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The missing role of gray matter in studying brain controllability

MPS-Authors
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Kumar,  VJ
Max Planck Institute for Biological Cybernetics, Max Planck Society;
Department High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Li,  M
Max Planck Institute for Biological Cybernetics, Max Planck Society;
Department High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Walter,  M
Max Planck Institute for Biological Cybernetics, Max Planck Society;
Department High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Citation

Jamalabadi, H., Zuberer, A., Kumar, V., Li, M., Alizadeh, S., Moradi, A., et al. (submitted). The missing role of gray matter in studying brain controllability.


Cite as: https://hdl.handle.net/21.11116/0000-0006-B9A2-2
Abstract
Brain controllability properties are normally derived from the white matter fiber tracts in which the neural substrate of the actual energy consumption, namely the gray matter, has been widely ignored. Here, we study the relationship between gray matter volume of regions across the whole cortex and their respective control property derived from the structural architecture of the white matter fiber tracts. The data suggests that the ability of white fiber tracts to exhibit control at specific nodes not only depends on the connection strength of the structural connectome but additionally strongly depends on gray matter volume at the host nodes. Our data indicates that connectivity strength and gray matter volume interact with respect to the brain’s control properties, such that gray matter exerts the great impact in regions with high structural connectivity. Disentangling effects of the regional gray matter volume and connectivity strength, we found that frontal and sensory areas play crucial roles in controllability. Together these results suggest that structural and regional properties of the white matter and gray matter provide complementary information in studying the control properties of the intrinsic structural and functional architectural of the brain.