: Microstructural imaging and connectomics are two research areas that hold great potential for investigating brain structure and function. Combining these two approaches can lead to a better and more complete characterization of the brain as a network. The aim of this work is characterizing the connectome from a novel perspective using the myelination measure given by the g-ratio. The g-ratio is the ratio of the inner to the outer diameters of a myelinated axon, whose aggregated value can now be estimated in vivo using MRI. In two different datasets of healthy subjects, we reconstructed the structural connectome and then used the g-ratio estimated from diffusion and magnetization transfer data to characterize the network structure. Significant characteristics of g-ratio weighted graphs emerged. First, the g-ratio distribution across the edges of the graph did not show the power-law distribution observed using the number of streamlines as a weight. Second, connections involving regions related to motor and sensory functions were the highest in myelin content. We also observed significant differences in terms of the hub structure and the rich-club organization suggesting that connections involving hub regions present higher myelination than peripheral connections. Taken together, these findings offer a characterization of g-ratio distribution across the connectome in healthy subjects and lay the foundations for further investigating plasticity and pathology using a similar approach.

Introducing axonal myelination in connectomics: a preliminary analysis of g-ratio distribution in healthy subjects / Mancini, Matteo; Giulietti, Giovanni; Dowell, Nicholas; Spanò, Barbara; Harrison, Neil; Bozzali, Marco; Cercignani, Mara. - In: NEUROIMAGE. - ISSN 1053-8119. - 182:(2018), pp. 351-359. [10.1016/j.neuroimage.2017.09.018]

Introducing axonal myelination in connectomics: a preliminary analysis of g-ratio distribution in healthy subjects

Giulietti, Giovanni;
2018

Abstract

: Microstructural imaging and connectomics are two research areas that hold great potential for investigating brain structure and function. Combining these two approaches can lead to a better and more complete characterization of the brain as a network. The aim of this work is characterizing the connectome from a novel perspective using the myelination measure given by the g-ratio. The g-ratio is the ratio of the inner to the outer diameters of a myelinated axon, whose aggregated value can now be estimated in vivo using MRI. In two different datasets of healthy subjects, we reconstructed the structural connectome and then used the g-ratio estimated from diffusion and magnetization transfer data to characterize the network structure. Significant characteristics of g-ratio weighted graphs emerged. First, the g-ratio distribution across the edges of the graph did not show the power-law distribution observed using the number of streamlines as a weight. Second, connections involving regions related to motor and sensory functions were the highest in myelin content. We also observed significant differences in terms of the hub structure and the rich-club organization suggesting that connections involving hub regions present higher myelination than peripheral connections. Taken together, these findings offer a characterization of g-ratio distribution across the connectome in healthy subjects and lay the foundations for further investigating plasticity and pathology using a similar approach.
2018
connectome; diffusion weighted imaging; graph theory; microstructure; myelin; structural connectivity; g-ratio
01 Pubblicazione su rivista::01a Articolo in rivista
Introducing axonal myelination in connectomics: a preliminary analysis of g-ratio distribution in healthy subjects / Mancini, Matteo; Giulietti, Giovanni; Dowell, Nicholas; Spanò, Barbara; Harrison, Neil; Bozzali, Marco; Cercignani, Mara. - In: NEUROIMAGE. - ISSN 1053-8119. - 182:(2018), pp. 351-359. [10.1016/j.neuroimage.2017.09.018]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1670331
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