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The large-scale organization of dynamical neural activity across cortex emerges through long-range interactions among local circuits. We hypothesized that large-scale dynamics are also shaped by heterogeneity of intrinsic local properties across cortical areas. One key axis along which microcircuit properties are specialized relates to hierarchical levels of cortical organization. We developed a large-scale dynamical circuit model of human cortex that incorporates heterogeneity of local synaptic strengths, following a hierarchical axis inferred from magnetic resonance imaging (MRI)-derived T1- to T2-weighted (T1w/T2w) mapping and fit the model using multimodal neuroimaging data. We found that incorporating hierarchical heterogeneity substantially improves the model fit to functional MRI (fMRI)-measured resting-state functional connectivity and captures sensory-association organization of multiple fMRI features. The model predicts hierarchically organized higher-frequency spectral power, which we tested with resting-state magnetoencephalography. These findings suggest circuit-level mechanisms linking spatiotemporal levels of analysis and highlight the importance of local properties and their hierarchical specialization on the large-scale organization of human cortical dynamics.

Original publication

DOI

10.1016/j.neuron.2019.01.017

Type

Journal article

Journal

Neuron

Publication Date

20/03/2019

Volume

101

Pages

1181 - 1194.e13

Keywords

brain networks, computational model, cortical gradients, cortical hierarchy, functional connectivity, large-scale modeling, magnetoencephalography, resting-state fMRI, structural connectivity, Brain Mapping, Cerebral Cortex, Functional Neuroimaging, Humans, Magnetic Resonance Imaging, Magnetoencephalography, Models, Neurological, Neural Pathways, Rest, Spatio-Temporal Analysis