A self-organizing neural network model for the development of aaerent and lateral input connections in cortical feature maps is presented. The weight adaptation process is purely activity-dependent, unsupervised, and local. The aaerent input weights self-organize into a topological map of the input space. At the same time, the lateral interaction weights develop a smooth \Mexican hat" shaped di...

This paper presents a computer simulation of the emergence of vowel systems in a population of agents. The agents (small computer programs that operate autonomously) are equipped with a realistic articulatory synthesizer, a model of human perception and the ability to imitate and learn sounds they hear. It is shown that due to the interactions between the agents and due to self-organization, re...

-In this work, we use Potts neurons for the competitive mechanism in a self-organization model. We obtain new algorithms on the basis of a Potts neural network for coherent mapping, and we remodel the Durbin algorithm and the Kohonen algorithm with mean field annealing. The resulting dimension-reducing mappings possess a highly reliable topology preservation such that the nearby elements in the...

We study collaboration networks in terms of evolving, self-organizing bipartite graph models. We propose a model of a growing network, which combines preferential edge attachment with the bipartite structure, generic for collaboration networks. The model depends exclusively on basic properties of the network, such as the total number of collaborators and acts of collaboration, the mean size of ...

We propose a model of parameter learning for signal transduction, where the objective function is defined by signal transmission efficiency. We apply this to learn kinetic rates as a form of evolutionary learning, and look for parameters which satisfy the objective. This is a novel approach compared to the usual technique of adjusting parameters only on the basis of experimental data. The resul...

Background noise is the irregular variation across repeated measurements of human performance. Background noise remains after task and treatment effects are minimized. Background noise refers to intrinsic sources of variability, the intrinsic dynamics of mind and body, and the internal workings of a living being. Two experiments demonstrate 1/f scaling (pink noise) in simple reaction times and ...

Introduction Humans are rather funny things, we often tend to imagine that we are so ‘special’, so divorced by our supposed ‘intelligence’ from the influences of the ‘natural world’ and so unique in our ‘abstracting’ abilities. We have this persistent delusion, evident since ancient Greek times, that we are ‘rational’, that we can behave as ‘disinterested observers’ of our world, which manifest...

background: blood donation safety is one of the basic goals of the organization of blood transfusion in the world. self-exclusion and failed options are additional screening tests to routine diagnostic tests which is performed to detect the transmitted infection through blood or blood products. the purpose of this study was to investigate the efficacy of these systems on the improvement of bloo...

This paper describes research that investigates the structure of human vowel systems through individual learning and self-organization. A population of agents that have to learn to imitate each other has been implemented. The agents can interact with each other through so-called imitation games: structured exchanges of sounds from which they can learn how to improve their repertoire of sounds. ...

In this chapter we discuss how the results developed within the theory of fractals and Self–Organized Criticality (SOC) can be fruitfully exploited as ingredients of adaptive network models. In order to maintain the presentation self– contained, we first review the basic ideas behind fractal theory and SOC. We then briefly review some results in the field of complex networks, and some of the mo...