Posts by Egor Levchenko
π 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
- Feed these fingerprints into a neural network to help distinguish ASD vs typically developing participants tested on a subset of 871 subjects (Autism Brain Imaging Dataset)
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 βbrain connectivity mapsβ using correlations between regions, but those maps are usually treated as undirected, even though real brain interactions often have a direction
π§ Can brain network βshapeβ help detect autism? Our new fMRI study
Thanks for sharing!
And many more! Check it out π
π Preprint: lnkd.in/dUP-Vn4p
πΎ Dataset: lnkd.in/dzzMcEvt
π» Code: lnkd.in/d4Vy9Ngw
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Motor activation maps!
Head movements were under good control!
π Whatβs inside:
β’ Full movie-watching inside the scanner (βBack to the Futureβ ποΈπ¨)
β’ Eye-tracking during movie-watching π
β’ Tasks to create individual maps of somatomotor, auditory and visual cortices (somatotopy, tonotopy, and retinotopy) π§
β’ Pulse oximetry π
π New open neuroimaging dataset released!
Iβm 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!
π