From Molecules to Networks (eBook)

Front Cover 1
From Molecules to Networks 4
Copyright Page 5
Table of Contents 6
Contributors 8
Preface to the Second Edition 10
Preface to the First Edition 11
Chapter 1: Cellular Components of Nervous Tissue 12
Neurons 12
Neuroglia 18
Cerebral Vasculature 25
References 28
Suggested Readings 28
Chapter 2: Subcellular Organization of the Nervous System: Organelles and Their Functions 30
Axons and Dendrites: Unique Structural Components of Neurons 30
Protein Synthesis in Nervous Tissue 35
Cytoskeletons of Neurons and Glial Cells 43
Molecular Motors in the Nervous System 49
Building and Maintaining Nervous System Cells 53
References 58
Chapter 3: Energy Metabolism in the Brain 60
Major Pathways of Brain Energy Metabolism 1
Substrates, Enzymes, Pathway Fluxes, and Compartmentation 83
Imaging Functional Metabolic Activity in Living Brain 88
Pathophysiological Conditions Disrupt Energy Metabolism 102
Roles of Nutrients and Metabolites in Regulation of Specific Functions and Overall Metabolic Economy 108
Metabolomics, Transcriptomics, and Proteomics 110
Summary 114
Acknowledgments 114
References 114
Literature References 115
Chapter 4: Electrotonic Properties of Axons and Dendrites 122
Toward a Theory of Neuronal information Processing 122
Basic Tools: Cable Theory and Compartmental Models 123
Spread of Steady-State Signals 123
Spread of Transient Signals 128
Electrotonic Properties Underlying Propagation in Axons 130
Electrotonic Spread in Dendrites 132
Dynamic Properties of Passive Electrotonic Structure 136
Relating Passive to Active Potentials 140
References 142
Chapter 5: Membrane Potential and Action Potential 144
The Membrane Potential 145
The Action Potential 150
References 166
Chapter 6: Molecular Properties of Ion Channels 170
Families of Ion Channels 170
Channel Gating 175
Ion Permeation 180
Ion Channel Distribution 184
Summary 187
References 187
Chapter 7: Dynamical Properties of Excitable Membranes 192
The Hodgkin-Huxley Model 192
A Geometric Analysis of Excitability 210
References 224
Chapter 8: Release of Neurotransmitters 228
Organization Of The Chemical Synapse 228
Excitation-Secretion Coupling 234
The Molecular Mechanisms of the Nerve Terminal 239
Quantal Analysis 252
Short-Term Synaptic Plasticity 266
References 269
Chapter 9: Pharmacology and Biochemistry of Synaptic Transmission: Classical Transmitters 278
Diverse Modes of Neuronal Communication 278
Chemical Transmission 279
Classic Neurotransmitters 283
Summary 308
References 308
Chapter 10: Nonclassic Signaling in the Brain 312
Peptide Neurotransmitters 312
Neurotensin as an Example of Peptide Neurotransmitters 318
Unconventional Transmitters 320
Synaptic Transmitters in Perspective 329
References 329
Chapter 11: Neurotransmitter Receptors 332
Ionotropic Receptors 332
G-Protein-Coupled Receptors 354
References 366
Chapter 12: Intracellular Signaling 370
Signaling Through G-Protein-Linked Receptors 370
Modulation of Neuronal Function by Protein Kinases and Phosphatases 384
References 397
Chapter 13: Regulation of Neuronal Gene Expression and Protein Synthesis 402
Intracellular Signaling Affects Nuclear Gene Expression 402
Role of cAMP and Ca21 in the Activation Pathways of Transcription 412
Summary 419
References 420
Chapter 14: Modeling and Analysis of Intracellular Signaling Pathways 424
Intracellular Transport of Signaling Molecules Can Be Modeled at Several Levels of Detail 426
Standard Equations Simplify Modeling of Enzymatic Reactions, Feedback Loops, and Allosteric Interactions 431
Positive and Negative Feedback Can Support Complex Dynamics of Biochemical Pathways 433
Model Dynamics should usually be robust to parameter variation 438
Parameter Uncertainties Imply the Majority of Models are Qualitative, Not Quantitative, Descriptions 440
Separation of Fast and Slow Processes to Simplify Models 441
Models Help to Analyze Metabolic Flux Regulation 441
Special Modeling Techniques are Required if Enzymes are Organized in Macromolecular Complexes 442
Stochastic Fluctuations in Molecule Numbers Influence the Dynamics of Biochemical Reactions 443
Genes can be Organized into Networks that are Activated by Signaling Pathways 444
Methods Exist to Model Gene Networks at Very Different Levels of Detail 446
Gene Network Models Suggest that Feedback Loops and Protein Dimerization can Generate Complex Dynamics 447
Random Fluctuations in Molecule Numbers can Strongly Influence Genetic Regulation 451
Summary 452
References 452
Chapter 15: Connexin- and Pannexin-Based Channels in the Nervous System: Gap Junctions and More 456
Cell Interactions in the Nervous System: The Larger Picture 456
General Properties and Structure of Gap Junction Channels and Hemichannels 456
Connexins in CNS Ontogeny 460
Connexins in Neurons of the Adult CNS 461
Astroglial Connexins 465
Connexins in Oligodendrocytes 468
Connexins in Microglia 468
Connexins in the Blood Brain Barrier (BBB) 468
Connexins in Ependimal Cells and Leptomeningeal Cells 469
Pattern of Pannexin Localization in Brain Cells 469
Gap Junction Channels and Hemichannels in Acquired and Genetic Pathologies of the CNS 470
Summary and Perspective 472
References 473
Chapter 16: Postsynaptic Potentials and Synaptic Integration 480
Ionotropic Receptors: Mediators of Fast Excitatory and Inhibitory Synaptic Potentials 480
Metabotropic Receptors: Mediators of Slow Synaptic Potentials 493
Integration of Synaptic Potentials 495
References 498
Cited 498
Chapter 17: Complex Information Processing in Dendrites 500
Strategies for Studying Complex Dendrites 500
Building Principles Step by Step 501
An Axon Places Constraints on Dendritic Processing 502
Dendrodendritic Interactions Between Axonal Cells 503
Passive Dendritic Trees Can Perform Complex Computations 503
Separation of Dendritic Fields Enhances Complex Information Processing 504
Distal Dendrites Can Be Closely Linked to Axonal Output 505
Depolarizing and Hyperpolarizing Dendritic Conductances Interact Dynamically 507
The Axon Hillock-initial Segment Encodes Global Output 508
Multiple Impulse Initiation Sites Are Under Dynamic Control 508
Retrograde Impulse Spread Into Dendrites Can Have Many Functions 511
Examples of How Voltage-gated Channels Enhance Dendritic Information Processing 514
Dendritic Spines Are Multifunctional Microintegrative Units 517
Summary: the Dendritic Tree as a Complex Information Processing System 518
References 520
Chapter 18: Information Processing in Neural Networks 524
Information Processing 524
Neural Representation 526
Encoding and Decoding 528
Iconic Neural Circuits 535
Plasticity 538
Example Circuits 539
Summary 546
References 546
Chapter 19: Learning and Memory: Basic Mechanisms 550
Long-term Synaptic Potentiation and Depression 550
A Breakthrough Discovery: LTP in the Hippocampus 551
The Hippocampal Circuit and Measuring Synaptic Transmission in the Hippocampal Slice 552
NMDA receptor-independent LTP 560
A Role for Calcium Influx in NMDA Receptor-Dependent LTP 562
LTP Outside the Hippocampus 566
Modulation of LTP Induction 566
Biochemical Mechanism for NMDAR-dependent LTP 567
Depotentiation and LTD 569
Summary 571
Paradigms Have Been Developed to Study Associative and Nonassociative Learning 571
Invertebrate Studies: Key Insights from Aplysia into Basic Mechanisms of Learning 572
Mechanisms Underlying Associative Learning in Aplysia 578
Classical Conditioning in Vertebrates: Discrete Responses and Fear Reactions as Models of Associative Learning 586
How does a Change in Synaptic Strength Store a Complex Memory? 604
Summary 606
References 606
Cited 607
Chapter 20: Molecular and Cellular Mechanisms of Neurodegenerative Disease 620
Introduction 620
Alzheimer Disease 622
Parkinson Disease 626
Amyotrophic Lateral Sclerosis 631
Glia and Neurodegenerative Disease 636
Summary 636
References 637
Index 642