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… 
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10 Citations

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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.
The frequent subgraphs of the connectome of the human brain
TLDR
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.
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TLDR
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TLDR
Based on the data of the NIH-funded Human Connectome Project, structural connectomes of 426 human subjects are computed in five different resolutions of 83, 129, 234, 463 and 1015 nodes and several edge weights in anatomically annotated GraphML format that facilitates better further processing and visualization.
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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.
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TLDR
This work uses the braingraphs, computed from the imaging data of the Human Connectome Project’s 414 subjects, each with 463 anatomically identified nodes, to identify frequent neighbor-sets of the hippocampus, which may influence numerous psychological parameters, including intelligence-related ones.
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TLDR
This work analyzes the pairwise correlations between 717 psychological-, anatomical- and structural connectome–properties, based also on the Human Connectome Project’s 500-subject dataset, and applies the maximum spanning tree method.
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References

SHOWING 1-10 OF 47 REFERENCES
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.
The frequent subgraphs of the connectome of the human brain
TLDR
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.
Sex differences in the structural connectome of the human brain
TLDR
Overall, the results suggest that male brains are structured to facilitate connectivity between perception and coordinated action, whereas female brains are designed to facilitate communication between analytical and intuitive processing modes.
Graph Theoretical Analysis Reveals: Women’s Brains Are Better Connected than Men’s
TLDR
It is shown that the average female connectome has more edges, is a better expander graph, has larger minimal bisection width, and has more spanning trees than the average male connectome, which shows that the female brain has better graph theoretical properties, in a sense, than the brain of males.
The braingraph.org database of high resolution structural connectomes and the brain graph tools
TLDR
Based on the data of the NIH-funded Human Connectome Project, structural connectomes of 426 human subjects are computed in five different resolutions of 83, 129, 234, 463 and 1015 nodes and several edge weights in anatomically annotated GraphML format that facilitates better further processing and visualization.
Comparative connectomics: Mapping the inter-individual variability of connections within the regions of the human brain
The hypothesis of neuronal interconnectivity as a function of brain size—a general organization principle of the human connectome
TLDR
The hypothesis of neuronal interconnectivity as a function of brain size might account for shorter and more symmetrical interhemispheric transfer times in women and for empirical evidence that visual and auditory processing are stronger lateralized in men is investigated.
The Budapest Reference Connectome Server v2.0
Normal neuroanatomical variation in the human brain: an MRI-volumetric study.
TLDR
High-resolution magnetic resonance imaging was used to measure regional brain volumes in 46 normal, right-handed adults between the ages of 22-49 years, and results have implications for understanding whether or not certain sectors of the brain have shown relative expansion over the course of hominid and hominoid evolution.
Sex differences in the human connectome: 4-Tesla high angular resolution diffusion imaging (HARDI) tractography in 234 young adult twins
TLDR
A novel Hough transform method was applied to extract fiber tracts throughout the entire brain, based on fields of constant solid angle orientation distribution functions, and found significant sex differences in the proportions of fibers connecting contralateral superior frontal cortices.
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