Statistical and Process Models for Cognitive Neuroscience and Aging: 1st Edition (Paperback) book cover

Statistical and Process Models for Cognitive Neuroscience and Aging

1st Edition

Edited by Michael J. Wenger, Christof Schuster

Psychology Press

358 pages

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Paperback: 9780805854145
pub: 2007-01-30
Hardback: 9780805854138
pub: 2007-01-30
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pub: 2007-01-30
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Statistical and Process Models for Cognitive Neuroscience and Aging addresses methodological techniques for researching cognitive impairment, Alzheimer's disease, the biophysics and structure of the nervous system, the physiology of memory, and the analysis of EEG data. Each chapter, written by the expert in the area, provides a carefully crafted introduction to the subject at hand and the key methodological challenges facing that area of study.

Although the chapters describe sophisticated techniques, each is accessible to scientists from a variety of fields. The editors' goal is to expose researchers working on a range of issues associated with cognitive aging to a variety of approaches and technologies, in an effort to cross disciplinary boundaries and further research in cognitive aging.

Intended for researchers in cognitive, behavioral, and computational neuroscience, psychometrics, gerontology, cognitive, health, and developmental psychology, radiology, and medical research, this book also serves as a text for graduate level courses in cognitive science and cognitive aging.

Table of Contents

Contents: M.J. Wenger, C. Schuster, Preface. S.D. Edland, R.C. Petersen, Longitudinal Study in Cognition and Aging. F.G. Ashby, V.V. Valentin, Computational Cognitive Neuroscience: Building and Testing Biologically Plausible Computational Models of Neuroscience, Neuroimaging, and Behavioral Data. M.E. Hasselmo, J. McGaughy, C. Linster, Modeling the Role of Acetylcholine and Hippocampal Theta Rhythm in Memory-Guided Behavior. J.M.J. Murre, M. Meeter, A.G. Chessa, Modeling Amnesia: Connectionist and Mathematical Approaches. A. Keinan, A. Kaufman, C.C. Hilgetag, I. Meilijson, E. Ruppin, Who Does What: Taking Measures. A. Cichocki, Generalized Component Analysis and Blind Source Separation Methods for Analyzing Multichannel Brain Signals. T.C. Ferree, M.A. Kramer, D.J. McGonigle, R.C. Hwa, Quantifying Scaling Properties in Neurophysiological Time Series. T.-P. Jung, T.-W. Lee, Applications of Independent Component Analysis to Electroencephalography.

About the Series

Notre Dame Series on Quantitative Methodology

The Notre Dame Series on Quantitative Methodology offers advanced training in quantitative methods for social and behavioral research.

Leading experts in data analytic techniques provide instruction in state-of-the-art methods designed to enhance quantitative skills in a substantive domain.

Each volume brings together expert methodologists and a workshop audience of substantive researchers. The substantive researchers are challenged with innovative techniques and the methodologists are challenged by innovative applications.

The goal is to stimulate an emergent substantive and methodological synthesis, enabling the solution of existing problems and raising new questions that need to be asked.

Each volume targets researchers in a specific substantive area, but also contains innovative techniques of interest to pure methodologists.

Learn more…

Subject Categories

BISAC Subject Codes/Headings:
PSYCHOLOGY / Cognitive Psychology
PSYCHOLOGY / Statistics
PSYCHOLOGY / Developmental / Adulthood & Aging