Human brain structural connectivity matrices–ready for modelling

The human brain represents a complex computational system, the function and structure of which may be measured using various neuroimaging techniques focusing on separate properties of the brain tissue and activity. We capture the organization of white matter fibers acquired by diffusion-weighted ima...

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Bibliographic Details
Published inScientific data Vol. 9; no. 1; pp. 486 - 9
Main Authors Škoch, Antonín, Rehák Bučková, Barbora, Mareš, Jan, Tintěra, Jaroslav, Sanda, Pavel, Jajcay, Lucia, Horáček, Jiří, Španiel, Filip, Hlinka, Jaroslav
Format Journal Article
LanguageEnglish
Published London Nature Publishing Group UK 09.08.2022
Nature Publishing Group
Nature Portfolio
Subjects
631/378/116/1925
692/617
692/698/1688/64
Brain
Computational neuroscience
Data Descriptor
Humanities and Social Sciences
Magnetic resonance imaging
multidisciplinary
Neural networks
Neuroimaging
Quality control
Science
Science (multidisciplinary)
Structure-function relationships
Substantia alba
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Summary:The human brain represents a complex computational system, the function and structure of which may be measured using various neuroimaging techniques focusing on separate properties of the brain tissue and activity. We capture the organization of white matter fibers acquired by diffusion-weighted imaging using probabilistic diffusion tractography. By segmenting the results of tractography into larger anatomical units, it is possible to draw inferences about the structural relationships between these parts of the system. This pipeline results in a structural connectivity matrix, which contains an estimate of connection strength among all regions. However, raw data processing is complex, computationally intensive, and requires expert quality control, which may be discouraging for researchers with less experience in the field. We thus provide brain structural connectivity matrices in a form ready for modelling and analysis and thus usable by a wide community of scientists. The presented dataset contains brain structural connectivity matrices together with the underlying raw diffusion and structural data, as well as basic demographic data of 88 healthy subjects. Measurement(s) Diffusion Weighted Imaging Technology Type(s) Magnetic Resonance Imaging Sample Characteristic - Organism Homo sapiens Sample Characteristic - Location Czech Republic
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ISSN:2052-4463
2052-4463
DOI:10.1038/s41597-022-01596-9