0000000000619897

AUTHOR

Giacopelli

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Graph-theoretical derivation of brain structural connectivity

2020

Brain connectivity at the single neuron level can provide fundamental insights into how information is integrated and propagated within and between brain regions. However, it is almost impossible to adequately study this problem experimentally and, despite intense efforts in the field, no mathematical description has been obtained so far. Here, we present a mathematical framework based on a graph-theoretical approach that, starting from experimental data obtained from a few small subsets of neurons, can quantitatively explain and predict the corresponding full network properties. This model also changes the paradigm with which large-scale model networks can be built, from using probabilisti…

0209 industrial biotechnologyTheoretical computer scienceComputer scienceNeuronal network02 engineering and technologyMECHANISMSCENTRALITY020901 industrial engineering & automationSettore MAT/05 - Analisi MatematicaNeuronal networksConnectome0202 electrical engineering electronic engineering information engineeringINDEXComputer Science::DatabasesRandom graphsSettore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniSettore INF/01 - InformaticaQuantitative Biology::Neurons and CognitionApplied MathematicsProbabilistic logicExperimental data020206 networking & telecommunicationsComputational MathematicsSYNCHRONIZATIONSIMULATIONGraph (abstract data type)Applied Mathematics and Computation
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