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  • 标题:Model of brain activation predicts the neural collective influence map of the brain
  • 本地全文:下载
  • 作者:Flaviano Morone ; Kevin Roth ; Byungjoon Min
  • 期刊名称:Proceedings of the National Academy of Sciences
  • 印刷版ISSN:0027-8424
  • 电子版ISSN:1091-6490
  • 出版年度:2017
  • 卷号:114
  • 期号:15
  • 页码:3849-3854
  • DOI:10.1073/pnas.1620808114
  • 语种:English
  • 出版社:The National Academy of Sciences of the United States of America
  • 摘要:Efficient complex systems have a modular structure, but modularity does not guarantee robustness, because efficiency also requires an ingenious interplay of the interacting modular components. The human brain is the elemental paradigm of an efficient robust modular system interconnected as a network of networks (NoN). Understanding the emergence of robustness in such modular architectures from the interconnections of its parts is a longstanding challenge that has concerned many scientists. Current models of dependencies in NoN inspired by the power grid express interactions among modules with fragile couplings that amplify even small shocks, thus preventing functionality. Therefore, we introduce a model of NoN to shape the pattern of brain activations to form a modular environment that is robust. The model predicts the map of neural collective influencers (NCIs) in the brain, through the optimization of the influence of the minimal set of essential nodes responsible for broadcasting information to the whole-brain NoN. Our results suggest intervention protocols to control brain activity by targeting influential neural nodes predicted by network theory.
  • 关键词:brain ; collective influence ; robustness ; network of networks ; optimal percolation
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