Statistical and Process Models for Cognitive Neuroscience and Aging

Herausgeber: Schuster, Christof; Wenger, Michael J.

• Broschiertes Buch

Produktbeschreibung

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.

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Produktdetails

• Verlag: Psychology Press
• Seitenzahl: 370
• Erscheinungstermin: 30. Januar 2007
• Englisch
• Abmessung: 229mm x 152mm x 20mm
• Gewicht: 536g
• ISBN-13: 9780805854145
• ISBN-10: 0805854142
• Artikelnr.: 22242616

Autorenporträt

Michael J. Wenger, Christof Schuster

Inhaltsangabe

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.