Cognitive neuroscience: the evolution of a discipline

Preface. The evolution of cognitive neuroscience has been spurred by the development of increasingly sophisticated investigative techniques to study human cognition. In Methods in Mind, experts examine the wide variety of tools available to cognitive neuroscientists, paying particular attention to the ways in which different methods can be integrated to strengthen empirical findings and how innovative uses for established techniques can be developed. The book will be a uniquely valuable resource for the researcher seeking to expand his or her repertoire of investigative techniques. Each chapter explores a different approach. These include transcranial magnetic stimulation, cognitive neuropsychiatry, lesion studies in nonhuman primates, computational modeling, psychophysiology, single neurons and primate behavior, grid computing, eye movements, fMRI, electroencephalography, imaging genetics, magnetoencephalography, neuropharmacology, and neuroendocrinology. As mandated, authors focus on convergence and innovation in their fields; chapters highlight such cross-method innovations as the use of the fMRI signal to constrain magnetoencephalography, the use of electroencephalography (EEG) to guide rapid transcranial magnetic stimulation at a specific frequency, and the successful integration of neuroimaging and genetic analysis. Computational approaches depend on increased computing power, and one chapter describes the use of distributed or grid computing to analyze massive datasets in cyberspace. Each chapter author is a leading authority in the technique discussed.

Impact of third-order fibre dispersion on the evolution of parabolic optical pulses

We develop a perturbation analysis that describes the effect of third-order dispersion on the similariton pulse solution of the nonlinear Schrodinger equation in a fibre gain medium. The theoretical model predicts with sufficient accuracy the pulse structural changes induced, which are observed through direct numerical simulations.

Overcoming network overload and redundancy in inter-organizational networks:the roles of potential and latent ties

This paper builds on Granovetter's distinction between strong and weak ties [Granovetter, M. S. 1973. The strength of weak ties. Amer. J. Sociol. 78(6) 1360–1380] in order to respond to recent calls for a more dynamic and processual understanding of networks. The concepts of potential and latent tie are deductively identified, and their implications for understanding how and why networks emerge, evolve, and change are explored. A longitudinal empirical study conducted with companies operating in the European motorsport industry reveals that firms take strategic actions to search for potential ties and reactivate latent ties in order to solve problems of network redundancy and overload. Examples are given, and their characteristics are examined to provide theoretical elaboration of the relationship between the types of tie and network evolution. These conceptual and empirical insights move understanding of the managerial challenge of building effective networks beyond static structural contingency models of optimal network forms to highlight the processes and capabilities of dynamic relationship building and network development. In so doing, this paper highlights the interrelationship between search and redundancy and the scope for strategic action alongside path dependence and structural influences on network processes.

Impact of third-order dispersion on the evolution of parabolic pulses

We present a perturbation analysis that describes the effect of third-order dispersion on the similariton pulse solution of the nonlinear Schrödinger equation in a fibre gain medium. The theoretical model predicts with sufficient accuracy the pulse structural changes induced, which are observed through direct numerical simulations.

The evolution of learning systems:to Bayes or not to be

Bayesian algorithms pose a limit to the performance learning algorithms can achieve. Natural selection should guide the evolution of information processing systems towards those limits. What can we learn from this evolution and what properties do the intermediate stages have? While this question is too general to permit any answer, progress can be made by restricting the class of information processing systems under study. We present analytical and numerical results for the evolution of on-line algorithms for learning from examples for neural network classifiers, which might include or not a hidden layer. The analytical results are obtained by solving a variational problem to determine the learning algorithm that leads to maximum generalization ability. Simulations using evolutionary programming, for programs that implement learning algorithms, confirm and expand the results. The principal result is not just that the evolution is towards a Bayesian limit. Indeed it is essentially reached. In addition we find that evolution is driven by the discovery of useful structures or combinations of variables and operators. In different runs the temporal order of the discovery of such combinations is unique. The main result is that combinations that signal the surprise brought by an example arise always before combinations that serve to gauge the performance of the learning algorithm. This latter structures can be used to implement annealing schedules. The temporal ordering can be understood analytically as well by doing the functional optimization in restricted functional spaces. We also show that there is data suggesting that the appearance of these traits also follows the same temporal ordering in biological systems. © 2006 American Institute of Physics.

Impact of third-order dispersion on the evolution of parabolic pulses

We present a perturbation analysis that describes the effect of third-order dispersion on the similariton pulse solution of the nonlinear Schrödinger equation in a fibre gain medium. The theoretical model predicts with sufficient accuracy the pulse structural changes induced, which are observed through direct numerical simulations.

Tracing the evolution of physics on the backbone of citation networks

Many innovations are inspired by past ideas in a nontrivial way. Tracing these origins and identifying scientific branches is crucial for research inspirations. In this paper, we use citation relations to identify the descendant chart, i.e., the family tree of research papers. Unlike other spanning trees that focus on cost or distance minimization, we make use of the nature of citations and identify the most important parent for each publication, leading to a treelike backbone of the citation network. Measures are introduced to validate the backbone as the descendant chart. We show that citation backbones can well characterize the hierarchical and fractal structure of scientific development, and lead to an accurate classification of fields and subfields. © 2011 American Physical Society.

The evolution of the car-making industry

Mass-production, cars, pollution – they all have long become well known and well connected phenomena of the modern life. Nowadays the people can also add to the list such items like awareness, scientific approach, long-term thinking, and environmental responsibility. They are surrounded by a multitude of consumer goods, most of which are produced in a scientific manner, and all of which will more sooner than later end up in the garbage. Cars are the most noticeable – both by size and by numbers – and also the most expensive of all the mass products in people’s view. For many of them they are a clear target for reprimand and regulation, and, as a result, the automotive industry is being increasingly brought under bureaucratic control, together with its whole supplier and distributor network. The author started writing this article in an attempt to place the above process under scrutiny, because it is his firm belief that similar measures, similar tough governmental control will inevitably spill over to other industries, which at the moment are producing more inconspicuous, but still polluting products. The present paper shows the relationship between car-making, supply chain management and the efforts of public administration to protect the environment – a connection with clear practical implications.

Unravelling the evolution of autumn colours: an interdisciplinary approach.

Leaf colour change is commonly observed in temperate deciduous forests in autumn. This is not simply a side effect of leaf senescence, and, in the past decade, several hypotheses have emerged to explain the evolution of autumn colours. Yet a lack of crosstalk between plant physiologists and evolutionary ecologists has resulted in slow progress, and so the adaptive value of this colour change remains a mystery. Here we provide an interdisciplinary summary of the current body of knowledge on autumn colours, and discuss unresolved issues and future avenues of research that might help reveal the evolutionary meaning of this spectacle of nature.

Social-cognitive antecedents of ambidextrous orientation in family-owned startups: The role of family ties, achievement motivation, and internal locus of control

Regulatory Focus Theory predicts that the motivation to self-regulate goal-directed thought and behavior depends on two distinct regulation strategies: a promotion focus based on attaining gains and a prevention focus based on avoiding losses. This study took a social-cognitive approach predicting that regulatory focus has an impact on how family startups (several family related founders) explore "new ideas", exploit "old certainties" and achieve the balance of both (ambidexterity), compared to lone founder startups (only one founder present). It was proposed that the social context of family ties among founders leads them to a prevention focus concerned with avoiding the loss of the socio-emotional benefits of those ties. In order to avoid such a loss, family founders were expected to increase their risk perceptions and thus, explore less than lone founders, who lack such socio-emotional ties. It was also proposed that two commonly used psychological traits in entrepreneurship research —achievement motivation and internal locus of control, predispose entrepreneurs to a promotion focus. Founders with a promotion focus, in turn, were hypothesized to lead startups to more risk-seeking behaviors and to more explorative orientation. The previous argument was used as a springboard to derive hypotheses about ambidexterity (the ability to exploit and explore simultaneously) and survival hazards. Using Regulatory Focus Theory, exploitative orientation, conceptualized as the motivational strength to continue on previous paths of action, was hypothesized to be not significantly different from that of lone founder startups. Taking previous arguments together, lone founder startups were hypothesized to be more ambidextrous than family startups. Finally, ambidexterity and internal locus of control were hypothesized to reduce survival hazards in family startups. The findings suggested that family startups explore less than lone founder startups even after controlling for group effects. Interesting but contradictory findings revealed that internal locus of control have both a positive direct effect and a positive interaction that increases the explorative and ambidextrous orientation gap of family startups over lone founder startups. As expected, ambidexterity and internal locus of control reduced survival hazards on family startups. Implications for practitioners were derived based on a sample of 470 nascent entrepreneurs.

The evolution of IL-4 and IL-13 and their receptor subunits

Peer reviewed

The Evolution of Pharmaceutical Care for Drug Misusers

This survey was funded by a grant from the Chief Scientist Office (CSO), Grant No: CZH/4/998.