Abstract
Deep, classical graph-theoretical parameters, like the size of the minimum vertex cover, the chromatic number, or the eigengap of the adjacency matrix of the graph were studied widely by mathematicians in the last century. Most researchers today study much simpler parameters of braingraphs or connectomes which were defined in the last twenty years for enormous networks—like the graph of the World Wide Web—with hundreds of millions of nodes. Since the connectomes, describing the connections of the human brain, typically contain several hundred vertices today, one can compute and analyze the much deeper, harder-to-compute classical graph parameters for these, relatively small graphs of the brain. This deeper approach has proven to be very successful in the comparison of the connectomes of the sexes in our earlier works: we have shown that graph parameters, deeply characterizing the graph connectivity are significantly better in women’s connectomes than in men’s. In the present contribution we compare numerous graph parameters in the three largest lobes—frontal, parietal, temporal—and in both hemispheres of the human brain. We apply the diffusion weighted imaging data of 423 subjects of the NIH-funded Human Connectome Project, and present some findings, never described before, including that the right parietal lobe contains significantly more edges, has higher average degree, density, larger minimum vertex cover and Hoffman bound than the left parietal lobe. Similar advantages in the deep graph connectivity properties are held for the left frontal versus the right frontal and the right temporal versus the left temporal lobes.
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Acknowledgements
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. The authors declare no conflicts of interest. VG was partially funded the NKFI-126472 grant of the National Research, Development and Innovation Office of Hungary. VG and BV were partially supported by the VEKOP-2.3.2-16-2017-00014 program, supported by the European Union and the State of Hungary, co-financed by the European Regional Development Fund. BV was supported in part by the EFOP-3.6.3-VEKOP-16-2017-00002 grant, funded by the European Union, co-financed by the European Social Fund.
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Szalkai, B., Varga, B. & Grolmusz, V. Comparing advanced graph-theoretical parameters of the connectomes of the lobes of the human brain. Cogn Neurodyn 12, 549–559 (2018). https://doi.org/10.1007/s11571-018-9508-y
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DOI: https://doi.org/10.1007/s11571-018-9508-y