Exploratory Analysis and Data Modeling in Functional Neuroimaging (Hardcover)

Description:

Functional imaging tools such as fMRI (functional magnetic resonance imaging), PET (positron emission tomography), EEG (electro-encephalogram), and MEG (magneto-encephalogram) allow researchers to record activity in the working brain and draw inferences about how the brain functions. This book provides a survey of theoretical and computational approaches to neuroimaging, including inferential, exploratory, and causal methods of data analysis; theories of cerebral function; and biophysical and computational models of neural nets. It also emphasizes the close relationships between different approaches, for example, between causal data analysis and biophysical modeling, and between functional theories and computational models.

Friedrich T. Sommer is Scientist at the Redwood Neuroscience Institute, Menlo Park, CA.

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Series Foreword	vii
	Foreword Manfred Spitzer	ix
	Preface	xiii
1.	Theories, Data Analysis, and Simulation Models in Neuroimaging--An Overview Friedrich T. Sommer, Judith A. Hirsch and Andrzej Wichert	1
I.	fMRI Data Analysis and Experimental Design	15
2.	Exploratory Analysis of fMRI Data by Fuzzy Clustering--Philosophy, Strategy, Tactics, Implementation Ray Somorjai and Mark Jarmasz	17
3.	Testing Competing Hypotheses about Single Trial fMRI Lars Kai Hansen, Archana Purushotham and Seong-Gi Kim	49
4.	Deterministic and Stochastic Features of fMRI Data: Implications for Data Averaging Martin J. McKeown	63
5.	Exploratory Analysis of Event-Related fMRI Demonstrated in a Working Memory Study Andrzej Wichert, Henrik Walter, Jo Grothe, Birgit Abler and Friedrich T. Sommer	77
6.	Functional Magnetic Resonance Imaging Adaptation: A Technique for Studying the Properties of Neuronal Networks Andreas S. Tolias, Zoe Kourtzi and Nikos K. Logothetis	109
II.	EGM/MEG Data Analysis	127
7.	Independent Components of Magnetoencephalography: Localization Akaysha C. Tang and Barak A. Pearlmutter	129
8.	Blind Decomposition of Multimodal Evoked Responses and DC Fields Ricardo Vigário, Andreas Ziehe, Matthias M. Müller, Gerd Wübbeler, Lutz Trahms, Bruno-Marcel Mackert, Gabriel Curio, Veikko Jousmäki, Jaakko Särelä and Erkki Oja	163
III.	Combination EEG/MEG and fMRI	193
9.	Having Your Voxels and Timing Them Too? Scott Makeig, Tzyy-Ping Jung and Terrence J. Sejnowski	195
10.	Recording of Evoked Potentials during Functional MRI Frithjof Kruggel and Christoph S. Herrmann	209
IV.	Models Integrating Neurophysiology and Functional Imaging	229
11.	Synthetic PET Imaging for Grasping: From Primate Neurophysiology to Human Behavior Michael A. Arbib, Andrew H. Fagg and Scott T. Grafton	231
12.	The Use of Large-Scale Modeling for Interpreting Human Brain Imaging Experiments M-A. Tagamets and Barry Horwitz	251
13.	Large-Scale Networks in Learning Analyzed with Partial Least Squares Hemanth P. Nair and Francisco Gonzalez-Lima	273
	Index	295