Inspired by empirical studies of networked systems such as the Internet, social networks, and biological networks, researchers have in recent years developed a variety of techniques and models to help us understand or predict the behavior of these systems. Here we review developments in this field, including such concepts as the small-world effect, degree distributions, clustering, network correlations, random graph models, models of network growth and preferential attachment, and dynamical processes taking place on networks.

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The Structure and Function of Complex Networks

Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Pattern Recognition and Machine Learning

http://www.maths.qmul.ac.uk/%7Elatora/report_06.pdf

Complex networks: Structure and dynamics

I have developed "tennis elbow" from lugging this book around the past four weeks, but it is worth the pain, the effort, and the aspirin. It is also worth the (relatively speaking) bargain price. Including appendixes, this book contains 894 pages of text. The entire panorama of the neural sciences is surveyed and examined, and it is comprehensive in its scope, from genomes to social behaviors. The editors explicitly state that the book is designed as "an introductory text for students of biology, behavior, and medicine," but it is hard to imagine any audience, interested in any fragment of neuroscience at any level of sophistication, that would not enjoy this book. The editors have done a masterful job of weaving together the biologic, the behavioral, and the clinical sciences into a single tapestry in which everyone from the molecular biologist to the practicing psychiatrist can find and appreciate his or

Principles of Neural Science

The organization of behavior: A neuropsychological theory

A recurrent idea in the study of complex systems is that optimal information processing is to be found near phase transitions. However, this heuristic hypothesis has few (if any) concrete realizations where a standard and biologically relevant quantity is optimized at criticality. Here we give a clear example of such a phenomenon: a network of excitable elements has its sensitivity and dynamic range maximized at the critical point of a non-equilibrium phase transition. Our results are compatible with the essential role of gap junctions in olfactory glomeruli and retinal ganglionar cell output. Synchronization and global oscillations also emerge from the network dynamics. We propose that the main functional role of electrical coupling is to provide an enhancement of dynamic range, therefore allowing the coding of information spanning several orders of magnitude. The mechanism could provide a microscopic neural basis for psychophysical laws.

Optimal Dynamical Range of Excitable Networks at Criticality

The number h of papers with at least h citations has been proposed to evaluate individuals scientific research production. This index is robust in several ways but yet strongly dependent on the research field. We propose a complementary index ) ( 2 T a I N h h = , with ) (T a N being the total number of authors in the considered h papers. A researcher with index hI has hI papers with at least hI citation if he/she had published alone. We have obtained the rank plots of h and h I for four Brazilian scientific communities. In contrast with the h-index, the h I index rank plots collapse into a single curve allowing comparison among different research areas.

Is it possible to compare researchers with different scientific interests

The number h of papers with at least h citations has been proposed to evaluate individual's scientific research production. This index is robust in several ways but yet strongly dependent on the research field. We propose a complementary index hI = h^2/N_t, with N_t being the total number of authors in the considered h papers. A researcher with index hI has hI papers with at least hI citation if he/she had published alone. We have obtained the rank plots of h and hI for four Brazilian scientific communities. Contrasting to the h-index curve, the hI index present a perfect data collapse into a unique allowing comparison among different research areas.

An index to quantify an individual's scientific research valid across disciplines

Background
Psychosis has various causes, including mania and schizophrenia. Since the differential diagnosis of psychosis is exclusively based on subjective assessments of oral interviews with patients, an objective quantification of the speech disturbances that characterize mania and schizophrenia is in order. In principle, such quantification could be achieved by the analysis of speech graphs. A graph represents a network with nodes connected by edges; in speech graphs, nodes correspond to words and edges correspond to semantic and grammatical relationships.

/pdf/speech-graphs-provide-a-quantitative-measure-of-thought-1j6wbngpq5.pdf

Speech Graphs Provide a Quantitative Measure of Thought Disorder in Psychosis

A new learning algorithm for the one-layer perceptron is presented. It aims to maximize the generalization gain per example. Analytical results are obtained for the case of single presentation of each example. The weight attached to a Hebbian term is a function of the expected stability of the example in the teacher perceptron. This leads to the obtention of upper bounds for the generalization ability. This scheme can be iterated and the results of numerical simulations show that it converges, within errors, to the theoretical optimal generalization ability of the Bayes algorithm. Analytical and numerical results for an algorithm with maximized generalization in the learning strategy with selection of examples are obtained and it is proved that, as expected, orthogonal selection is optimal. Exponential decay of the generalization error is obtained for the single presentation of selected examples.

Osame Kinouchi

Papers

Optimal Dynamical Range of Excitable Networks at Criticality

Is it possible to compare researchers with different scientific interests

An index to quantify an individual's scientific research valid across disciplines

Speech Graphs Provide a Quantitative Measure of Thought Disorder in Psychosis

Optimal generalization in perceptions