzzy Ripple artifacts in dual polarity 3D-EPI fMRI data. LN2_ZSCORE: Simple z-scoring for time series data. LN2_DESPIKE: Developed mai...

github.com

New auditory layer-fMRI manuscript finds that: -> deep layers contain content-specific predictions, -> superficial layers contain prediction–input alignment, -> all layers contain repetition suppression. By Haren et al. doi.org/10.1101/2025...

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Two exciting new manuscripts on layer-fMRI VASO in the Hippocampus: 1/2 Ahmadi et al. focuses on the biophysical challenges and how to account for them. They show the feasibility of laminar specific VASO- disseminated across multiple clinical 7T scanners. doi.org/10.1101/2025...

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Happy to see this out: our new preprint shows that laminar GE-BOLD fMRI decoding isn’t immune to vascular draining biases. Simulations reveal false positives due to multivariate signal spread across layers, but oversampling + deconvolution can (sometimes) improve specificity.

bioRxiv Neuroscience@biorxiv-neursci.bsky.social · 11mo ago

Vascular draining confounds laminar decoding in fMRI https://www.biorxiv.org/content/10.1101/2025.08.26.672278v1