Inversion of a large-scale circuit model reveals a cortical hierarchy in the dynamic resting human brain

Peng Wang, Ru Kong, Xiaolu Kong, Raphaël Liégeois, Csaba Orban, Gustavo Deco, Martijn P. Van Den Heuvel, B. T.Thomas Yeo

Research output: Contribution to journalArticleAcademicpeer-review

128 Citations (Scopus)


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.

Original languageEnglish
Article numbereaat7854
JournalTropical and Subtropical Agroecosystems
Issue number3
Publication statusPublished - 1 Jan 2019
Externally publishedYes

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