The Human Functional Brain Network Demonstrates Structural and Dynamical Resilience to Targeted Attack
Author(s) -
Karen E. Joyce,
Satoru Hayasaka,
Paul J. Laurienti
Publication year - 2013
Publication title -
plos computational biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.628
H-Index - 182
eISSN - 1553-7358
pISSN - 1553-734X
DOI - 10.1371/journal.pcbi.1002885
Subject(s) - resilience (materials science) , computer science , complex network , human brain , centrality , network science , network dynamics , dynamic network analysis , node (physics) , betweenness centrality , key (lock) , network analysis , neuroscience , computer network , computer security , biology , physics , mathematics , discrete mathematics , combinatorics , world wide web , thermodynamics , quantum mechanics
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.
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom