The CONNECT project: Combining macro- and micro-structure
In recent years, diffusion MRI has become an extremely important tool for studying the morphology of living brain tissue, as it provides unique insights into both its macrostructure and microstructure. Recent applications of diffusion MRI aimed to characterize the structural connectome using tractog...
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Veröffentlicht in: | NeuroImage (Orlando, Fla.) Fla.), 2013-10, Vol.80, p.273-282 |
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Sprache: | eng |
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Zusammenfassung: | In recent years, diffusion MRI has become an extremely important tool for studying the morphology of living brain tissue, as it provides unique insights into both its macrostructure and microstructure. Recent applications of diffusion MRI aimed to characterize the structural connectome using tractography to infer connectivity between brain regions. In parallel to the development of tractography, additional diffusion MRI based frameworks (CHARMED, AxCaliber, ActiveAx) were developed enabling the extraction of a multitude of micro-structural parameters (axon diameter distribution, mean axonal diameter and axonal density). This unique insight into both tissue microstructure and connectivity has enormous potential value in understanding the structure and organization of the brain as well as providing unique insights to abnormalities that underpin disease states.
The CONNECT (Consortium Of Neuroimagers for the Non-invasive Exploration of brain Connectivity and Tracts) project aimed to combine tractography and micro-structural measures of the living human brain in order to obtain a better estimate of the connectome, while also striving to extend validation of these measurements. This paper summarizes the project and describes the perspective of using micro-structural measures to study the connectome.
•Recently developed diffusion MRI methods quantify white matter micro-structure.•Combination of tractography and micro-structural measures define better of the connectome.•CONNECT established the first in-vivo atlas of brain micro-structural features. |
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ISSN: | 1053-8119 1095-9572 |
DOI: | 10.1016/j.neuroimage.2013.05.055 |