These depictions are produced from the approach described in my paper [PubMed], Locally Linear Embedding and fMRI feature selection in psychiatric classification.

Visualisations for other published figures:
ADHD (ADHD200): Peking_1 [106.5MB], Peking_2 [155MB], and Peking_3 [32.8MB] datasets
AUTISM (ABIDE): UCLA_1 [119.9MB], UM_1 [158.7MB], Yale [84.4MB], Stanford [53.7MB], USM [61.5MB] and UM_2 [84.1MB].
SCHIZOPHRENIA: COBRE/MRN (resting-state and block-design datasets) [104.9MB]
PARKINSONS: PPMI [130.1MB] NEUROCON/TAOWU [27.6MB] (FULL [63.9MB]) (New [unpublished] work)

Big thanks to Don McCurdy, and Dr. Duncan Murdoch (for his rGL and upcoming rgl2GLTF packages) who made these easy-to-consume depictions possible
P.S. you are probably (still) best-served if you view these pages on a real computer, as the renderings may not load on certain mobile device/browser configurations!

You are currently consuming the content in the latest webGL format. To view the legacy site, please click here

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