Ispc

A comprehensive guide to the conceptual, mathematical, and implementational aspects of analyzing electrical brain signals, including data from MEG, EEG, and LFP recordings. This book offers a comprehensive guide to the theory and practice of analyzing electrical brain signals. It explains the conceptual, mathematical, and implementational (via Matlab programming) aspects of time-, time-frequency- and synchronization-based analyses of magnetoencephalography (MEG), electroencephalography (EEG), and local field potential (LFP) recordings from humans and nonhuman animals. It is the only book on the topic that covers both the theoretical background and the implementation in language that can be understood by readers without extensive formal training in mathematics, including cognitive scientists, neuroscientists, and psychologists. Readers who go through the book chapter by chapter and implement the examples in Matlab will develop an understanding of why and how analyses are performed, how to interpret results, what the methodological issues are, and how to perform single-subject-level and group-level analyses. Researchers who are familiar with using automated programs to perform advanced analyses will learn what happens when they click the “analyze now” button. The book provides sample data and downloadable Matlab code. Each of the 38 chapters covers one analysis topic, and these topics progress from simple to advanced. Most chapters conclude with exercises that further develop the material covered in the chapter. Many of the methods presented (including convolution, the Fourier transform, and Euler's formula) are fundamental and form the groundwork for other advanced data analysis methods. Readers who master the methods in the book will be well prepared to learn other approaches.

Comprehensive Natural Products III, Third Edition, Seven Volume Set updates and complements the previous two editions, including recent advances in cofactor chemistry, structural diversity of natural products and secondary metabolites, enzymes and enzyme mechanisms and new bioinformatics tools. Natural products research is a dynamic discipline at the intersection of chemistry and biology concerned with isolation, identification, structure elucidation, and chemical characteristics of naturally occurring compounds such as pheromones, carbohydrates, nucleic acids and enzymes. This book reviews the accumulated efforts of chemical and biological research to understand living organisms and their distinctive effects on health and medicine and to stimulate new ideas among the established natural products community. Provides readers with an in-depth review of current natural products research and a critical insight into the future direction of the field Bridges the gap in knowledge by covering developments in the field since the second edition published in 2010 Split into 7 sections on key topics to allow students, researchers and professionals to find relevant information quickly and easily Ensures that the knowledge within is easily understood by and applicable to a large audience

Conflict adaptation theory is one of the most popular theories in cognitive psychology. The theory argues that participants strategically modulate attention away from distracting stimulus features in response to conflict. Although results with proportion congruent, sequential congruency, and similar paradigms seem consistent with the conflict adaptation view, some researchers have expressed scepticism. The paradigms used in the study of conflict adaptation require the manipulation of stimulus frequencies, sequential dependencies, time-on-task regularities, and various other task regularities that introduce the potential for learning of conflict-unrelated information. This results in the unintentional confounding of measures of conflict adaptation with simpler learning and memory biases. There are also alternative accounts which propose that attentional adaptation does occur, but via different mechanisms, such as valence, expectancy, or effort. A significant (and often heated) debate remains surrounding the question of whether conflict adaptation exists independent of these alternative mechanisms of action. The aim of this Research Topic is to provide a forum for current directions in this area, considering perspectives from all sides of the debate.

A major hallmark in the adaptive control of voluntary action is the ability to anticipate short and long term future events. Anticipation in its various forms is an important prerequisite for (higher order) cognitive abilities such as planning, reasoning and the pursuit of both immediate goals and long-term goals that may even stand in opposition to immediate desires and needs (e.g., to invest in pension funds). Therefore, it is not surprising that diverse and rather independent research lines have evolved, all somehow targeting various anticipatory capacities that are involved in the control of voluntary action and thus, contribute to the uniqueness of human goal-directed behavior. For example, prediction of the incentive value of action outcomes drives goal-directed instrumental behavior (e.g., Dickinson & Balleine, 2000; Rushworth & Behrens, 2008). Similarly, the Ideo-Motor Principle assumes that actions are selected and activated by the mere anticipation of the sensory experience they produce (e.g., James, 1890; Prinz, 1990). Furthermore, the degree of match between intended, anticipated and actual action effects has been proposed to be a major determinant of motor programming and online action corrections (Jeannerod, 1981), motor learning (e.g., Wolpert, Diedrichsen, & Flanagan, 2011), and the subjective sense of causing and controlling an action and its effects (Sense of Agency; e.g., Abell, Happé, & Frith, 2000). The role of anticipation in the control of voluntary action, however, goes far beyond the anticipation of immediate action effects and desired goals. For instance, pre-cues and alerting signals are used for advance preparation of what to do (e.g., Meiran, 1996), when to act or expect an event onset (e.g., Callejas, Lupianez, & Tudela, 2004; Los & van der Heuvel, 2001; Nobre & Coull, 2010) and to anticipate conflict (e.g., Correa, Rao, & Nobre, 2009). Voluntary action is influenced by the anticipation and prediction of mental effort in task processing (e.g., Song & Schwarz, 2008). In addition, the anticipation of long-term future social consequences (e.g., expected aloneness) has been shown to affect cognitive mechanisms involved in logic and reasoning (e.g., Baumeister, Twenge, & Nuss, 2002). Last but not least, learning of statistical contingencies (e.g., conflict frequency) leads to the anticipation and prediction of context-specific executive control requirements (e.g., Crump, Gong, & Milliken, 2006, Dreisbach & Haider, 2006). The aim of the present Research Topic is to provide a platform that offers the possibility of cross-fertilization and enhanced visibility among to date rather segregated research lines.