Accurate prediction of individual subject identity and task, but not autism diagnosis, from functional connectomes.

Human Brain Mapping
Lisa Byrge, Daniel P Kennedy

Abstract

Despite enthusiasm about the potential for using fMRI-based functional connectomes in the development of biomarkers for autism spectrum disorder (ASD), the literature is full of negative findings-failures to distinguish ASD functional connectomes from those of typically developing controls (TD)-and positive findings that are inconsistent across studies. Here, we report on a new study designed to either better differentiate ASD from TD functional connectomes-or, alternatively, to refine our understanding of the factors underlying the current state of affairs. We scanned individuals with ASD and controls both at rest and while watching videos with social content. Using multiband fMRI across repeat sessions, we improved both data quantity and scanning duration by collecting up to 2 hr of data per individual. This is about 50 times the typical number of temporal samples per individual in ASD fcMRI studies. We obtained functional connectomes that were discriminable, allowing for near-perfect individual identification regardless of diagnosis, and equally reliable in both groups. However, contrary to what one might expect, we did not consistently or robustly observe in the ASD group either reductions in similarity to TD functional con...Continue Reading

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Citations

Oct 24, 2020·Proceedings of the National Academy of Sciences of the United States of America·Farnaz Zamani EsfahlaniRichard F Betzel
Jun 13, 2021·NeuroImage·Emily S Finn, Monica D Rosenberg

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Methods Mentioned

BETA
MDS
genotyping

Software Mentioned

Advanced Normalization Tools ( ANTs
epi
FEAT
FSL topup
FSL FAST
ANTs
FSL
Matlab
FMRIB
MELODIC

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