http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
Statistical signal processing for neuroscience and neurotechnology
This is a uniquely comprehensive reference that summarizes the state of the art of signal processing theory and techniques for solving emerging problems in neuroscience, and which clearly presents new theory, algorithms, software and hardware tools that are specifically tailored to the nature of the neurobiological environment. It gives a broad overview of the basic principles, theories and methods in statistical signal processing for basic and applied neuroscience problems. Written by experts in the field, the book is an ideal reference for researchers working in the field of neural engineering, neural interface, computational neuroscience, neuroinformatics, neuropsychology and neural physiology. By giving a broad overview of the basic principles, theories and methods, it is also an ideal introduction to statistical signal processing in neuroscience. A comprehensive overview of the specific problems in neuroscience that require application of existing and development of new theory, techniques, and technology by the signal processing community Contains state-of-the-art signal processing, information theory, and machine learning algorithms and techniques for neuroscience research Presents quantitative and information-driven science that has been, or can be, applied to basic and translational neuroscience problems.
Detection and classification of extracellular action potential recordings / Karim G. Oweiss and Mehdi A. Aghagolzadeh -- Information-theoretic analysis of neural data / Don H. Johnson -- Identification of nonlinear dynamics in neural population activity / Dong Song and Theodore W. Berger -- Graphical models of functional and effective neuronal connectivity / Seif M. Eldawlatly and Karim G. Oweiss -- State-space modeling of neural spike train and behavioral data / Zhe Chen, Riccardo Barbieri, and Emery N. Brown -- Neural decoding for motor and communication prostheses / Byron M. Yu ... [et al.] -- Inner products for representation and learning in the spike train domain / Antonio R.C. Paiva, Il Park, and José C. Príncipe -- Signal processing and machine learning for single-trial analysis of simultaneously acquired EEG and fMRI / Paul Sajda ... [et al.] -- Statistical pattern recognition and machine learning in brain-computer interfaces / Rajesh P.N. Rao and Reinhold Scherer -- Prediction of muscle activity from cortical signals to restore hand grasp in subjects with spinal cord injury / Emily R. Oby ... [et al.].
Includes bibliographical references and index.
Burlington, MA : Academic Press/Elsevier, c2010
177376:173809 Elsevier Science & Technology