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www.frontiersin.org/journals/psy...
- 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 “brain connectivity maps” using correlations between regions, but those maps are usually treated as undirected, even though real brain interactions often have a direction
🧠 Can brain network “shape” help detect autism? Our new fMRI study