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Self-Organized Criticality of a Neural Model in Complex Neural Networks
##manager.scheduler.building##: Edificio Santa Maria
##manager.scheduler.room##: Auditorio San Agustin
Date: 2019-07-08 11:45 AM – 03:30 PM
Last modified: 2019-06-15
Abstract
Some neural systems shows self-organized criticality. The probability distribution of the neural avalanches in some neural systems showed a power law with exponent 1.5. In this work we consider a modified integrate-and-fire neural model that includes the plasticity between the neural connections. The external inputs are applied on a randomly selected neurons. Each neuron accumulates the action potential from the nearest neighobrs and random input. We observed the self-organized criticality on complex neural networks such as random networks, small-world networks, and scale-free networks. The critical exponents of the power law depend on the network structure of the neural systems.