Simulation of Robustness against Lesions of Cortical Networks - Quantitative Biology Neurons and CognitionReport as inadecuate




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Abstract: Structure entails function and thus a structural description of the brainwill help to understand its function and may provide insights into manyproperties of brain systems, from their robustness and recovery from damage, totheir dynamics and even their evolution. Advances in the analysis of complexnetworks provide useful new approaches to understanding structural andfunctional properties of brain networks. Structural properties of networksrecently described allow their characterization as small-world, randomexponential and scale-free. They complement the set of other properties thathave been explored in the context of brain connectivity, such as topology,hodology, clustering, and hierarchical organization. Here we apply new networkanalysis methods to cortical inter-areal connectivity networks for the cat andmacaque brains. We compare these corticocortical fibre networks to benchmarkrewired, small-world, scale-free and random networks, using two analysisstrategies, in which we measure the effects of the removal of nodes andconnections on the structural properties of the cortical networks. The brainnetworks structural decay is in most respects similar to that of scale-freenetworks. The results implicate highly connected hub-nodes and bottleneckconnections as structural basis for some of the conditional robustness of brainsystems. This informs the understanding of the development of brain networksconnectivity.



Author: Marcus Kaiser, Robert Martin, Peter Andras, Malcolm P. Young

Source: https://arxiv.org/



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