Statistical and Process Models for Cognitive Neuroscience and Aging

by Michael J. Wenger (Editor), Christof Schuster (Editor)

Overview

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 i

Product Details

ISBN-13:	9781135603342
Publisher:	Taylor & Francis
Publication date:	01/30/2007
Series:	Notre Dame Series on Quantitative Methodology
Sold by:	Barnes & Noble
Format:	eBook
Pages:	368
File size:	4 MB

About the Author

Michael J. Wenger, Christof Schuster

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.