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Assistant Professor in Cognitive Neuroscience @ Maastricht University. Magnets on my mind. Previously postdoc at CMRR, Minnesota
Logan Dowdle









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New layer-fMRI manuscript finding laminar response differences across orientation-tuned surround suppression. doi.org/10.64898/202... By Emerson et al
Data only shows associations. Turning those into claims about mechanism or causation? That requires a Rosetta Stone of prior knowledge + theory. Resting-state fMRI is purely observational; correlation is its currency. From this, plenty of "theoretical toys" about brain function can be built...
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...
🚨Paper alert!🚨 TL;DR first: We used a pre-trained deep neural network to model fMRI data and to generate images predicted to elicit a large response for each many different parts of the brain. We aggregate these into an awesome interactive brain viewer: piecesofmind.psyc.unr.edu/activation_m...
About to start my travel to #OHBM2026 Excited to help organize a full day ed course on multi-echo fMRI. Schedule is here: me-ica.github.io/ohbm-2026-mu... @enekourunuela.com @drjuliamoser.bsky.social @dowdlelt.bsky.social @ohbmofficial.bsky.social
#Neuroimaging crowd, hear me out! 👀 Did you ever want to add #EyeTracking to your #fMRI study but found it too much hassle? Got existing data you’d love to add eye tracking to? Consider trying out *MR-based eye tracking* (i.e. inferring gaze from eye voxels)! Here is a 🧵 with a few options!👇 1/9
If you are setting up the meso-veins protocol for the first time at your 7T (doi.org/10.1126/scia...), you should watch this video where I am providing the most up to date pointers. As well as the tips on quality controlling your images: youtu.be/57URvSjUYRY
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14 months after submission, our article “Stimulus-modulated approach to steady state (SASS): a flexible paradigm for event-related fMRI" is now out in @natmethods.nature.com . You can read it here rdcu.be/ePJo6 It is the first first author paper from my student @renilmathew.bsky.social 👏🏽👏🏽👏🏽 …1/N
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...
How do we define "good" fMRI data? Especially with resting state, there are circularity risks if we evaluate data quality as showing the networks we expect to see. Javier Gonzalez-Castillo (& me & others) developed pBOLD, a new metric that uses multi-echo info. www.biorxiv.org/content/10.6... 1/8
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piecesofmind.psyc.unr.edu
Cortex Feature Visualization
me-ica.github.io
Gang Chen
Nature Methods - Stimulus-modulated approach to steady state (SASS) is an acquisition scheme for event-related fMRI that generates data with high temporal signal-to-noise ratios interspaced with...
rdcu.be
Stimulus-modulated approach to steady state (SASS): a flexible paradigm for event-related fMRI
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...
www.biorxiv.org
www.biorxiv.org
Rapid decoding of neural information representation from ultra-fast functional magnetic resonance imaging signals
Paul Taylor
Faruk Gulban
Mark Lescroart
Matthias Nau
Resting-State fMRI and the Risk of Overinterpretation: Noise, Mechanisms, and a Missing Rosetta Stone https://www.biorxiv.org/content/10.1101/2025.09.16.676611v1