title: Intrinsic Plasticity for Natural Competition in Koniocortex-Like Neural Networks.
abstract: In this paper, we use the neural property known as intrinsic plasticity to develop neural network models that resemble the koniocortex, the fourth layer of sensory cortices. These models evolved from a very basic two-layered neural network to a complex associative koniocortex network. In the initial network, intrinsic and synaptic plasticity govern the shifting of the activation function, and the modification of synaptic weights, respectively. In this first version, competition is forced, so that the most activated neuron is arbitrarily set to one and the others to zero, while in the second, competition occurs naturally due to inhibition between second layer neurons. In the third version of the network, whose architecture is similar to the koniocortex, competition also occurs naturally owing to the interplay between inhibitory interneurons and synaptic and intrinsic plasticity. A more complex associative neural network was developed based on this basic koniocortex-like neural network, capable of dealing with incomplete patterns and ideally suited to operating similarly to a learning vector quantization network. We also discuss the biological plausibility of the networks and their role in a more complex thalamocortical model.
authors.affiliation: 1 Center of Mathematics, Computation and Cognition, Federal University of ABC, Santo André SP 09210-580 Brazil.
authors.forename: Francisco Javier Ropero
authors.initials: FJ
authors.lastname: Peláez
authors.affiliation: 2 Neurosciences and Behavior Research Nucleus, University of Sao Paulo, SP 05508-030, Brazil.
authors.forename: Mariana Antonia
authors.initials: MA
authors.lastname: Aguiar-Furucho
authors.affiliation: 3 Group for Automation in Signal and Communications, Technical University of Madrid, ETSI Telecomunicación, 28040 Madrid, Spain.
authors.forename: Diego
authors.initials: D
authors.lastname: Andina
mesh_terms: D000465:Algorithms; D001499:Bayes Theorem; D002540:Cerebral Cortex / Q000502:physiology; D003198:Computer Simulation; D006801:Humans; D000069550:Machine Learning; D008959:Models, Neurological; D009433:Neural Inhibition / Q000502:physiology; D016571:Neural Networks, Computer; D009434:Neural Pathways / Q000502:physiology; D009473:Neuronal Plasticity / Q000502:physiology; D009474:Neurons / Q000502:physiology; D012984:Software; D013788:Thalamus / Q000502:physiology
keywords: Intrinsic plasticity; emergent process; feature extraction; koniocortex; pre-synaptic rule; winner-take-all