Please use this identifier to cite or link to this item: https://doi.org/10.1126/sciadv.aat7854
Title: Inversion of a large-scale circuit model reveals a cortical hierarchy in the dynamic resting human brain
Authors: Wang, P. 
Kong, R. 
Kong, X.
Liégeois, R. 
Orban, C. 
Deco, G.
Van Den Heuvel, M.P.
Yeo, B.T.T. 
Issue Date: 2019
Publisher: Universidad Autonoma de Yucatan
Citation: Wang, P., Kong, R., Kong, X., Liégeois, R., Orban, C., Deco, G., Van Den Heuvel, M.P., Yeo, B.T.T. (2019). Inversion of a large-scale circuit model reveals a cortical hierarchy in the dynamic resting human brain. Tropical and Subtropical Agroecosystems 21 (3) : eaat7854. ScholarBank@NUS Repository. https://doi.org/10.1126/sciadv.aat7854
Rights: Attribution-NonCommercial 4.0 International
Abstract: We considered a large-scale dynamical circuit model of human cerebral cortex with region-specific microscale properties. The model was inverted using a stochastic optimization approach, yielding markedly better fit to new, out-of-sample resting functional magnetic resonance imaging (fMRI) data. Without assuming the existence of a hierarchy, the estimated model parameters revealed a large-scale cortical gradient. At one end, sensorimotor regions had strong recurrent connections and excitatory subcortical inputs, consistent with localized processing of external stimuli. At the opposing end, default network regions had weak recurrent connections and excitatory subcortical inputs, consistent with their role in internal thought. Furthermore, recurrent connection strength and subcortical inputs provided complementary information for differentiating the levels of the hierarchy, with only the former showing strong associations with other macroscale and microscale proxies of cortical hierarchies (meta-analysis of cognitive functions, principal resting fMRI gradient, myelin, and laminarspecific neuronal density). Overall, this study provides microscale insights into a macroscale cortical hierarchy in the dynamic resting brain. © 2019 American Association for the Advancement of Science. All rights reserved.
Source Title: Tropical and Subtropical Agroecosystems
URI: https://scholarbank.nus.edu.sg/handle/10635/210836
ISSN: 18700462
DOI: 10.1126/sciadv.aat7854
Rights: Attribution-NonCommercial 4.0 International
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