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Topological impact of negative links on the stability of resting-state brain network

Majid Saberi, Reza Khosrowabadi, Ali Khatibi, Bratislav Mišić, Gholamreza Jafari

2021Scientific Reports50 citationsDOIOpen Access PDF

Abstract

Stability is a physical attribute that stands opposite the change. However, it is still unclear how the arrangement of links called topology affects network stability. In this study, we tackled this issue in the resting-state brain network using structural balance. Structural balance theory employs the quality of triadic associations between signed links to determine the network stability. In this study, we showed that negative links of the resting-state network make hubs to reduce balance-energy and push the network into a more stable state compared to null-networks with trivial topologies. In this regard, we created a global measure entitled 'tendency to make hub' to assess the hubness of the network. Besides, we revealed nodal degrees of negative links have an exponential distribution that confirms the existence of negative hubs. Our findings indicate that the arrangement of negative links plays an important role in the balance (stability) of the resting-state brain network.

Topics & Concepts

Resting state fMRIStability (learning theory)Topology (electrical circuits)Network topologyState (computer science)Computer scienceBalance (ability)Functional connectivityNull modelNull (SQL)MathematicsComputer networkNeurosciencePsychologyData miningAlgorithmMachine learningCombinatoricsFunctional Brain Connectivity StudiesNeural dynamics and brain functionNonlinear Dynamics and Pattern Formation
Topological impact of negative links on the stability of resting-state brain network | Litcius