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

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Abstract

Connections of the living human brain, on a macroscopic scale, can be mapped by a diffusion MR imaging based workflow. Since the same anatomic regions can be corresponded between distinct brains, one can compare the presence or the absence of the edges, connecting the very same two anatomic regions, among multiple cortices. Previously, we have constructed the consensus braingraphs on 1015 vertices first in five, then in 96 subjects in the Budapest Reference Connectome Server v1.0 and v2.0, respectively. Here we report the construction of the version 3.0 of the server, generating the common edges of the connectomes of variously parameterizable subsets of the 1015-vertex connectomes of 477 subjects of the Human Connectome Project’s 500-subject release. The consensus connectomes are downloadable in CSV and GraphML formats, and they are also visualized on the server’s page. The consensus connectomes of the server can be considered as the “average, healthy” human connectome since all of their connections are present in at least k subjects, where the default value of \(k=209\), but it can also be modified freely at the web server. The webserver is available at http://connectome.pitgroup.org.

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Acknowledgments

Data were provided in part by the Human Connectome Project, WU-Minn Consortium (Principal Investigators: David Van Essen and Kamil Ugurbil; 1U54MH091657) funded by the 16 NIH Institutes and Centers that support the NIH Blueprint for Neuroscience Research; and by the McDonnell Center for Systems Neuroscience at Washington University.

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The authors declare no conflicts of interest.

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Correspondence to Vince Grolmusz.

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Balázs Szalkai, Csaba Kerepesi and Bálint Varga are joint first authors.

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Szalkai, B., Kerepesi, C., Varga, B. et al. Parameterizable consensus connectomes from the Human Connectome Project: the Budapest Reference Connectome Server v3.0. Cogn Neurodyn 11, 113–116 (2017). https://doi.org/10.1007/s11571-016-9407-z

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  • DOI: https://doi.org/10.1007/s11571-016-9407-z

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