Mood Disorders: Brain Imaging and Therapeutic Implications

Description

Mood disorders such as depression and bipolar disorder are common mental illnesses, affecting millions of patients worldwide. The application of newly available brain imaging methods to the study of mood disorders holds substantial promise in uncovering the brain mechanisms affected in these illnesses. This comprehensive and authoritative text features contributions from leading international experts, providing easily accessible information on the study of the brain mechanisms involved in the causation of mood disorders and the available treatments. Topics covered include the potential of magnetoencephalography (MEG), neuroimaging brain inflammation in depression, electrophysiology studies in mood disorders, and the applications of machine learning, filling an important gap in available neuropsychiatric literature and highlighting new developments. An invaluable resource for practitioners in the fields of psychiatry, neurology, primary care medicine, and related mental health professions, as well as researchers, students, graduate and post-graduate trainees. Half title Title page Imprints page Contents Contributors Preface Section 1 General Chapter 1 Brain Imaging Methods in Mood Disorders 1.1 Introduction 1.2 Clinical Features 1.3 Etiology and Pathophysiology of Mood Disorders 1.4 Neuroimaging Techniques 1.5 Clinical Applications of Neuroimaging 1.6 Conclusion References Section 2 Anatomical Studies Chapter 2 Neuroanatomical Findings in Unipolar Depression and the Role of the Hippocampus 2.1 Introduction 2.2 Structural Magnetic Resonance Imaging in Major Depressive Disorders 2.3 Postmortem Studies in Depression 2.4 Evidence of Structural Changes in Depression Following Prolonged Stress, and the Role of the Hippocampus and Hypothalamic–Pituitary–Adrenal Axis 2.5 Hippocampal Abnormalities: State versus Trait Marker for a Depressive Episode 2.6 Neuroanatomical Circuitry Involved in Major Depression References Chapter 3 Neuroanatomical Findings in Bipolar Disorder 3.1 Introduction 3.2 Case-Control Studies 3.2.1 Lateral Ventricles 3.2.2 Subcortical Structures 3.2.3 Cortical Regions 3.2.4 White Matter 3.2.5 Diffusion Tensor Imaging 3.2.6 Structural Network Findings 3.3 Bipolar Disorder Compared with Schizophrenia and Major Depressive Disorder 3.4 Sources of Heterogeneity 3.4.1 Psychotropic Medication 3.4.2 Demographic and Clinical Variables 3.4.3 Longitudinal 3.5 Conclusions References Chapter 4 Neuroimaging Biomarkers in Pediatric Mood Disorders 4.1 Aberrant Responses to Stress and Reward Reward processing in pediatric BD. Reward processing in pediatric MDD. 4.2 Maladaptive Developmental Trajectories 4.3 Implications of Neurobiological Markers for Treatment 4.4 Pediatric BD Treatment Implications 4.5 Pediatric MDD Treatment Implications 4.6 Conclusion References Section 3 Functional and Neurochemical Brain Studies Chapter 5 Brain Imaging of Reward Dysfunction in Unipolar and Bipolar Disorders 5.1 Introduction 5.2 Neurobiology of Reward Processing and Its Components 5.3 Major Depressive Disorder 5.3.1 Neural Correlates of Reward Anticipation 5.3.2 Neural Correlates of Reward Consumption 5.3.3 Neural Correlates of Reward Learning 5.4 Is Reward Dysfunction a Potential Endophenotype of MDD? 5.5 Bipolar Disorder 5.5.1 Neural Correlates of Reward Anticipation 5.5.2 Neural Correlates of Reward Consumption 5.6 Heritability of Reward Dysfunction in BD 5.7 Studies Comparing MDD to BD 5.8 Future Directions: Transdiagnostic Mechanisms and Multimodal Imaging 5.9 Conclusions References Chapter 6 Resting-State Functional Connectivity in Unipolar Depression 6.1 Background 6.2 MRI Neurocircuitry Findings 6.2.1 Limbic-Cortical-Striatal-Pallidal-Thalamic Circuit 6.2.2 Functional Connectivity Findings Related to Suicide in Depression 6.3 Core Brain Networks in Depression 6.3.1 Default Mode Network 6.3.2 Central Executive Network 6.3.3 Salience Network 6.3.4 Between-Network Connectivity 6.4 Functional Connectomics in Depression 6.5 Conclusions *Corresponding author Acknowledgment References Chapter 7 Functional Connectome in Bipolar Disorder 7.1 Introduction 7.2 The Functional Connectome 7.2.1 Methods to Study the Functional Connectome in Brain Imaging Studies Task-Based Functional Connectivity: Resting-State Low-Frequency BOLD Fluctuations Correlation (Connectivity): Seed-Based Functional Connectivity Analysis: Independent Component Analysis (ICA): Graph-Theory Analysis: 7.2.2 The Functional Connectome in Bipolar Disorder 7.2.2.1 Study Designs for Investigation of Functional Connectome in Bipolar Disorder 7.2.2.2 ROI Based Analysis 7.2.2.2a Cortico-Limbic Connectivity Task-Related Cortico-Limbic Psychophysiological Interaction (PPI) Studies: Resting-State Reference ROI-Based Cortico-Limbic Connectivity Studies: 7.2.2.2b Cortico-Cortical Connectivity Task-Related Cortico-Cortical Psychophysiological Interaction (PPI) Studies: Resting-State Reference ROI-Based Cortico-Cortical Functional Connectivity Studies: 7.2.2.2c Intrinsic Subcortical Connectivity Resting-State Reference ROI-Based Subcortical Functional Connectivity Studies: 7.2.2.3 Independent Component Analysis Studies 7.2.2.4 Graph-Theory Network Properties Studies 7.2.2.5 Functional Connectome in Subjects At-Risk for Bipolar Disorder Task-Related Psychophysiological Interaction (PPI) High-Risk Studies: Resting-State Functional Connectivity High-Risk Studies: Graph-Theory Analysis High-Risk Studies: 7.2.2.6 Treatment Effect on the Functional Connectome in BD 7.2.2.7 Psychotic Bipolar Disorder 7.3 Discussion References Chapter 8 Magnetic Resonance Spectroscopy Investigations of Bioenergy and Mitochondrial Function in Mood Disorders Abbreviations 8.1 Introduction 8.2 Magnetic Resonance Spectroscopy and Brain Bioenergetics 8.3 Major Depressive Disorder 8.4 Bipolar Disorder 8.5 Conclusion References Chapter 9 Imaging Glutamatergic and GABAergic Abnormalities in Mood Disorders 9.1 Background 9.2 Glutamate 9.3 GABA 9.4 Magnetic Resonance Spectroscopy 9.5 Major Depressive Disorder and Glutamate 9.6 Bipolar Disorder and Glutamate 9.7 Major Depressive Disorder and GABA 9.8 Bipolar Disorder and GABA 9.9 Concluding Remarks and Clinical Relevance References Chapter 10 Neuroimaging Brain Inflammation in Mood Disorders 10.1 Introduction 10.2 Rationale for Neuroimaging Inflammation in Mood Disorders 10.3 Translocator Protein Imaging 10.4 Novel PET Imaging Probes of Neuroinflammation 10.5 Conclusions References Section 4 Novel Approaches in Brain Imaging Chapter 11 Imaging Genetic and Epigenetic Markers in Mood Disorders 11.1 Genome-Wide Association Studies 11.2 Polygenic Risk Score 11.3 Candidate Gene Studies 11.4 Epigenetics References Chapter 12 fMRI Neurofeedback as Treatment for Depression 12.1 Introduction 12.2 The Neural Basis of Neurofeedback 12.3 fMRI-NF Neurofeedback Treatments for Depression 12.3.1 Mechanisms Shared across fMRI-NF Neurofeedback Treatments for Depression 12.3.1.1 Self-regulation 12.3.1.2 Reinforcement and Regulation of Neural States 12.3.2 Different fMRI-NF Neurofeedback Approaches in Depression 12.3.2.1 Emotion Regulation: Positive Affect General Positive Affect Saliency of Positive Affective Experiences 12.3.2.2 Emotion Regulation: Negative Affect General Negative Affect Saliency of Negative Affective Experiences 12.3.2.3 Connectivity Neurofeedback 12.4 Discussion References Chapter 13 Functional Near-Infrared Spectroscopy Studies in Mood Disorders 13.1 Introduction 13.2 Principle of Near-Infrared Spectroscopy 13.3 Application to Mood Disorders 13.3.1 Major Depressive Disorder versus Healthy Subjects 13.3.1.1 VFT, Letter Version 13.3.1.2 Other Tasks 13.3.2 Bipolar Disorder versus Healthy Subjects 13.3.3 Comparisons with Mood Disorders and Other Psychiatric Illnesses 13.4 Conclusions and Future Directions References Chapter 14 Electrophysiological Biomarkers for Mood Disorders 14.1 Introduction 14.1.1 Event-Related Potentials 14.1.2 P300 14.1.3 Diagnosis 14.1.4 Treatment Prediction 14.2 Error-Related Negativity 14.2.1 Diagnosis 14.2.2 Treatment Prediction 14.3 Loudness Dependence of the Auditory Evoked Potential 14.3.1 Diagnosis 14.3.2 Treatment Prediction 14.3.2.1 Quantitative EEG 14.4 Alpha Activity 14.4.1 Diagnosis 14.4.2 Treatment Prediction 14.5 Theta Activity 14.5.1 Diagnosis 14.5.2 Treatment Prediction 14.6 Gamma Activity 14.6.1 Diagnosis 14.6.2 Treatment Prediction 14.7 Limitations and Recommendations to the Field References Chapter 15 Magnetoencephalography Studies in Mood Disorders 15.1 Introduction to Magnetoencephalography 15.2 MEG in Mood Disorders 15.3 Sensory Evoked Fields 15.3.1 Motor and Somatosensory Evoked Fields 15.3.2 Auditory Evoked Fields 15.4 Emotional Paradigms 15.4.1 Evoked Responses to Affective Stimuli 15.4.2 Induced Oscillatory Responses to Affective Stimuli 15.4.3 Other Cognitive Tasks 15.5 Resting-State MEG 15.5.1 Spectral Power 15.5.2 Nonlinear Measures 15.5.3 Connectivity 15.6 MEG and Neuromodulation 15.7 Conclusions Acknowledgments References Chapter 16 An Overview of Machine Learning Applications in Mood Disorders 16.1 Machine Learning: An Answer to Historic Challenges in Psychiatry? 16.2 Machine Learning Techniques 16.2.1 Supervised ML 16.2.2 Unsupervised Learning 16.2.3 Reinforcement Learning 16.2.4 Selection of Algorithm Training and Validation Samples 16.2.5 Feature and Data Dimensionality Reduction 16.2.6 Model Training and Parameter Optimization 16.3 Applications of Machine Learning Techniques to Neuroimaging and Clinical Data in Mood Disorders 16.3.1 Diagnostic Classification of Mood Disorders, Decoding Clinical Variables, Identification of Unique Disease Subtypes and Supporting Mechanistic Understanding 16.3.2 Prediction of Treatment Response 16.3.3 Prediction of Other Clinical Outcomes Such As Suicide, Medication Side Effects and Clinical Staging 16.4 Conclusion 16.4.1 Interpretability of Machine Learning Models and Variability in Implementations 16.4.2 Lack of Standards and Other Issues Around Ethics References Section 5 Therapeutic Applications of Neuroimaging in Mood Disorders Chapter 17 Effects of Lithium on Brain Structure in Bipolar Disorder 17.1 Introduction 17.2 Magnetic Resonance Imaging Studies 17.3 Mechanisms of Brain Changes Associated with Lithium Treatment 17.4 Brain-Derived Neurotrophic Factor 17.5 Hippocampal Subregion Neuroplasticity 17.6 Summary and Future Directions References Chapter 18 Molecular Imaging of Dopamine and Antipsychotics in Bipolar Disorder 18.1 Introduction 18.2 Dopamine and Bipolar Disorder 18.3 The Use of Antipsychotics in Bipolar Disorder 18.3.1 Acute Treatment of Mania 18.3.2 Acute Treatment of Depression 18.3.3 Maintenance Treatment 18.4 Dopamine Synthesis and Metabolism 18.5 Molecular Imaging of the Dopamine System 18.5.1 Presynaptic System 18.5.2 Extra-Striatal Imaging of the Dopamine System 18.6 Molecular Imaging of the Dopamine System in Bipolar Disorder 18.6.1 Euthymic States 18.6.2 Bipolar Depression 18.6.3 Mania 18.6.4 Bipolar Psychosis 18.7 What is the Mechanism of Antipsychotic Response in Bipolar Disorder? 18.8 Future Directions Acknowledgments References Chapter 19 Brain Imaging and the Mechanisms of Antidepressant Action 19.1 Introduction 19.2 Treatments in Context: A Short Account of the Neural Basis for Depression 19.3 An Impact of AD on the Brain 19.3.1 Impact of “Classical” Antidepressant Medications 19.3.2 Structural Effects of “Typical” AD Actions 19.3.3 Focus on Brain Connectivity 19.3.4 “Bottom-Up” or “Top-Down” Effect? 19.3.5 New Antidepressant Drugs: Ketamine 19.3.6 A Note on Ligand PET Studies 19.4 Understanding Finer-Grained Aspects of Antidepressant Action 19.4.1 The Role for Negative Bias Attenuation and Cognitive Neuropsychological Model 19.4.2 Different Drugs, Different Patterns of Neural Change? 19.4.3 Importance of Additional Factors for Antidepressant Action 19.4.4 Effect of a Single and Repeated Doses 19.5 Final Remarks References Chapter 20 Neuroimaging Studies of Effects of Psychotherapy in Depression 20.1 Introduction 20.2 Literature Search 20.3 Effects of Psychotherapy on the Brain in Depression 20.3.1 fMRI 20.3.2 PET and SPECT 20.3.3 MRS 20.4 Imaging as a Predictor of Psychotherapy Response 20.4.1 fMRI 20.4.2 PET 20.4.3 Structural MRI and EEG 20.5 Discussion 20.6 Final Conclusions References Index