The Human Functional Brain Network Demonstrates Structural and Dynamical Resilience to Targeted Attack

Karen E Joyce, Satoru Hayasaka and Paul J Laurienti

PLOS Computational Biology, 2013, vol. 9, issue 1, 1-11

Abstract: In recent years, the field of network science has enabled researchers to represent the highly complex interactions in the brain in an approachable yet quantitative manner. One exciting finding since the advent of brain network research was that the brain network can withstand extensive damage, even to highly connected regions. However, these highly connected nodes may not be the most critical regions of the brain network, and it is unclear how the network dynamics are impacted by removal of these key nodes. This work seeks to further investigate the resilience of the human functional brain network. Network attack experiments were conducted on voxel-wise functional brain networks and region-of-interest (ROI) networks of 5 healthy volunteers. Networks were attacked at key nodes using several criteria for assessing node importance, and the impact on network structure and dynamics was evaluated. The findings presented here echo previous findings that the functional human brain network is highly resilient to targeted attacks, both in terms of network structure and dynamics. Author Summary: Why can the brain endure numerous micro-strokes with seemingly no detrimental impact, until one cataclysmal stroke hinders the ability to perform essential functions such as speech and mobility? Perhaps various small regions or foci of the brain are highly important to information transfer, and the loss of such highly central foci would be severely injurious to brain function. Identification of such foci, via modeling of the functional brain using network theory, could lead to important advances with regard to brain disease and stroke. In this work, we utilized functional brain networks constructed from human volunteers to study how removing particular regions of the brain impacts brain network structure and information transfer properties. We sought to determine whether a particular measure of region importance may be able to identify highly critical regions, and whether targeting highly critical regions would have a more detrimental impact than removing regions at random. We found that, while in general targeted removal has a larger impact on network structure and dynamics, the human brain network is comparatively resilient against both targeted and random removal.

Date: 2013
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pcbi00:1002885

DOI: 10.1371/journal.pcbi.1002885

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