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- W2025115943 startingPage "P03003" @default.
- W2025115943 abstract "It is now generally assumed that the heterogeneity of most networks in nature probably arises via preferential attachment of some sort. However, the origin of various other topological features, such as degree-degree correlations and related characteristics, is often not clear and attributed to specific functional requirements. We show how it is possible to analyse a very general scenario in which nodes gain or lose edges according to any (e.g., nonlinear) functions of local and/or global degree information. Applying our method to two rather different examples of brain development -- synaptic pruning in humans and the neural network of the worm C. Elegans -- we find that simple biologically motivated assumptions lead to very good agreement with experimental data. In particular, many nontrivial topological features of the worm's brain arise naturally at a critical point." @default.
- W2025115943 created "2016-06-24" @default.
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- W2025115943 date "2010-03-04" @default.
- W2025115943 modified "2023-10-17" @default.
- W2025115943 title "Evolving networks and the development of neural systems" @default.
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- W2025115943 doi "https://doi.org/10.1088/1742-5468/2010/03/p03003" @default.
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