Literature DB >> 29067135

The braingraph.org database of high resolution structural connectomes and the brain graph tools.

Csaba Kerepesi1,2, Balázs Szalkai1, Bálint Varga1, Vince Grolmusz1,3.   

Abstract

Based on the data of the NIH-funded Human Connectome Project, we have computed structural connectomes of 426 human subjects in five different resolutions of 83, 129, 234, 463 and 1015 nodes and several edge weights. The graphs are given in anatomically annotated GraphML format that facilitates better further processing and visualization. For 96 subjects, the anatomically classified sub-graphs can also be accessed, formed from the vertices corresponding to distinct lobes or even smaller regions of interests of the brain. For example, one can easily download and study the connectomes, restricted to the frontal lobes or just to the left precuneus of 96 subjects using the data. Partially directed connectomes of 423 subjects are also available for download. We also present a GitHub-deposited set of tools, called the Brain Graph Tools, for several processing tasks of the connectomes on the site http://braingraph.org.

Entities:  

Keywords:  Brain connections; Braingraph; Connectome; Human Connectome Project

Year:  2017        PMID: 29067135      PMCID: PMC5637719          DOI: 10.1007/s11571-017-9445-1

Source DB:  PubMed          Journal:  Cogn Neurodyn        ISSN: 1871-4080            Impact factor:   5.082


  11 in total

1.  An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest.

Authors:  Rahul S Desikan; Florent Ségonne; Bruce Fischl; Brian T Quinn; Bradford C Dickerson; Deborah Blacker; Randy L Buckner; Anders M Dale; R Paul Maguire; Bradley T Hyman; Marilyn S Albert; Ronald J Killiany
Journal:  Neuroimage       Date:  2006-03-10       Impact factor: 6.556

2.  Microstructural and physiological features of tissues elucidated by quantitative-diffusion-tensor MRI.

Authors:  P J Basser; C Pierpaoli
Journal:  J Magn Reson B       Date:  1996-06

3.  Brain size bias compensated graph-theoretical parameters are also better in women's structural connectomes.

Authors:  Balázs Szalkai; Bálint Varga; Vince Grolmusz
Journal:  Brain Imaging Behav       Date:  2018-06       Impact factor: 3.978

Review 4.  FreeSurfer.

Authors:  Bruce Fischl
Journal:  Neuroimage       Date:  2012-01-10       Impact factor: 6.556

5.  Comparative connectomics: Mapping the inter-individual variability of connections within the regions of the human brain.

Authors:  Csaba Kerepesi; Balázs Szalkai; Bálint Varga; Vince Grolmusz
Journal:  Neurosci Lett       Date:  2017-10-06       Impact factor: 3.046

6.  Parameterizable consensus connectomes from the Human Connectome Project: the Budapest Reference Connectome Server v3.0.

Authors:  Balázs Szalkai; Csaba Kerepesi; Bálint Varga; Vince Grolmusz
Journal:  Cogn Neurodyn       Date:  2016-09-15       Impact factor: 5.082

7.  The Human Connectome Project and beyond: initial applications of 300 mT/m gradients.

Authors:  Jennifer A McNab; Brian L Edlow; Thomas Witzel; Susie Y Huang; Himanshu Bhat; Keith Heberlein; Thorsten Feiweier; Kecheng Liu; Boris Keil; Julien Cohen-Adad; M Dylan Tisdall; Rebecca D Folkerth; Hannah C Kinney; Lawrence L Wald
Journal:  Neuroimage       Date:  2013-05-24       Impact factor: 6.556

8.  The connectome mapper: an open-source processing pipeline to map connectomes with MRI.

Authors:  Alessandro Daducci; Stephan Gerhard; Alessandra Griffa; Alia Lemkaddem; Leila Cammoun; Xavier Gigandet; Reto Meuli; Patric Hagmann; Jean-Philippe Thiran
Journal:  PLoS One       Date:  2012-12-18       Impact factor: 3.240

9.  Graph Theoretical Analysis Reveals: Women's Brains Are Better Connected than Men's.

Authors:  Balázs Szalkai; Bálint Varga; Vince Grolmusz
Journal:  PLoS One       Date:  2015-07-01       Impact factor: 3.240

10.  How to Direct the Edges of the Connectomes: Dynamics of the Consensus Connectomes and the Development of the Connections in the Human Brain.

Authors:  Csaba Kerepesi; Balázs Szalkai; Bálint Varga; Vince Grolmusz
Journal:  PLoS One       Date:  2016-06-30       Impact factor: 3.240

View more
  8 in total

1.  The frequent subgraphs of the connectome of the human brain.

Authors:  Máté Fellner; Bálint Varga; Vince Grolmusz
Journal:  Cogn Neurodyn       Date:  2019-05-06       Impact factor: 5.082

2.  Comparing advanced graph-theoretical parameters of the connectomes of the lobes of the human brain.

Authors:  Balázs Szalkai; Bálint Varga; Vince Grolmusz
Journal:  Cogn Neurodyn       Date:  2018-10-06       Impact factor: 5.082

3.  The Frequent Network Neighborhood Mapping of the human hippocampus shows much more frequent neighbor sets in males than in females.

Authors:  Máté Fellner; Bálint Varga; Vince Grolmusz
Journal:  PLoS One       Date:  2020-01-28       Impact factor: 3.240

4.  Braiding Braak and Braak: Staging patterns and model selection in network neurodegeneration.

Authors:  Prama Putra; Travis B Thompson; Pavanjit Chaggar; Alain Goriely
Journal:  Netw Neurosci       Date:  2021-11-30

5.  The braingraph.org database with more than 1000 robust human connectomes in five resolutions.

Authors:  Bálint Varga; Vince Grolmusz
Journal:  Cogn Neurodyn       Date:  2021-03-12       Impact factor: 5.082

6.  Identifying super-feminine, super-masculine and sex-defining connections in the human braingraph.

Authors:  László Keresztes; Evelin Szögi; Bálint Varga; Vince Grolmusz
Journal:  Cogn Neurodyn       Date:  2021-07-15       Impact factor: 5.082

7.  Introducing and applying Newtonian blurring: an augmented dataset of 126,000 human connectomes at braingraph.org.

Authors:  László Keresztes; Evelin Szögi; Bálint Varga; Vince Grolmusz
Journal:  Sci Rep       Date:  2022-02-23       Impact factor: 4.379

8.  Nonlocal models in the analysis of brain neurodegenerative protein dynamics with application to Alzheimer's disease.

Authors:  Swadesh Pal; Roderick Melnik
Journal:  Sci Rep       Date:  2022-05-05       Impact factor: 4.996

  8 in total

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