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The Graph of Our Mind
Graph theory in the last two decades penetrated sociology, molecular biology, genetics, chemistry, computer engineering, and numerous other fields of science. One of the more recent areas of its applications is the study of the connections of the human brain. By the development of diffusion magnetic...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7998275/ https://www.ncbi.nlm.nih.gov/pubmed/33800527 http://dx.doi.org/10.3390/brainsci11030342 |
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author | Szalkai, Balázs Varga, Bálint Grolmusz, Vince |
author_facet | Szalkai, Balázs Varga, Bálint Grolmusz, Vince |
author_sort | Szalkai, Balázs |
collection | PubMed |
description | Graph theory in the last two decades penetrated sociology, molecular biology, genetics, chemistry, computer engineering, and numerous other fields of science. One of the more recent areas of its applications is the study of the connections of the human brain. By the development of diffusion magnetic resonance imaging (diffusion MRI), it is possible today to map the connections between the 1–1.5 cm [Formula: see text] regions of the gray matter of the human brain. These connections can be viewed as a graph. We have computed 1015-vertex graphs with thousands of edges for hundreds of human brains from one of the highest quality data sources: the Human Connectome Project. Here we analyze the male and female braingraphs graph-theoretically and show statistically significant differences in numerous parameters between the sexes: the female braingraphs are better expanders, have more edges, larger bipartition widths, and larger vertex cover than the braingraphs of the male subjects. These parameters are closely related to the quality measures of highly parallel computer interconnection networks: the better expanding property, the large bipartition width, and the large vertex cover characterize high-quality interconnection networks. We apply the data of 426 subjects and demonstrate the statistically significant (corrected) differences in 116 graph parameters between the sexes. |
format | Online Article Text |
id | pubmed-7998275 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-79982752021-03-28 The Graph of Our Mind Szalkai, Balázs Varga, Bálint Grolmusz, Vince Brain Sci Article Graph theory in the last two decades penetrated sociology, molecular biology, genetics, chemistry, computer engineering, and numerous other fields of science. One of the more recent areas of its applications is the study of the connections of the human brain. By the development of diffusion magnetic resonance imaging (diffusion MRI), it is possible today to map the connections between the 1–1.5 cm [Formula: see text] regions of the gray matter of the human brain. These connections can be viewed as a graph. We have computed 1015-vertex graphs with thousands of edges for hundreds of human brains from one of the highest quality data sources: the Human Connectome Project. Here we analyze the male and female braingraphs graph-theoretically and show statistically significant differences in numerous parameters between the sexes: the female braingraphs are better expanders, have more edges, larger bipartition widths, and larger vertex cover than the braingraphs of the male subjects. These parameters are closely related to the quality measures of highly parallel computer interconnection networks: the better expanding property, the large bipartition width, and the large vertex cover characterize high-quality interconnection networks. We apply the data of 426 subjects and demonstrate the statistically significant (corrected) differences in 116 graph parameters between the sexes. MDPI 2021-03-08 /pmc/articles/PMC7998275/ /pubmed/33800527 http://dx.doi.org/10.3390/brainsci11030342 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ). |
spellingShingle | Article Szalkai, Balázs Varga, Bálint Grolmusz, Vince The Graph of Our Mind |
title | The Graph of Our Mind |
title_full | The Graph of Our Mind |
title_fullStr | The Graph of Our Mind |
title_full_unstemmed | The Graph of Our Mind |
title_short | The Graph of Our Mind |
title_sort | graph of our mind |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7998275/ https://www.ncbi.nlm.nih.gov/pubmed/33800527 http://dx.doi.org/10.3390/brainsci11030342 |
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