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Functional Magnetic Resonance Imaging 3rd Revised edition [Hardback]

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  • Formāts: Hardback, 573 pages, height x width x depth: 221x282x28 mm, weight: 1678 g, 515 p., 1 Hardback
  • Izdošanas datums: 18-Aug-2014
  • Izdevniecība: Oxford University Press Inc
  • ISBN-10: 0878936270
  • ISBN-13: 9780878936274
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Functional Magnetic Resonance Imaging 3rd Revised editionPalielināt
  • Formāts: Hardback, 573 pages, height x width x depth: 221x282x28 mm, weight: 1678 g, 515 p., 1 Hardback
  • Izdošanas datums: 18-Aug-2014
  • Izdevniecība: Oxford University Press Inc
  • ISBN-10: 0878936270
  • ISBN-13: 9780878936274
Citas grāmatas par šo tēmu:
Permanent link: https://www.kriso.lv/db/9780878936274.html
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Published by Sinauer Associates, an imprint of Oxford University Press.

Functional Magnetic Resonance Imaging was the first textbook to provide a true introduction to fMRI--one that presented material authoritatively and comprehensively, yet was accessible to undergraduate students, graduate students, and beginning researchers.

This third edition features an updated discussion of the physiological basis of fMRI that includes recent discoveries about the origins of the BOLD response, new data-driven and computational approaches to fMRI data analysis, explanations of creative approaches to experimental design, and discussions of ethical and methodological controversies, among many other revisions.

Examples are drawn both from seminal historical work and cutting-edge current research. Concepts are reinforced by numerous thought problems and illustrated with full-color figures, all revised for this edition to achieve a contemporary graphic look. Each chapter is accompanied by updated references and suggested readings.
Preface xiii
Chapter 1 An Introduction to fMRI 1(30)
What Is fMRI?
3(13)
Measurement versus manipulation techniques
4(6)
Box 1.1 What Is fMRI Used For?
6(4)
Key concept: Contrast
10(3)
Key concept: Resolution
13(3)
History of fMRI
16(9)
Early studies of magnetic resonance
16(2)
NMR in bulk matter: Bloch and Purcell
18(1)
The earliest MR images
19(5)
Box 1.2 A Nobel Prize for MM
22(2)
Growth of MM
24(1)
Organization of the Textbook
25(4)
Physical bases of fMRI
26(1)
Principles of BOLD fMRI
26(1)
Design and analysis of fMRI experiments
27(1)
Applications and future directions
28(1)
Summary
29(1)
Suggested Readings
29(1)
Chapter References
30(1)
Chapter 2 MRI Scanners 31(26)
How MRI Scanners Work
31(13)
Static magnetic field
32(3)
Radiofrequency coils
35(3)
Gradient coils
38(3)
Shimming coils
41(1)
Computer hardware and software
41(2)
Experimental control system
43(1)
Physiological monitoring equipment
43(1)
MRI Safety
44(10)
Effects of static magnetic fields on human physiology
44(6)
Box 2.1 Outline of an fMRI Experiment
22(28)
Translation and torsion
50(1)
Gradient magnetic field effects
51(1)
Radiofrequency field effects
52(1)
Claustrophobia
53(1)
Acoustic noise
54(1)
Summary
54(1)
Suggested Readings
55(1)
Chapter References
55(2)
Chapter 3 Basic Principles of MR Signal Generation 57(32)
Quantitative Path
59(9)
Nuclear Spins
59(1)
Spins in an External Magnetic Field
60(3)
Magnetization of a Spin System
63(1)
Excitation of a Spin System and Signal Reception
64(2)
Relaxation Mechanisms of the MR Signal
66(1)
Conceptual Summary of MR Signal Generation
67(1)
Conceptual Path
68(19)
Common Terms and Notations
68(1)
Nuclear Spins
69(1)
Magnetic Moment
69(1)
Angular Momentum
70(1)
Spins in an External Magnetic Field
71(3)
Spin precession
72(2)
Energy Difference between Parallel and Antiparallel States
74(2)
Magnetization of a Spin System
76(2)
Excitation of a Spin System and Signal Reception
78(7)
Spin excitation
78(2)
Box 3.1 A Quantitative Consideration of the Rotating Reference Frame
80(3)
Signal reception
83(2)
Relaxation Mechanisms of a Spin System
85(2)
The Bloch Equation for MR Signal Generation
87(1)
Summary
87(1)
Suggested Readings
88(1)
Chapter 4 Basic Principles of MR Image Formation 89(34)
Conceptual Path
90(10)
Slice Selection
91(3)
Frequency Encoding
94(1)
Phase Encoding
95(2)
Summary of Image Formation (Conceptual Path)
97(3)
Box 4.1 An Example of Spatial Encoding
98(2)
Quantitative Path
100(20)
Analysis of the MR Signal
100(7)
Longitudinal magnetization (Mz)
102(1)
Transverse magnetization (Mxy)
103(3)
The MR signal equation
106(1)
Slice Selection, Spatial Encoding, and Image Reconstruction
107(11)
Slice selection
107(3)
Two-dimensional spatial encoding in k-space: Frequency and phase encoding
110(4)
Relationship between image space and k-space
114(3)
Converting from k-space to image space
117(1)
3-D Imaging
118(1)
Potential Problems in Image Formation
119(1)
Summary
120(1)
Suggested Readings
121(2)
Chapter 5 MRI Contrast Mechanisms and Acquisition Techniques 123(36)
Static Contrasts
124(12)
Proton-density contrast
126(2)
T1 contrast
128(3)
T2 contrast
131(2)
T2 contrast
133(1)
Chemical contrast
134(2)
Motion Contrasts
136(11)
MR angiography
136(2)
Diffusion-weighted contrast
138(2)
Perfusion-weighted contrast
140(7)
Box 5.1 Diffusion Tensor Imaging
142(5)
Image Acquisition Techniques
147(9)
Echo-planar imaging
148(2)
Spiral imaging
150(2)
Signal recovery and distortion correction for EPI and spiral images
152(1)
Parallel imaging
153(3)
Summary
156(1)
Suggested Readings
156(1)
Chapter References
157(2)
Chapter 6 From Neuronal to Hemodynamic Activity 159(52)
Information Processing in the Central Nervous System
162(8)
Neurons
162(1)
Glia
163(1)
Neuronal membranes and ion channels
164(3)
Synapses: Information transmission between neurons
167(1)
Synaptic potentials and action potentials
168(2)
Cerebral Metabolism: Neuronal Energy Consumption
170(4)
Adenosine triphosphate (ATP)
171(1)
The energy budget of the brain
172(2)
The Vascular System of the Brain
174(6)
Arteries, capillaries, and veins
175(2)
Arterial and venous anatomy of the human brain
177(2)
Microcirculation
179(1)
Blood Flow
180(12)
Control of blood flow
181(2)
Feedback and feedforward control of blood flow
183(3)
The neurovascular unit
186(1)
Pericytes
187(2)
Nitric oxide
189(1)
Vascular conducted response
189(3)
Box 6.1 Hemodynamic Balance: Push-Pull and Vascular Steal
190(2)
The Coupling of Blood Flow, Metabolism, and Neuronal Activity
192(14)
The oxygen-glucose index (OGI)
192(3)
Box 6.2 PET Imaging
193(2)
Explanations for the uncoupling of CBF, CMRQ2, and CMRglu
195(1)
Functional hyperemia redux
196(16)
Box 6.3 Primer on Neuroanatomy
198(8)
Summary
206(1)
Suggested Readings
206(1)
Chapter References
207(4)
Chapter 7 BOLD fMRI: Origins and Properties 211(60)
History of BOLD fMRI
212(4)
Discovery of BOLD contrast
213(3)
The Growth of BOLD fMRI
216(7)
Contributing factors
216(3)
Early fMRI studies
219(4)
Box 7.1 Functional Studies Using Contrast Agents
220(3)
The BOLD Hemodynamic Response
223(6)
The initial dip
225(4)
The Neural Correlates of BOLD Contrast
229(9)
Box 7.2 Sustained Negative BOLD Signals
230(8)
Spatial Resolution
238(7)
Spatial specificity in the vascular system
240(3)
What spatial resolution is needed?
243(2)
Temporal Resolution of fMRI
245(10)
What temporal resolution is needed?
248(2)
Effects of stimulus duration and timing
250(5)
Linearity of the Hemodynamic Response
255(9)
Properties of a linear system
256(2)
Evidence for rough linearity
258(2)
Challenges to linearity
260(1)
fMRI-adaptation
261(3)
Summary
264(1)
Suggested Readings
265(1)
Chapter References
266(5)
Chapter 8 Signal, Noise, and Preprocessing of fMRI Data 271(52)
Understanding Signal and Noise
272(6)
Signal and noise defined
273(4)
Box 8.1 Terminology of fMRI
274(3)
Functional SNR
277(1)
Effects of Field Strength on fMRI Data
278(5)
Field strength and raw SNR
278(1)
Field strength and spatial properties of activation
279(3)
Challenges of high-field fMRI
282(1)
Sources of Noise in fMRI
283(12)
Thermal noise
284(2)
System noise
286(1)
Motion and physiological noise
287(3)
Non-task-related neural variability
290(1)
Behavioral and cognitive variability in task Performance
290(5)
Box 8.2 Variability in the Hemodynamic Response over Subjects and Sessions
292(3)
Preprocessing
295(13)
Quality assurance
295(2)
Slice acquisition time correction
297(2)
Head motion: An overview
299(3)
Prevention of head motion
302(2)
Correction of head motion
304(2)
Distortion correction
306(2)
Functional-Structural Coregistration and Normalization
308(5)
Functional-structural coregistration
309(1)
Spatial normalization
310(3)
Temporal and Spatial Filtering
313(5)
Temporal filtering
314(1)
Spatial filtering
315(3)
Summary
318(1)
Suggested Readings
319(1)
Chapter References
320(3)
Chapter 9 Experimental Design 323(40)
Principles of Experimental Design
324(2)
Setting Up a Good Research Hypothesis
326(6)
Are fMRI data correlational?
328(1)
Confounding factors
329(3)
Good Practices in fMRI Experimental Design
332(1)
Blocked Designs
333(11)
Setting up a blocked design
333(7)
Box 9.1 Baseline Activation in fMRI: The Default Mode Network
336(4)
Advantages and disadvantages of blocked designs
340(4)
Event-Related Designs
344(14)
Principles of event-related fMRI
346(4)
Advantages of event-related designs
350(6)
Box 9.2 Efficient fMRI Experimental Design
352(4)
Mixed designs
356(2)
Summary
358(1)
Suggested Readings
359(1)
Chapter References
359(4)
Chapter 10 Statistical Analysis I: Basic Analyses 363(48)
Basic Statistical Tests
365(7)
Contrasts: Comparing experimental conditions
366(4)
Model-building: Predicting the fMRI signal from the experimental design
370(2)
Regression Analyses
372(16)
The general linear model: An overview
373(1)
Constructing a design matrix: Regressors of interest
374(6)
Box 10.1 Periodic Activation Evoked by Blocked Experimental Designs
376(4)
Constructing a design matrix: Nuisance regressors
380(2)
Modeling neuronal activity
382(1)
Modeling hemodynamic convolution
382(3)
Contrasts
385(2)
Assumptions of the general linear model
387(1)
Corrections for Multiple Comparisons
388(6)
Calculating the significance threshold
389(2)
Permutation testing
391(1)
Estimating the number of independent tests
392(1)
Cluster-based thresholding
393(1)
Region-of-Interest Analyses
394(3)
Intersubject Analyses
397(7)
Group and parametric effects
400(12)
Box 10.2 Reverse Inference
401(3)
Displaying Statistical Results
404(4)
Summary
408(1)
Suggested Readings
408(1)
Chapter References
409(2)
Chapter 11 Statistical Analysis II: Advanced Approaches 411(52)
Data Exploration Approaches
412(9)
Principal components analysis (PCA)
412(1)
Independent components analysis (ICA)
413(7)
Partial least squares (PLS)
420(1)
Between-Subjects Correlations
421(5)
Correlations evoked by interactions: Hyperscanning
422(1)
Correlations evoked by common experience
423(3)
Functional Connectivity Approaches
426(16)
From coactivation to connectivity: A conceptual overview
427(2)
Resting-state connectivity
429(4)
Box 11.1 Increasing the Scale of fMRI Research: The Human Connectome
431(2)
Psychophysiological interactions
433(2)
Inferring causality from fMRI data
435(5)
Combining fMRI and DTI
440(2)
Prediction Approaches
442(16)
Predicting variation among individuals
443(5)
Box 11.2 Rapid Analyses of fMRI Data: Real-Time fMRI
444(4)
Predicting variation in behavior
448(2)
Pattern classification using machine learning algorithms
450(4)
Capabilities and challenges of fMRI pattern classification
454(4)
Summary
458(1)
Suggested Readings
458(1)
Chapter References
459(4)
Chapter 12 Advanced fMRI Methods 463(22)
The Constant Pursuit of Spatial Resolution
464(8)
Ultrahigh-resolution structural MRI: Differentiating cortical layers
464(3)
High-resolution fMRI: Inferring causality
467(1)
Ultrahigh-resolution DTI delineates cortical columns
468(1)
Innovative array coils that enable high spatial resolution and fidelity
469(3)
The Constant Pursuit of High Temporal Resolution
472(4)
Compressed sensing
472(2)
Multi-band imaging
474(2)
Advanced fMRI Contrast Mechanisms
476(6)
Imaging with SPIO nanoparticles to enhance sensitivity
476(1)
Ion-gated contrast
477(2)
pH-dependent contrast
479(1)
Neuroelectromagnetic contrast
480(2)
Summary
482(1)
Suggested Readings
482(1)
Chapter References
483(2)
Chapter 13 Combining fMRI with Other Techniques 485(48)
Cognitive Neuroscience
485(3)
Strategies for research in cognitive neuroscience
487(1)
Manipulating Brain Function
488(16)
Direct cortical stimulation
488(4)
Transcranial direct current stimulation (tDCS)
492(1)
Transcranial magnetic stimulation (TMS)
493(3)
Brain lesions
496(3)
Combined lesion and fMRI studies
499(1)
Probabilistic brain atlases
500(2)
Brain imaging and genomics
502(2)
Measuring Brain Function
504(24)
Single-unit recording
504(7)
Box 13.1 Electrogenesis
506(5)
Properties of electric field potentials
511(1)
Localizing the neural generators of field potentials
512(1)
Intracranially recorded field potentials
513(4)
Box 13.2 Localization of Function Using Field Potential Recordings
515(2)
Scalp-recorded field potentials
517(4)
Box 13.3 Combining fMRI and EEG/ERP Techniques
519(2)
Magnetoencephalography (MEG)
521(2)
Using fMRI with non-human animals
523(5)
Summary
528(1)
Suggested Readings
529(1)
Chapter References
529(4)
Chapter 14 The Future of fMRI: Practical and Ethical Issues 533
Interpreting and Presenting fMRI Data
535(10)
Coverage of fMRI research in the popular media
536(5)
Box 14.1 Linking fMRI to Individual Differences: The Controversy about Circular Analyses
538(3)
Core principles for presenting fMRI research
541(4)
Conducting fMRI Research
545(10)
Proposing and approving fMRI research
545(3)
Ensuring the confidentiality of fMRI data
548(5)
Box 14.2 Incidental Findings in fMRI Research
549(4)
Safe conduct of fMRI studies
553(2)
Pregnancy testing in fMRI research
555(1)
Applying fMRI to New and Controversial Topics
555(13)
Reading minds
557(2)
Detecting lies
559(3)
Identifying traits
562(4)
Box 14.3 Why Biology Matters: The Case of Self-Control
564(2)
Advertising and marketing
566(2)
The Future of fMRI Research (and Your Role in It)
568(2)
Summary
570(1)
Suggested Readings
571(1)
Chapter References
571
Glossary G-1
Index I-1
Scott A. Huettel is the Jerry G. and Patricia Crawford Hubbard Professor and Chair of the Department of Psychology and Neuroscience at Duke University, with secondary appointments in the Departments of Psychiatry and Neurobiology. His research uses a combination of behavioral, physiological, and neuroscience techniques to discover the neural mechanisms that support cognition, with a focus on decision-making. Much of his research--which includes collaborations with neuroscientists, psychologists, behavioral economists, and business and medical faculty--falls within the emerging interdiscipline of neuroeconomics. He is also a co-editor of Principles of Cognitive Neuroscience (2nd edition, 2013). Allen W. Song is Director of the Brain Imaging and Analysis Center and Professor in the Departments of Radiology, Psychiatry, Neurobiology, and Biomedical Engineering at Duke University.