Principles of inter-areal connections of the macaque cortex
| Autor: | Nikola Markov, Maria Magdolna Ercsey-Ravasz, Marie-Alice Gariel, Julien Vezoli, René Quilodran, Arnaud Falchier, Cyril Huissoud, Simon Clavagnier, Jerome Sallet, Pascale Giroud, Camille Lamy, Pierre Misery, Dominique Sappey-Marinier, Pascal Barone, Colette Dehay, Kenneth Knoblauch, Henry Kennedy, Zoltan Toroczkai |
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| Přispěvatelé: | Institut cellule souche et cerveau (U846 Inserm - UCBL1), Institut National de la Recherche Agronomique (INRA)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de la Santé et de la Recherche Médicale (INSERM), Department of Physics, University of Notre Dame [Indiana] (UND), Centre d'Etude et de Recherche Multimodal Et Pluridisciplinaire en imagerie du vivant (CERMEP - imagerie du vivant), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-CHU Grenoble-Hospices Civils de Lyon (HCL)-CHU Saint-Etienne-Université Jean Monnet [Saint-Étienne] (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA), Fourcaud-Trocmé, Nicolas, Université de Lyon-Université de Lyon-CHU Grenoble-Hospices Civils de Lyon (HCL)-CHU Saint-Etienne-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA) |
| Jazyk: | angličtina |
| Rok vydání: | 2010 |
| Předmět: | |
| Zdroj: | Cinquième conférence plénière française de Neurosciences Computationnelles, "Neurocomp'10" Cinquième conférence plénière française de Neurosciences Computationnelles, "Neurocomp'10", Aug 2010, Lyon, France HAL |
| Popis: | The operation of real world networks is largely determined by their weighted and spatial characteristics. Surprisingly little is known about these features in cortex. We generated in macaque, a consistent database of inter-areal connections comprising projection densities (link weights) and physical lengths. Contrary to previous assumptions, the cortical connection matrix is dense (66%) and therefore, not a small-world graph. Link weights are both highly specific and heterogeneous and we show that it is these properties that characterize the network. The embedding of this weighted network is governed by a distance rule that predicts both its binary features as well as the global and local communication efficiencies. Analysis of the efficiency of this weighted network suggests that small changes in global communication efficiency are offset by large changes in local efficiency. These findings indicate a weight-based hierarchical layering in cortical architecture and processing. |
| Databáze: | OpenAIRE |
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