Graph Theoretical Analysis Reveals: Women's Brains are Better Connected than Men's
Balazs Szalkai, Balint Varga, Vince Grolmusz

TL;DR
This study uses graph theory to analyze brain connectomes from MRI data, revealing that female brains are more well-connected and efficient than male brains based on several graph metrics.
Contribution
It applies advanced graph-theoretic analysis to large-scale human brain data, uncovering structural differences between male and female brains with novel quantitative measures.
Findings
Female connectomes have more edges than male connectomes.
Female brains exhibit better graph expansion properties.
Female brains have more spanning trees, indicating higher connectivity.
Abstract
Deep graph-theoretic ideas in the context with the graph of the World Wide Web led to the definition of Google's PageRank and the subsequent rise of the most-popular search engine to date. Brain graphs, or connectomes, are being widely explored today. We believe that non-trivial graph theoretic concepts, similarly as it happened in the case of the World Wide web, will lead to discoveries enlightening the structural and also the functional details of the animal and human brains. When scientists examine large networks of tens or hundreds of millions of vertices, only fast algorithms can be applied because of the size constraints. In the case of diffusion MRI-based structural human brain imaging, the effective vertex number of the connectomes, or brain graphs derived from the data is on the scale of several hundred today. That size facilitates applying strict mathematical graph algorithms…
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