Please use this identifier to cite or link to this item: https://doi.org/10.1038/s41467-021-21732-0
Title: Differences in subcortico-cortical interactions identified from connectome and microcircuit models in autism
Authors: Park, Bo-Yong
Hong, Seok-Jun
Valk, Sofie L.
Paquola, Casey
Benkarim, Oualid
Bethlehem, Richard A. I.
Di Martino, Adriana
Milham, Michael P.
Gozzi, Alessandro
Yeo, B. T. Thomas 
Smallwood, Jonathan
Bernhardt, Boris C.
Issue Date: 13-Apr-2021
Publisher: Nature Research
Citation: Park, Bo-Yong, Hong, Seok-Jun, Valk, Sofie L., Paquola, Casey, Benkarim, Oualid, Bethlehem, Richard A. I., Di Martino, Adriana, Milham, Michael P., Gozzi, Alessandro, Yeo, B. T. Thomas, Smallwood, Jonathan, Bernhardt, Boris C. (2021-04-13). Differences in subcortico-cortical interactions identified from connectome and microcircuit models in autism. Nature Communications 12 (1) : 2225. ScholarBank@NUS Repository. https://doi.org/10.1038/s41467-021-21732-0
Rights: Attribution 4.0 International
Abstract: The pathophysiology of autism has been suggested to involve a combination of both macroscale connectome miswiring and microcircuit anomalies. Here, we combine connectome-wide manifold learning with biophysical simulation models to understand associations between global network perturbations and microcircuit dysfunctions in autism. We studied neuroimaging and phenotypic data in 47 individuals with autism and 37 typically developing controls obtained from the Autism Brain Imaging Data Exchange initiative. Our analysis establishes significant differences in structural connectome organization in individuals with autism relative to controls, with strong between-group effects in low-level somatosensory regions and moderate effects in high-level association cortices. Computational models reveal that the degree of macroscale anomalies is related to atypical increases of recurrent excitation/inhibition, as well as subcortical inputs into cortical microcircuits, especially in sensory and motor areas. Transcriptomic association analysis based on postmortem datasets identifies genes expressed in cortical and thalamic areas from childhood to young adulthood. Finally, supervised machine learning finds that the macroscale perturbations are associated with symptom severity scores on the Autism Diagnostic Observation Schedule. Together, our analyses suggest that atypical subcortico-cortical interactions are associated with both microcircuit and macroscale connectome differences in autism. © 2021, The Author(s).
Source Title: Nature Communications
URI: https://scholarbank.nus.edu.sg/handle/10635/232751
ISSN: 2041-1723
DOI: 10.1038/s41467-021-21732-0
Rights: Attribution 4.0 International
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