Systems Neuroscience (eBook)

Albert Cheung-Hoi YU, Lina Li (Herausgeber)

eBook Download: PDF

2018
XII, 307 Seiten
Springer International Publishing (Verlag)
978-3-319-94593-4 (ISBN)

Infos

This edition of Advances in Neurobiology brings together experts in the emerging field of Systems Neuroscience to present an overview of this area of research. Topics covered include: how different neural circuits analyze sensory information, form perceptions of the external world, make decisions, and execute movements; how nerve cells behave when connected together to form neural networks; the relationship between molecular and cellular approaches to understanding brain structure and function; the study of high-level mental functions; and studying brain pathologies and diseases with Systems Neuroscience. A hierarchy of biological complexity arises from the genome, transcriptome, proteome, organelles, cells, synapses, circuits, brain regions, the whole brain, and behaviour. The best way to study the brain, the most complex organ in the body composed of 100 billion cells with trillions of interconnections, is with a Systems Biology approach. Systems biology is an inter-disciplinary field that focuses on complex interactions within biological systems to reveal 'emergent properties' - properties of cells and groups of cells functioning as a system whose actual and theoretical description is only possible using Systems Biology techniques.

Inhalt

Preface 5
Contents 7
Contributors 9
Chapter 1: Neuronal Bases of Systemic Organization of Behavior 13
1.1 The Systems View of Neuroscience 13
1.1.1 Goal-Directed Behavior and the Result 13
1.1.2 Activity Paradigm 15
1.1.3 Active Neuron 16
1.2 The Formation of Memory during Learning and Systemic Structure of Behavior 17
1.2.1 Systemogenesis 17
1.2.2 The Formation of Neuronal Specializations during Individual Development Continues Phylogenesis 19
1.2.3 The Patterns of Neuronal Specializations in Different Species 19
1.2.4 The Traditional View of Memory Consolidation 22
1.2.5 The Systems View of Memory Consolidation 23
1.3 Fundamentals of Learning within the Systems Perspective 27
1.3.1 Memory Formation Starts with Mismatch 27
1.3.2 From Mismatch through Match to Consolidation 28
1.3.3 “Altruistic Suicide” 33
1.3.4 Long-Term Potentiation: Traditional and Systems Approach 35
1.4 The History of Memory Formation and the Memory Structure Are Interrelated 36
1.5 Conclusion 37
References 39
Chapter 2: Neural Circuits Mediating Fear Learning and Extinction 46
2.1 Introduction 46
2.2 Fear Conditioning and Extinction 47
2.3 Neural Circuits of Fear and Extinction 48
2.4 Anatomy 49
2.5 Functional Roles 51
2.5.1 The Amygdala 51
2.5.2 Medial Prefrontal Cortex 52
2.5.3 Hippocampus 54
2.6 Conclusions 56
References 56
Chapter 3: The Hippocampal Ensemble Code for Spatial Navigation and Episodic Memory 60
3.1 Introduction 60
3.2 Discovery of Place Cells 61
3.3 Formation of Place Fields 62
3.4 Spatial Information of Place Fields 65
3.5 Changes in the Location and Firing Rates of a Place Field 66
3.6 Place Field Remapping in Terms of Past and Future Locations 68
3.7 Variation of Location and Firing Rate of the Place Field in Relation to Episodes 69
3.8 Context-Dependent Encoding Within the Place Field 71
3.9 Hippocampal Place Cells Hierarchically Organize Contexts in the Episodic-Like Memory Trace 72
3.10 Reactivation of Place Cell Activity While an Animal Briefly Pauses 74
3.11 Summary 77
References 79
Chapter 4: Context-Dependent Adjustments in Executive Control of Goal-Directed Behaviour: Contribution of Frontal Brain Areas to Conflict-Induced Behavioural Adjustments in Primates 82
4.1 Introduction 82
4.2 Conflict-Induced Behavioural Adjustment 84
4.2.1 Conflict Tasks Used in Psychophysical Studies in Humans 84
4.2.2 Neural Substrate and Underlying Mechanisms of Conflict-Induced Behavioural Modulations 85
4.2.2.1 Imaging Studies in Humans 85
4.2.2.2 Studies in Non-Human Primates 87
4.3 Conclusion 91
References 92
Chapter 5: Synaptic Excitatory-Inhibitory Balance Underlying Efficient Neural Coding 95
5.1 Introduction 95
5.2 E/I Balance Is Ubiquitous in Cortical Circuits 96
5.3 Mechanisms to Achieve E/I Balance 98
5.4 E/I Balance and Information Representation 100
5.4.1 Irregular Spike Trains and Global E/I Balance 100
5.4.2 Sparse Coding, E/I Balance and Energy Efficiency 101
5.4.3 Decorrelation and E/I Balance 103
5.5 E/I Balance and Information Propagation 104
5.6 Conclusion 106
References 107
Chapter 6: Mapping Molecular Datasets Back to the Brain Regions They are Extracted from: Remembering the Native Countries of Hypothalamic Expatriates and Refugees 111
6.1 Introduction 115
6.1.1 Summary and Rationale 115
6.1.2 Topic and Organization 115
6.2 Why Does Location Matter? 116
6.3 Historical Antecedents 117
6.3.1 Heuristic Entry Points to Relevant History 117
6.3.2 Sampling at the Level of the Single Cell 118
6.3.3 Sampling at the Level of Isolated Tissues 120
6.4 Molecular Mining of the Hypothalamus 120
6.4.1 Early Studies 120
6.4.2 Studies of the Hypothalamus Using High Throughput Methods 121
6.4.2.1 Whole Brain Extraction and Multi-Region Comparison Studies 123
6.4.2.2 Molecular Extraction from Whole Hypothalamus 151
6.4.2.3 Molecular Extraction from the Hypothalamic Circadian System 153
6.4.2.4 Molecular Extraction from the Hypothalamo-Neurohypophysial System 154
6.4.2.5 Molecular Extraction from the Arcuate Hypothalamic Nucleus (ARH) 155
6.4.2.6 Molecular Extraction from Other Hypothalamic Sub-Regions (LHA, VMH) 156
6.4.3 A Note About “Hypothalamic-Derived” Molecules 158
6.5 Laser-Capture Microdissection Studies: Methodological Considerations 158
6.5.1 LCM for General Sampling of Brain Regions 159
6.5.2 Immuno-LCM 160
6.5.2.1 Advantages 160
6.5.2.2 Challenges and Pitfalls 161
6.5.3 Use of LCM to Target Cells Expressing Fluorescent Reporter Molecules 162
6.5.3.1 Advantages 162
6.5.3.2 Challenges and Pitfalls 163
6.5.4 RNA Integrity 163
6.6 Anchoring Molecular Information to Their Native Regions Using Digital Atlas Maps 164
6.6.1 Documenting the Native Substrate Before Extraction 164
6.6.2 Mapping to Standardized Atlases 165
6.7 The Benefits of Mapping Native Substrates and Anchoring Datasets 168
6.7.1 Data Integration 168
6.7.2 Data Migration 170
6.7.3 Data Refinement 171
6.8 Concluding Remarks and Future Directions 172
6.8.1 Future Directions in Data Management 173
6.8.2 Future Directions in Imaging 173
6.8.3 Future Directions in Molecular Analysis 175
6.8.4 Future Directions in Mapping 176
6.8.5 Final Remarks 176
References 177
Chapter 7: Genome-Scale Brain Metabolic Networks as Scaffolds for the Systems Biology of Neurodegenerative Diseases: Mapping Metabolic Alterations 204
7.1 Introduction 204
7.2 Omics Data Analysis for Neurodegenerative Diseases: Metabolism Perspective 205
7.2.1 Alzheimer’s Disease (AD) 207
7.2.2 Parkinson’s Disease (PD) 209
7.2.3 Other Disorders 211
7.3 Genome-Scale Metabolic Network Reconstructions for Brain 212
7.3.1 Analysis of Neurodegenerative Diseases via Constraint-Based Modelling of Genome-Scale Reconstructions 215
7.3.2 Analysis of Neurodegenerative Diseases via Graph-Based Integration of Genome-Scale Reconstructions and Omics Data 218
7.4 Final Remarks 221
References 222
Chapter 8: Synaptic Plasticity and Synchrony in the Anterior Cingulate Cortex Circuitry: A Neural Network Approach to Causality of Chronic Visceral Pain and Associated Cognitive Deficits 227
8.1 Brain Targets for Visceral Pain “Memory” Process in the Visceral Hypersensitive State 228
8.1.1 Viscerally Hypersensitive Rat Model 229
8.1.2 Enhanced ACC Nociceptive Transmission in Viscerally Hypersensitive Rats 229
8.1.3 N-Methyl-D-Aspartate (NMDA) Receptor Mediate ACC Synaptic Responses After the Induction of Visceral Hypersensitivity 231
8.1.4 The ACC Plays a Critical Role in the Modulation of Behavioral Visceral Pain Responses in VH Rats 232
8.1.5 Up-Regulation and Phosphorylation of CaMKII Post-Synaptic Binding to NR2B Receptors Contributes Visceral Pain 234
8.1.6 Perigenual ACC (pACC) Are Necessary for the “Aversiveness” of Visceral Nociceptor Stimulation 237
8.2 ACC Synaptic Plasticity Mediates Learning and Long-Lasting Functional Visceral Pain Memory 237
8.2.1 Visceral Hypersensitivity Is Associated with Alterations of the Properties of Synaptic Plasticity in the ACC 238
8.2.2 Visceral Hypersensitivity vs ACC Synaptic Plasticity: Chicken or Egg? 239
8.3 Visceral Pain and Cognitive Deficits 239
8.3.1 Visceral Hypersensitivity Affects Decision-Making Ability in Rats 240
8.4 ACC Neuronal Spike Field Phase Locking and Synchrony Cross Areas Associated Involved in the Processing of Chronic Visceral Pain 241
8.4.1 Tight Coordination of Spike Timing with the Local Theta Oscillation Is a Key Index for Predicting Successful Cognitive Function 242
8.4.2 Interruption of Amygdala-ACC Integrative Coordination Contribute Causally to Cognitive Dysfunctions in Chronic Pain States 244
8.5 Vagus Nerve Stimulation Modulates Neuronal Spike Field Phase Locking and Synchrony Cross Areas Associated with Facilitation of Decision-Making in Rats 246
8.5.1 Vagal Nerve Stimulation Enhances Cognitive Performance and Facilitate Decision Making 246
8.5.2 Vagal Nerve Stimulation Regulates LFP and Spike Phases, Enhances Spike-Phase Coherence Between Key Brain Areas Involved in Cognitive Performance 247
8.5.3 Final Remark 248
References 249
Chapter 9: Large De Novo Microdeletion in Epilepsy with Intellectual and Developmental Disabilities, with a Systems Biology Analysis 254
9.1 Introduction 254
9.2 Large De Novo Rare Microdeletion Is an Important Pathological Cause of Epilepsy with ID/DD 255
9.2.1 Ethics and Patients 255
9.2.2 CNV Detection by Array CGH 256
9.2.3 The Loci of Microdeletions 256
9.3 Pathogenic Mechanism Analysis 258
9.4 Systems Biological Analysis 266
References 267
Chapter 10: Using Systems Biology and Mathematical Modeling Approaches in the Discovery of Therapeutic Targets for Spinal Muscular Atrophy 274
10.1 Introduction 275
10.2 Spinal Muscular Atrophy 275
10.3 SMN2 as an Endogenous Genetic Modifier of SMA Phenotype 276
10.4 Regulation of SMN2 Expression by cAMP Signaling 278
10.5 Mathematical Modeling of Gene Expression 279
10.6 Overall Strategy for Building Mathematical Models of Gene Expression 280
10.7 Mathematical Modeling of SMN2 Regulation by cAMP Signaling 282
10.8 Conclusions and Future Directions 283
References 285
Chapter 11: Not Cure But Heal: Music and Medicine 289
11.1 Introduction 289
11.2 Musical Behavior: Universal, Ancient and Precocious 291
11.3 Music-and-Movement Therapy 293
11.4 Music-and-Emotion Therapy 295
11.4.1 Music Structure, Music Emotions and Music Therapy 299
11.4.2 Music, Emotional Communication and Socio-Cognitive Therapy 303
11.5 Music Cognition and Intervention in Learning Disabilities 305
11.6 Conclusion 307
References 307

Produkt-Details

• Erscheint lt. Verlag: 17.10.2018
• Reihe/Serie: Advances in Neurobiology
• Reihe/Serie: Advances in Neurobiology
• Zusatzinfo: XII, 307 p. 51 illus., 32 illus. in color.
• Verlagsort: Cham
• Sprache: englisch
• Themenwelt: Medizin / Pharmazie ► Studium
• Schlagworte: Circuits • functional genomics • neural diseases • Neural networks • systems biology
• ISBN-10: 3-319-94593-9 / 3319945939
• ISBN-13: 978-3-319-94593-4 / 9783319945934