K-shell decomposition reveals hierarchical cortical organization of the human brain
Nir Lahav, Baruch Ksherim, Eti Ben-Simon, Adi Maron-Katz, Reuven Cohen, and Shlomo Havlin

TL;DR
This study uses k-shell decomposition to analyze the hierarchical organization of the human brain's cortical network, revealing a structured, efficient, and functionally diverse connectivity pattern that may underpin consciousness.
Contribution
It applies k-shell decomposition to human cortical networks derived from MRI/DSI data, uncovering hierarchical layers and their potential roles in information flow and consciousness.
Findings
The cortex forms a connected giant component with no isolated nodes.
Hierarchical shells correspond to different functional roles.
The nucleus correlates with consciousness-related regions.
Abstract
In recent years numerous attempts to understand the human brain were undertaken from a network point of view. A network framework takes into account the relationships between the different parts of the system and enables to examine how global and complex functions might emerge from network topology. Previous work revealed that the human brain features 'small world' characteristics and that cortical hubs tend to interconnect among themselves. However, in order to fully understand the topological structure of hubs one needs to go beyond the properties of a specific hub and examine the various structural layers of the network. To address this topic further, we applied an analysis known in statistical physics and network theory as k-shell decomposition analysis. The analysis was applied on a human cortical network, derived from MRI\DSI data of six participants. Such analysis enables us to…
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