78 research outputs found
The Advantage is at the Ladies: Brain Size Bias-Compensated Graph-Theoretical Parameters are Also Better in Women's Connectomes
In our previous study we have shown that the female connectomes have
significantly better, deep graph-theoretical 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 size- and 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 that all the brains in the
female set are larger than all the brains in the male set. For the sets, we
have computed the corresponding braingraphs and computed numerous
graph-theoretical parameters. We have found that (i) the small male brains lack
the better connectivity advantages shown in our previous study for female
brains in general; (ii) in numerous parameters, the connectomes computed from
the large-brain females, still have the significant, deep connectivity
advantages, demonstrated in our previous study.Comment: arXiv admin note: substantial text overlap with arXiv:1501.0072
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
resonance imaging (diffusion MRI), it is possible today to map the connections
between the 1-1.5 cm regions of the gray matter of the human brain. These
connections can be viewed as a graph: the vertices are the anatomically
identified regions of the gray matter, and two vertices are connected by an
edge if the diffusion MRI-based workflow finds neuronal fiber tracts between
these areas. This way we can compute 1015-vertex graphs with tens of thousands
of edges. In a previous work, we have analyzed the male and female braingraphs
graph-theoretically, and we have found 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. Our previous study has applied the
data of 96 subjects; here we present a much larger study of 426 subjects. Our
data source is an NIH-founded project, the "Human Connectome Project (HCP)"
public data release. As a service to the community, we have also made all of
the braingraphs computed by us from the HCP data publicly available at the
\url{http://braingraph.org} for independent validation and further
investigations.Comment: arXiv admin note: substantial text overlap with arXiv:1512.01156,
arXiv:1501.0072
The Frequent Complete Subgraphs in the Human Connectome
While it is still not possible to describe the neural-level connections of
the human brain, we can map the human connectome with several hundred vertices,
by the application of diffusion-MRI based techniques. In these graphs, the
nodes correspond to anatomically identified gray matter areas of the brain,
while the edges correspond to the axonal fibers, connecting these areas. In our
previous contributions, we have described numerous graph-theoretical phenomena
of the human connectomes. Here we map the frequent complete subgraphs of the
human brain networks: in these subgraphs, every pair of vertices is connected
by an edge. We also examine sex differences in the results. The mapping of the
frequent subgraphs 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. We list here the
frequent complete subgraphs of the human braingraphs of 414 subjects, each with
463 nodes, with a frequency threshold of 80%, and identify 812 complete
subgraphs, which are more frequent in male and 224 complete subgraphs, which
are more frequent in female connectomes
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