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

@article{Szalkai2017BrainSB,
  title={Brain size bias compensated graph-theoretical parameters are also better in women’s structural connectomes},
  author={Bal{\'a}zs Szalkai and B{\'a}lint Varga and Vince Grolmusz},
  journal={Brain Imaging and Behavior},
  year={2017},
  volume={12},
  pages={663-673}
}
In our previous study it was shown that the female connectomes have significantly better, deep graphtheoretical parameters, related to superior “connectivity”, than the connectome of the males. Since the average female brain is smaller than the average male brain, one cannot rule out that the significant advantages are due to the sizeand not to the sex-differences in the data. To filter out the possible brain-volume related artifacts, we have chosen 36 small male and 36 large female brains such… Expand
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TLDR
Comparing numerous graph parameters in the three largest lobes—frontal, parietal, temporal—and in both hemispheres of the human brain is compared, and some findings are presented, 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 leftParietal lobe. Expand
The frequent subgraphs of the connectome of the human brain
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The present contribution describes the frequent connected subgraphs of at most six edges in the human brain, and analyzes these frequent graphs and examines sex differences in these graphs: numerous connected sub graphs that are more frequent in female or male connectomes. Expand
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TLDR
The mapping of the frequent complete subgraphs of the human brain networks gives robust substructures in the graph: if a subgraph is present in the 80% of the graphs, then, most probably, it could not be an artifact of the measurement or the data processing workflow. Expand
The braingraph.org database of high resolution structural connectomes and the brain graph tools
TLDR
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TLDR
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TLDR
The new method of the Frequent Network Neighborhood Mapping for the connectome, which serves as a robust identification of the neighborhoods of given vertices of special interest in the graph, is introduced and strong statistical asymmetries between the connectomes of the sexes are discovered. Expand
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Comparing advanced graph-theoretical parameters of the connectomes of the lobes of the human brain
TLDR
Comparing numerous graph parameters in the three largest lobes—frontal, parietal, temporal—and in both hemispheres of the human brain is compared, and some findings are presented, 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 leftParietal lobe. Expand
The frequent subgraphs of the connectome of the human brain
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The present contribution describes the frequent connected subgraphs of at most six edges in the human brain, and analyzes these frequent graphs and examines sex differences in these graphs: numerous connected sub graphs that are more frequent in female or male connectomes. Expand
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