Statistical and Process Models for Cognitive Neuroscience and Aging

Michael J. Wenger, Christof Schuster

This book 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. Intended for researchers in cognitive, be

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.