Thomas Martinetz

TL;DR: It is shown that the dynamics of the reference (weight) vectors during the input-driven adaptation procedure are determined by the gradient of an energy function whose shape can be modulated through a neighborhood determining parameter and resemble the dynamicsof Brownian particles moving in a potential determined by a data point density.

TL;DR: This competitive Hebbian rule provides a novel approach to the problem of constructing topology preserving feature maps and representing intricately structured manifolds and makes this novel approach particularly useful in all applications where neighborhood relations have to be exploited or the shape and topology of submanifolds have to been take into account.

TL;DR: It is shown in sleeping humans that auditory stimulation in phase with the ongoing rhythmic occurrence of slow oscillation up states profoundly enhances theSlow oscillation rhythm, phase-coupled spindle activity, and, consequently, the consolidation of declarative memory.

TL;DR: In this article, a comprehensive introduction to neural networks and neural information processing is presented. And the most important models of neural networks are described and how they contribute to our understanding of information and organization processes in the brain.

TL;DR: The stimuli types often used in laboratory experiments, static images and professionally cut material, are not very representative of natural viewing behavior, and eye movements on Hollywood movies are significantly more coherent than those on natural movies.