Egor Levchenko

Egor Levchenko

@egorlevchenko.bsky.social

πŸ“ London, UK

32 followers43 following18 posts

πŸ’₯ Our paper on NNDb-3T+ is out in Scientific Data 🧡 A dataset that puts naturalistic movie-watching and controlled sensory mapping in the same 40 people, so you can link someone's individual brain topography to how they respond to a story πŸ‘‡πŸ‘‡πŸ‘‡ www.nature.com/articles/s41...

nature.comA neuroimaging dataset combining movie-watching, eye-tracking, sensorimotor mapping, and cognitive tasks - Scientific DataScientific Data - A neuroimaging dataset combining movie-watching, eye-tracking, sensorimotor mapping, and cognitive tasks
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Bust a move! Participants moved four body parts: hand, foot, face, tongue. We modelled each movement with a GLM and contrasted body parts: Face vs Feet, Face vs Hand, Hand vs Tongue, etc. The result - a textbook homunculus: face lateral, tongue ventral, feet dorsomedial, hand in between 🧠

πŸ’₯ Our paper on NNDb-3T+ is out in Scientific Data 🧡 A dataset that puts naturalistic movie-watching and controlled sensory mapping in the same 40 people, so you can link someone's individual brain topography to how they respond to a story πŸ‘‡πŸ‘‡πŸ‘‡ www.nature.com/articles/s41...

nature.comA neuroimaging dataset combining movie-watching, eye-tracking, sensorimotor mapping, and cognitive tasks - Scientific DataScientific Data - A neuroimaging dataset combining movie-watching, eye-tracking, sensorimotor mapping, and cognitive tasks

Everyone watched "Back to the Future" in the scanner, AND did somatotopic, retinotopic, and tonotopic mapping. As far as we know, it's the first public dataset combining all of this: full movie + 3 mapping tasks + eye-tracking + physio + behavioural tests in the same cohort

Look at this beautiful figure of retinotopic mapping! Participants viewed a contrast-reversing checkerboard. We fit a pRF model per vertex on the cortical surface to estimate x, y, and pRF size. Each participant gets their own version of this, so you can define subject-specific visual ROIs! πŸ‘€

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πŸ‘‰ The key takeaway: these topology-based features seem to capture useful structure in directed brain networks and can complement more standard approaches for connectome-based classification

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In this work, we: - Build directed brain networks from resting-state fMRI (using a simple time-lagged correlation) - Summarise each network with a set of topology-based fingerprints (called Betti curves) that capture global patterns like how the network connects and forms loops

Autism spectrum disorder is linked to differences in how brain regions communicate. Many fMRI studies build β€œbrain connectivity maps” using correlations between regions, but those maps are usually treated as undirected, even though real brain interactions often have a direction

πŸ†• New open neuroimaging dataset released! I’m happy to share that our Naturalistic Neuroimaging Database (NNDb3T+) is now publicly available! NNDb3T+ captures rich, multimodal brain activity in a naturalistic setting with 40 participants and over 160 hours of scanning!

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πŸ†• New open neuroimaging dataset released! I’m happy to share that our Naturalistic Neuroimaging Database (NNDb3T+) is now publicly available! NNDb3T+ captures rich, multimodal brain activity in a naturalistic setting with 40 participants and over 160 hours of scanning!

πŸ‘‰ What’s inside: β€’ Full movie-watching inside the scanner (β€œBack to the Future” πŸŽοΈπŸ’¨) β€’ Eye-tracking during movie-watching πŸ‘€ β€’ Tasks to create individual maps of somatomotor, auditory and visual cortices (somatotopy, tonotopy, and retinotopy) 🧠 β€’ Pulse oximetry πŸ“ˆ

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