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Human brain structural connectivity matrices-ready for modelling

A. Škoch, B. Rehák Bučková, J. Mareš, J. Tintěra, P. Sanda, L. Jajcay, J. Horáček, F. Španiel, J. Hlinka

. 2022 ; 9 (1) : 486. [pub] 20220809

Language English Country England, Great Britain

Document type Dataset, Journal Article

Persistent link   https://www.medvik.cz/link/bmc22024878

Grant support
DRO 2021 National Institute of Mental Health - NIMH IN 00023752 Ministerstvo Zdravotnictví Ceské Republiky (Ministry of Health of the Czech Republic)
DRO 2021 National Institute of Mental Health - NIMH IN 00023752 Ministerstvo Zdravotnictví Ceské Republiky (Ministry of Health of the Czech Republic)
DRO 2021 National Institute of Mental Health - NIMH IN 00023752 Ministerstvo Zdravotnictví Ceské Republiky (Ministry of Health of the Czech Republic)
DRO 2021 National Institute of Mental Health - NIMH IN 00023752 Ministerstvo Zdravotnictví Ceské Republiky (Ministry of Health of the Czech Republic)
DRO 2021 National Institute of Mental Health - NIMH IN 00023752 Ministerstvo Zdravotnictví Ceské Republiky (Ministry of Health of the Czech Republic)
DRO 2021 National Institute of Mental Health - NIMH IN 00023752 Ministerstvo Zdravotnictví Ceské Republiky (Ministry of Health of the Czech Republic)
DRO 2021 National Institute of Mental Health - NIMH IN 00023752 Ministerstvo Zdravotnictví Ceské Republiky (Ministry of Health of the Czech Republic)
NU21-08-00432 Agentura Pro Zdravotnický Výzkum České Republiky (Czech Health Research Council)
NU21-08-00432 Agentura Pro Zdravotnický Výzkum České Republiky (Czech Health Research Council)
NU21-08-00432 Agentura Pro Zdravotnický Výzkum České Republiky (Czech Health Research Council)
NU21-08-00432 Agentura Pro Zdravotnický Výzkum České Republiky (Czech Health Research Council)
Strategy AV21 Akademie Věd České Republiky (Academy of Sciences of the Czech Republic)
Strategy AV21 Akademie Věd České Republiky (Academy of Sciences of the Czech Republic)
Strategy AV21 Akademie Věd České Republiky (Academy of Sciences of the Czech Republic)
Strategy AV21 Akademie Věd České Republiky (Academy of Sciences of the Czech Republic)
Strategy AV21 Akademie Věd České Republiky (Academy of Sciences of the Czech Republic)
21-32608S Grantová Agentura České Republiky (Grant Agency of the Czech Republic)
21-32608S Grantová Agentura České Republiky (Grant Agency of the Czech Republic)
SGS20/172/OHK3/3T/13 České Vysoké Učení Technické v Praze (Czech Technical University in Prague)

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.

References provided by Crossref.org

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