Abstract : Small-world networks provide an appealing description of cortical architecture owing to their capacity for integration and segregation combined with an economy of connectivity. Previous reports of low-density interareal graphs and apparent small-world properties are challenged by data that reveal high-density cortical graphs in which economy of connections is achieved by weight heterogeneity and distance-weight correlations. These properties define a model that predicts many binary and weighted features of the cortical network including a core-periphery, a typical feature of self-organizing information processing systems. Feedback and feedforward pathways between areas exhibit a dual counterstream organization, and their integration into local circuits constrains cortical computation. Here, we propose a bow-tie representation of interareal architecture derived from the hierarchical laminar weights of pathways between the high-efficiency dense core and periphery.
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Contributor : Henry Kennedy
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Nikola Markov, Mária Ercsey-Ravasz, David van Essen, Kenneth Knoblauch, Zoltán Toroczkai, et al.. Cortical high-density counterstream architectures.. Science, American Association for the Advancement of Science, 2013, 342 (6158), pp.1238406. ⟨10.1126/science.1238406⟩. ⟨inserm-00879494⟩
