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Introduction to human neuroimaging / Hans Op de Beeck, Chie Nakatani. -- Cambridge, United Kingdom ; New York, NY : Cambridge University Press, 2019. – (64.118/B414) |
Contents
List of
Figures
Preface
1 Introduction and Overview
1.1 Brain Enthusiasm: The Relevance of
Distinguishing Fact from Fiction
1.2 The Basis of Neural Signals
1.3 A Short Overview of Methods in Human
Neuroscience
Part I
Structural Neuroimaging
2 The Physics behind Magnetic Resonance Imaging
(MRI)
2.1 The Effect of Magnetic Fields on the Human
Body
2.2 From Resonance to Imaging
2.3 How Do These Physical Principles Give Rise to
an Image with Anatomical Structure?
2.4 The Hardware of a Scanner
2.5 Parameters That Are Chosen by the User
3 Structural Imaging Methods
3.1 Structural T1-Weighted MRI
3.2 Diffusion Tensor Imaging (DTI)
3.3 Magnetic Resonance Spectroscopy (MRS)
Part II
Hemodynamic Neuroimaging
4 Hemodynamic Imaging Methods
4.1 Hemodynamics and Its Relationship to Neural
Activity
4.2 Functional Magnetic Resonance Imaging (fMRI)
4.3 Positron Emission Tomography (PET)
4.4 Functional Near-Infrared Spectroscopy (fNIRS)
4.5 A Comparison of Research with fMRI, PET, and
fNIRS
5 Designing a Hemodynamic Imaging Experiment
5.1 Think Before You Start an Experiment
5.2 Which Conditions to Include: The Subtraction
Method
5.3 How to Present the Conditions: The Block
Design
5.4 The Event-Related Design
5.5 The Baseline or Rest Condition
5.6 Task and Stimuli in the Scanner
6 Image
Processing
6.1 Software Packages
6.2 Properties of the Images
6.3 Preprocessing Step 1: Slice Timing
6.4 Preprocessing Step 2: Motion Correction
6.5 Preprocessing Step 3: Coregistration
6.6 Preprocessing Step 4: Normalization
6.7 Preprocessing Step 5: Spatial Smoothing
7 Basic Statistical Analyses
7.1 Statistical Analyses: The General Linear
Model
7.2 Determining Significance and Interpreting It
8 Advanced Statistical Analyses
8.1 Functional Connectivity: Designs and Analyses
8.2 Multi-voxel Pattern Analyses
8.3 Functional MRI Adaptation
Part III
Electrophysiological Neuroimaging
9
Electromagnetic Field of the Brain
9.1 Electrophysiological Activity of the Brain
9.2 Electromagnetic Field Signals
9.3 Brain Dynamics vs. Mind Dynamics
10
Electroencephalography and Magnetoencephalography
10.1
Electroencephalography (EEG)
10.2
Magnetoencephalography (MEG)
10.3
Comparison between EEG and MEG
11 Basic
Analysis of Electrophysiological Signals
11.1
Preprocessing
11.2
Main Signal Processing
11.3 Statistical
Tests
12
Advanced Data Analysis
12.1
Short Time Fourier Transform and Wavelet Transform
12.2
Phase Analysis
12.3
Autoregression and Granger Causality
Part IV
Complementary Methods
13
Multi-modal Imaging
13.1 The Spatial and Temporal Unfolding of Visual
Category Representations
13.2 Simultaneous Application of EEG and fMRI
13.3 M/EEG Source Localization
13.4 Differentiating between Representational and
Access Theories of Disorders
13.5 Clinical Diagnostics with Multi-modal Imaging
14
Causal Methods to Modulate Brain Activity
14.1 Microstimulation and Deep Brain Stimulation
14.2 Focused Ultrasound Stimulation (FUS)
14.3 Transcranial Magnetic Stimulation (TMS)
14.4 Transcranial Current Stimulation (TCS)
Glossary
References
Index
