Hierarchical growing neural gas

“The original publication is available at www.springerlink.com”. Copyright Springer.This paper describes TreeGNG, a top-down unsupervised learning method that produces hierarchical classification schemes. TreeGNG is an extension to the Growing Neural Gas algorithm that maintains a time history of the learned topological mapping. TreeGNG is able to correct poor decisions made during the early phases of the construction of the tree, and provides the novel ability to influence the general shape and form of the learned hierarchy

Fast algorithm for detecting community structure in networks

It has been found that many networks display community structure -- groups of vertices within which connections are dense but between which they are sparser -- and highly sensitive computer algorithms have in recent years been developed for detecting such structure. These algorithms however are computationally demanding, which limits their application to small networks. Here we describe a new algorithm which gives excellent results when tested on both computer-generated and real-world networks and is much faster, typically thousands of times faster than previous algorithms. We give several example applications, including one to a collaboration network of more than 50000 physicists.Comment: 5 pages, 4 figure

TELEPENSOUTH project: Measurement of the Earth gravitomagnetic field in a terrestrial laboratory

We will expose a preliminary study on the feasibility of an experiment leading to a direct measurement of the gravitomagnetic field generated by the rotational motion of the Earth. This measurement would be achieved by means of an appropriate coupling of a TELEscope and a Foucault PENdulum in a laboratory on ground, preferably at the SOUTH pole. An experiment of this kind was firstly proposed by Braginski, Polnarev and Thorne, 18 years ago, but it was never re-analyzed.Comment: 7 pages, LaTeX, Springer style files included. Contribution to the Proceedings of the Spanish Relativity Meeting-ERE-2001 (Madrid, September 2001). To appear in the book "Relativistic Astrophysics", Lecture Notes in Physics, Springer Verlag (2002), edited by L. Fernandez-Jambrina, L.M. Gonzalez-Romer

Triple dissociation of anterior cingulate, posterior cingulate, and medial frontal cortices on visual discrimination tasks using a touchscreen testing procedure for the rat.

Four experiments examined effects of quinolinic acid-induced lesions of the anterior cingulate, posterior cingulate, and medial frontal cortices on tests of visual discrimination learning, using a new touchscreen testing method for rats. Anterior cingulate cortex lesions impaired acquisition of an 8-pair concurrent discrimination task, whereas posterior cingulate cortex lesions facilitated learning but selectively impaired the late stages of acquisition of a visuospatial conditional discrimination. Medial frontal cortex lesions selectively impaired reversal learning when stimuli were difficult to discriminate; lesions of anterior and posterior cingulate cortex had no effect. These results suggest roles for the anterior cingulate, posterior cingulate, and medial frontal cortex in stimulus-reward learning, stimulus-response learning or response generation, and attention during learning, respectively

Preferential attachment of communities: the same principle, but a higher level

The graph of communities is a network emerging above the level of individual nodes in the hierarchical organisation of a complex system. In this graph the nodes correspond to communities (highly interconnected subgraphs, also called modules or clusters), and the links refer to members shared by two communities. Our analysis indicates that the development of this modular structure is driven by preferential attachment, in complete analogy with the growth of the underlying network of nodes. We study how the links between communities are born in a growing co-authorship network, and introduce a simple model for the dynamics of overlapping communities.Comment: 7 pages, 3 figure