Networks of living neurons exhibit an avalanche mode of activity, experimentally found in organotypic cultures. Moreover, experimental studies of morphology indicate that neurons develop a network of small-world-like connections, with the possibility of a very high connectivity degree. Here we study a recent model based on self-organized criticality, which consists of an electrical network with threshold firing and activity-dependent synapse strengths. We study the model on a scale-free network, the Apollonian network. The system exhibits an avalanche activity with a power law distribution of sizes and durations. The analysis of the power spectra of the electrical signal reproduces very robustly the power law behavior with the exponent 0.8, experimentally measured in electroencephalogram spectra. The exponents are found to be quite stable with respect to initial configurations and strength of plastic remodeling, indicating that universality holds for a wide class of neural network models.

Activity-dependent neural network model on scale-free networks

DE ARCANGELIS, Lucilla;
2007

Abstract

Networks of living neurons exhibit an avalanche mode of activity, experimentally found in organotypic cultures. Moreover, experimental studies of morphology indicate that neurons develop a network of small-world-like connections, with the possibility of a very high connectivity degree. Here we study a recent model based on self-organized criticality, which consists of an electrical network with threshold firing and activity-dependent synapse strengths. We study the model on a scale-free network, the Apollonian network. The system exhibits an avalanche activity with a power law distribution of sizes and durations. The analysis of the power spectra of the electrical signal reproduces very robustly the power law behavior with the exponent 0.8, experimentally measured in electroencephalogram spectra. The exponents are found to be quite stable with respect to initial configurations and strength of plastic remodeling, indicating that universality holds for a wide class of neural network models.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11591/190165
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