Bøker i Synthesis Lectures on Biomedical Engineering-serien

The present book illustrates the theoretical aspects of several methodologies related to the possibility of i) enhancing the poor spatial information of the electroencephalographic (EEG) activity on the scalp and giving a measure of the electrical activity on the cortical surface. ii) estimating the directional influences between any given pair of channels in a multivariate dataset. iii) modeling the brain networks as graphs. The possible applications are discussed in three different experimental designs regarding i) the study of pathological conditions during a motor task, ii) the study of memory processes during a cognitive task iii) the study of the instantaneous dynamics throughout the evolution of a motor task in physiological conditions. The main outcome from all those studies indicates clearly that the performance of cognitive and motor tasks as well as the presence of neural diseases can affect the brain network topology. This evidence gives the power of reflecting cerebral "states" or "traits" to the mathematical indexes derived from the graph theory. In particular, the observed structural changes could critically depend on patterns of synchronization and desynchronization - i.e. the dynamic binding of neural assemblies - as also suggested by a wide range of previous electrophysiological studies. Moreover, the fact that these patterns occur at multiple frequencies support the evidence that brain functional networks contain multiple frequency channels along which information is transmitted. The graph theoretical approach represents an effective means to evaluate the functional connectivity patterns obtained from scalp EEG signals. The possibility to describe the complex brain networks sub-serving different functions in humans by means of "numbers" is a promising tool toward the generation of a better understanding of the brain functions. Table of Contents: Introduction / Brain Functional Connectivity / Graph Theory / High-Resolution EEG / Cortical Networks in Spinal Cord Injured Patients / Cortical Networks During a Lifelike Memory Task / Application to Time-varying Cortical Networks / Conclusions

Heredity performs literal communication of immensely long genomes through immensely long time intervals. Genomes nevertheless incur sporadic errors referred to as mutations which have significant and often dramatic effects, after a time interval as short as a human life. How can faithfulness at a very large timescale and unfaithfulness at a very short one be conciliated? The engineering problem of literal communication has been completely solved during the second half of the XX-th century. Originating in 1948 from Claude Shannon's seminal work, information theory provided means to measure information quantities and proved that communication is possible through an unreliable channel (by means left unspecified) up to a sharp limit referred to as its capacity, beyond which communication becomes impossible. The quest for engineering means of reliable communication, named error-correcting codes, did not succeed in closely approaching capacity until 1993 when Claude Berrou and Alain Glavieuxinvented turbocodes. By now, the electronic devices which invaded our daily lives (e.g., CD, DVD, mobile phone, digital television) could not work without highly efficient error-correcting codes. Reliable communication through unreliable channels up to the limit of what is theoretically possible has become a practical reality: an outstanding achievement, however little publicized. As an engineering problem that nature solved aeons ago, heredity is relevant to information theory. The capacity of DNA is easily shown to vanish exponentially fast, which entails that error-correcting codes must be used to regenerate genomes so as to faithfully transmit the hereditary message. Moreover, assuming that such codes exist explains basic and conspicuous features of the living world, e.g., the existence of discrete species and their hierarchical taxonomy, the necessity of successive generations and even the trend of evolution towards increasingly complex beings. Providing geneticists with an introduction to information theory and error-correcting codes as necessary tools of hereditary communication is the primary goal of this book. Some biological consequences of their use are also discussed, and guesses about hypothesized genomic codes are presented. Another goal is prompting communication engineers to get interested in genetics and biology, thereby broadening their horizon far beyond the technological field, and learning from the most outstanding engineer: Nature. Table of Contents: Foreword / Introduction / A Brief Overview of Molecular Genetics / An Overview of Information Theory / More on Molecular Genetics / More on Information Theory / An Outline of Error-Correcting Codes / DNA is an Ephemeral Memory / A Toy Living World / Subsidiary Hypothesis, Nested System / Soft Codes / Biological Reality Conforms to the Hypotheses / Identification of Genomic Codes / Conclusion and Perspectives

In the past 50 years there has been an explosion of interest in the development of technologies whose end goal is to connect the human brain and/or nervous system directly to computers. Once the subject of science fiction, the technologies necessary to accomplish this goal are rapidly becoming reality. In laboratories around the globe, research is being undertaken to restore function to the physically disabled, to replace areas of the brain damaged by disease or trauma and to augment human abilities. Building neural interfaces and neuro-prosthetics relies on a diverse array of disciplines such as neuroscience, engineering, medicine and microfabrication just to name a few. This book presents a short history of neural interfacing (N.I.) research and introduces the reader to some of the current efforts to develop neural prostheses. The book is intended as an introduction for the college freshman or others wishing to learn more about the field. A resource guide is included for students along with a list of laboratories conducting N.I. research and universities with N.I. related tracks of study.Table of Contents: Neural Interfaces Past and Present / Current Neuroprosthesis Research / Conclusion / Resources for Students