Note: Front cover -- Contents -- Preface to the Second Edition -- Contributors -- Foreword -- About the Editors -- 1 Introduction to Modeling in the Neurosciences -- 2 Patterns of Genetic Interactions: Analysis of mRNA Levels from cDNA Microarrays -- CONTENTS -- 2.1 INTRODUCTION 2.1.1 Biological Organisms are Complex Systems -- 2.1.2 Genes Interact withEac hOth er -- 2.2 GENETIC INTERACTION -- 2.2.1 Network Topologies -- 2.2.2 Genomic Networks -- 2.3 GENETIC NETWORKS -- 2.4 INTEGRATIVE MODELING APPROACH -- 2.4.1 The General Model -- 2.4.2 Five Models of Genetic Networks -- 2.4.3 EachModel Generates mRNA Levels with a Characteristic PDF -- 2.5 BIOLOGICAL DATA -- 2.6 SUMMARY -- ACKNOWLEDGMENTS -- PROBLEMS -- APPENDIX: MULTI-HISTOGRAM ALGORITHM FOR DETERMINING THE PDF -- 3 Calcium Signaling in Dendritic Spines -- CONTENTS -- 3.1 INTRODUCTION -- 3.2 FIRST-GENERATION DENDRITIC-SPINE CALCIUM MODELS -- 3.2.1 Calcium Diffusion -- 3.2.2 Calcium Buffering -- 3.2.3 Calcium Pumps -- 3.2.4 Calcium Influx -- 3.2.5 Calcium from Intracellular Stores -- 3.2.6 Summary -- 3.3 INSIGHTS -- 3.3.1 SpinesCompartmentalize Calcium Concentration Changes -- 3.3.2 SpinesAmplify Calcium Concentration Changes -- 3.3.3 Spine-Head Calcium (or CaMCa4) Concentration isa Good Predictor of LTP -- 3.3.4 Spine Shape Playsan Important Role in the Ability of a Spine to Concentrate Calcium -- 3.4 ISSUES -- 3.4.1 Calcium Pumps -- 3.4.2 Calcium Buffers -- 3.4.3 Calcium Source -- 3.5 IMAGING STUDIES TEST MODEL PREDICTIONS -- 3.5.1 SpinesCompartmentalize Calcium Concentration Changes -- 3.5.2 Importance of Spine Geometry -- 3.6 INSIGHTS -- 3.6.1 Sourcesof Calcium in Spines -- 3.6.2 Calcium Extrusion via Pumps -- 3.6.3 Calcium Buffersin Spines -- 3.7 ADDITIONAL INSIGHTS -- 3.7.1 Spine Motility -- 3.7.2 Coincidence Detection with Backpropagating Action Potentials. , 3.8 SECOND-GENERATION SPINE MODELS: REACTIONS LEADING -- 3.8.1 Modeling CaMKII Activation isComplicated -- 3.8.2 Characteristics of Second-Generation Models -- 3.9 INSIGHTS -- 3.9.1 Frequency Dependence of CaMKII Activation -- 3.9.2 Different Stagesof CaMKII Activation -- 3.9.3 CaMKII Activation asa Bistable Molecular Switch -- 3.9.4 CaMKII and Bidirectional Plasticity -- 3.9.5 CaMKII Activation and Spine Shape -- 3.9.6 ModelsPr edict the Need for Repetition of Short TetanusT rains -- 3.10 FUTURE PERSPECTIVES -- 3.11 SUMMARY -- PROBLEMS -- APPENDIX 1. TRANSLATING BIOCHEMICAL REACTION EQUATIONS TO DIFFERENTIAL EQUATIONS -- APPENDIX 2. STOCHASTIC RATE TRANSITIONS -- APPENDIX 3. USE OF MICHAELIS-MENTEN KINETICS IN DEPHOSPHORYLATION REACTIONS -- 4 Physiological and Statistical Approaches to Modeling of Synaptic Responses -- CONTENTS -- 4.1 INTRODUCTION 4.1.1 Modeling Synaptic Function in the CNS -- 4.1.2 Complexity Introduced by Synaptic Heterogeneity and Plasticity -- 4.1.3 Complexity Associated with Physiological Recordings -- 4.1.4 Classical Statistical Models -- 4.2 NONTRADITIONAL MODELS -- 4.2.1 Introduction to the Bayesian Model and Comparison to Classical Models -- 4.2.2 Bayesian Site Analysis -- 4.2.3 Application of the Bayesian Site Model to Simulated Data -- 4.2.4 Application of the Bayesian Model to Recorded Data -- 4.3 DISCUSSION 4.3.1 Comparison of Simulations and Physiological Data Sets -- 4.3.2 Analysis of Components in Contrast to Sites -- 4.3.3 Analysis of Physiological Data Sets -- 4.3.4 Conclusions and Future Perspectives -- ACKNOWLEDGMENTS -- APPENDIX: MATHEMATICAL DERIVATION OF THE MODEL -- 4.A1 PRIOR DISTRIBUTIONS -- 4.A1.1 General Structure -- 4.A1.2 -- 4.A1.3 -- 4.A1.4 Priors for Noise Moments m and v -- 4.A2 POSTERIOR DISTRIBUTIONS -- 4.A3 CONDITIONAL POSTERIORS -- 4.A4 PARAMETER IDENTIFICATION -- 4.A5 INCORPORATION. , 5 Natural Variability in the Geometry of Dendritic Branching Patterns -- CONTENTS -- 5.1 INTRODUCTION -- 5.2 DENDRITIC SHAPE PARAMETERS -- 5.2.1 Dendritic Topology -- 5.2.2 Dendritic Metrics -- 5.3 OBSERVED VARIABILITY -- 5.3.1 Variation in Topological Structure -- 5.3.2 Variation in the Number of Dendritic Segments -- 5.3.3 Variation in Segment Length -- 5.3.4 Variation in Dendritic Diameter -- 5.4 MODELING DENDRITIC BRANCHING PATTERNS -- 5.4.1 Modeling Topological Variation (QS Model) -- 5.4.2 Modeling the Variation in the Number of Terminal Segments per Dendrite (BE, BES, and BEST Models) -- 5.4.3 Modeling the Variation in the Length of Dendritic Segments (BESTL Model and Simulation Procedure) -- 5.4.4 Modeling the Variation in Segment Diameter -- 5.5 DISCUSSION -- 5.6 CONCLUSIONS -- 5.7 SUMMARY -- ACKNOWLEDGMENTS -- PROBLEMS -- 6 Multicylinder Models for Synaptic and Gap-Junctional Integration -- CONTENTS -- 6.1 INTRODUCTION -- 6.2 THE MULTICYLINDER MODEL 6.2.1 The Mathematical Problem -- 6.2.2 Problem Normalization and General Solution -- 6.2.3 Synaptic Reversal Potentials and Quasi-Active Ionic Currents -- 6.3 THE MULTICYLINDER MODEL WITH TAPER -- 6.3.1 The Mathematical Problem -- 6.3.2 Problem Normalization and General Solution -- 6.3.3 Synaptic Reversal Potentials -- 6.4 TWO GAP-JUNCTIONALLY COUPLED MULTICYLINDER MODELS TAPER -- 6.4.1 Soma-Somatic Coupling -- 6.4.2 Dendro-Dendritic Coupling -- 6.5 DISCUSSION -- 6.6 CONCLUSIONS -- ACKNOWLEDGMENT -- PROBLEMS -- 7 Voltage Transients in Branching Multipolar Neurons with Tapering Dendrites and Sodium Channels -- CONTENTS -- 7.1 INTRODUCTION -- 7.2 SOLUTIONS FOR TRANSIENTS IN A FULL ARBOR MODEL WITH TAPERED BRANCHES AND BRANCH-SPECIFIC MEMBRANE RESISTIVITY -- 7.2.2 Relationship between Tapering Multicylinder Model and Tapering Single Cylinder -- 7.2.3 Separation of Variables Solution. , 7.3 SOLUTIONS FOR TRANSIENTS IN A FULL AROR MODEL WITH LINEAR EMBEDDING OF SODIUM CHANNELS -- 7.3.1 Definition of the System -- 7.3.2 Approximate Solutions for Persistent (Na+P) Sodium Channels -- 7.3.3 Approximate Solutions for Transient (Na+) Sodium Channels -- 7.4 DISCUSSION -- 7.5 SUMMARY -- ACKNOWLEDGMENT -- PROBLEMS -- APPENDIX: CARLEMAN LINEARIZATION -- 8 Analytical Solutions of the Frankenhaeuser-Huxley Equations Modified for Dendritic Backpropagation of a Single SodiumSpike -- CONTENTS -- 8.1 INTRODUCTION -- 8.2 THE CABLE EQUATION -- 8.3 SCALING THE MACROSCOPIC Na+ CURRENT DENSITY -- 8.4 REFORMULATION -- 8.5 A PERTURBATIVE EXPANSION -- 8.6 VOLTAGE-DEPENDENT ACTIVATION -- 8.7 STEADY-STATE INACTIVATION OF THE SODIUM CHANNEL -- 8.8 RESULTS 8.8.1 Electrotonic Spread of bAP without Na+ Ion Channels -- 8.8.2 How the Location of Hot Spots with Identical Strengths of Na+ Ion Channels Affects the bAP -- 8.8.3 How the Number (N) of Uniformly Distributed Hot Spots with Identical Strengths of Na+ Ion Channel Densities Affects the bAP -- 8.8.4 How the Conductance Strength of Na+ ion Channel Densities with Identical Regional Distribution of Hot Spots Affects the bAP -- 8.9 DISCUSSION -- 8.10 SUMMARY -- 8.11 CONCLUSIONS -- ACKNOWLEDGMENTS -- APPENDIX -- PROBLEMS -- 9 Inverse Problems for Some Cable Models of Dendrites -- CONTENTS -- 9.1 INTRODUCTION -- 9.2 CONDUCTANCE-BASED MODELING -- 9.3 NONUNIFORM ION-CHANNEL DENSITIES -- 9.3.1 Recovering a Density in Passive Cable -- 9.3.2 Recovering a Density in Active Cable -- 9.3.3 Numerical Results -- 9.4 DENDRITES WITH EXCITABLE APPENDAGES -- 9.4.1 Recovering a Spatially Distributed Spine Density -- 9.4.2 Recovering a Spatially Distributed Filopodia Density -- 9.5 DISCUSSION -- 9.6 CONCLUSIONS -- 9.7 SUMMARY -- ACKNOWLEDGMENTS -- PROBLEMS -- 10 Equivalent Cables - Analysis and Construction -- CONTENTS. , 10.1 INTRODUCTION -- 10.2 CONSTRUCTION OF THE CONTINUOUS MODEL DENDRITE -- 10.2.1 Construction of the Discrete Model Dendrite -- 10.3 MATHEMATICAL MODEL OF UNIFORM CABLE -- 10.3.1 Notation -- 10.3.2 Application to a Cable -- 10.3.3 Symmetrizing a Cable Matrix -- 10.3.4 The Simple Y-Junction -- 10.3.5 Application to a Branched Dendrite -- 10.4 STRUCTURE OF TREE MATRICES -- 10.4.1 Self-Similarity Argument -- 10.4.2 Node Numbering -- 10.4.3 Symmetrizing the Tree Matrix -- 10.4.4 Concept of the Equivalent Cable -- 10.5 ILLUSTRATIVE EXAMPLES -- 10.5.1 A Simple Asymmetric Y-Junction -- 10.5.2 A Symmetric Y-Junction -- 10.5.3 Special Case: c1c4 = c2c3 -- 10.6 HOUSEHOLDER TRANSFORMATIONS -- 10.6.1 Householder Matrices -- 10.7 EXAMPLES OF EQUIVALENT CABLES -- 10.7.1 Interneurons Receiving Unmyelinated Afferent Input -- 10.7.2 Neurons Receiving Myelinated Afferent Input -- 10.8 DISCUSSION -- ACKNOWLEDGMENTS -- PROBLEMS -- APPENDIX -- 11 The Representation of Three-Dimensional Dendritic Structure by a One-Dimensional Model - The Conventional Cable Equation as the First Member of a Hierarchy of Equations -- CONTENTS -- 11.1 INTRODUCTION -- 11.2 BIOPHYSICAL PRELIMINARIES -- 11.2.1 Geometrical Considerations -- 11.2.2 Bioelectrical Considerations -- 11.2.3 Specification of the Mathematical Problem -- 11.3 IDENTIFICATION OF A ONE-DIMENSIONAL MEMBRANE POTENTIAL -- 11.4 DEVELOPMENT OF A HIERARCHY OF MEMBRANE EQUATIONS -- 11.4.1 The Membrane Boundary Conditions -- 11.4.2 Consistency of Boundary Conditions -- 11.5 THE MEMBRANE EQUATIONS -- 11.5.1 First Membrane Equation -- 11.5.2 Second Membrane Equation -- 11.5.3 Computation of Axial Current -- 11.6 CONSTITUTIVE EQUATIONS FOR TRANSMEMBRANE CURRENT -- 11.6.1 IntrinsicV oltage-Dependent Current -- 11.6.2 SynapticCurr ent -- 11.7 MEMBRANE EQUATIONS FOR SEGMENTS OF CONSTANT CONDUCTANCE. , 11.7.1 Constant Conductance Dendritic Model.

Note: CITY OF FORESTS, CITY OF FARMS -- Contents -- List of Tables, Maps, and Illustrations -- Preface and Acknowledgments -- List of Acronyms and Abbreviations -- Introduction: Juxtaposing Urban Forestry and Agriculture in the PlaNYC Era -- 1. Greening New York City: Political Economic Context and Environmental Stewardship from 1970 to the Present -- 2. Creating PlaNYC: The Politics of Urban Sustainability Planning -- 3. City of Forests: Planting One Million Trees -- 4. Beyond Planting: Creating an Urban Forestry Movement -- 5. Growing in the City: From Community Gardening to Urban Agriculture -- 6. City of Farms: Cultivating Urban Agriculture through Food Policy Visions and Plans -- 7. Constructing the "Greener, Greater" City: Politics, Discourses, and Material Practices -- 8. City as Ecosystem: Changing Form, Function, and Governance of Urban Socio-Nature -- Epilogue: From Bloomberg to de Blasio and Beyond -- Notes -- References -- Index.