1. The History of Quantitative Neuroanatomy.- 1.1. Introduction.- 1.2. Early History of Drawing Neurons.- 1.3. How the Microscope Handicaps the User.- 1.3.1. Medium.- 1.3.2. Perspective.- 1.3.3. Magnification.- 1.3.4. Contrast.- 1.3.5. Measurement.- 1.4. Drawing with the Camera Lucida.- 1.5. The Pantograph: A Plotter for the Microscope.- 1.6. Physical Model Building.- 1.7. Early Attempts at Statistical Summaries.- 1.8. How the Computer Helps Visualizing and Summarizing.- 1.9. For Further Reading.- 1.10. What This Book Presents.- 2. Laboratory Computer Hardware.- 2.1. Introduction.- 2.2. Overview of Key Components.- 2.2.1. Bus.- 2.2.2. Central Processing Unit.- 2.2.3. Memory.- 2.2.4. Disks.- 2.2.5. Disk Drives.- 2.2.6. Keyboard.- 2.2.7. Terminal.- 2.2.8. Graphics Board.- 2.2.9. Ports.- 2.2.10. Analog-to-Digital Converter.- 2.3. Concepts and Definitions.- 2.3.1. Forms of Data.- 2.3.2. Analog and Digital Values.- 2.3.3. Storage of Digital Data.- 2.4. Computing Hardware Described in Some Depth.- 2.4.1. Central Processing Unit.- 2.4.2. Math Coprocessors.- 2.4.3. Random Access Memory.- 2.4.4. Disks.- 2.4.5. Magnetic Tapes.- 2.4.6. Graphics Display Cards.- 2.4.7. Computer Speeds.- 2.4.8. Bus.- 2.4.9. Plotters.- 2.4.10. Printers.- 2.4.11. Analog-to-Digital Converter.- 2.4.12. Digital-to-Analog Converter.- 2.4.13. Modem.- 2.4.14. Graphics Display Systems.- 2.4.15. Data Tablets.- 2.4.16. Mouse.- 2.4.17. Joysticks.- 2.4.18. Trackball.- 2.4.19. Stepping Motors.- 2.4.20. Components Used for Sensing Position and Motion.- 2.4.21. Ports.- 2.5. Physical Construction of Laboratory Computers.- 2.6. Common Laboratory Computers.- 2.6.1. IBM PC.- 2.6.2. IBM XT.- 2.6.3. IBM AT.- 2.6.4. 80386 Machines.- 2.6.5. IBM Personal System/2.- 2.6.6. Apple II.- 2.6.7. Macintosh.- 2.6.8. Macintosh II.- 2.6.9. VME-Bus Machines.- 2.6.10. DEC PDP-11.- 2.6.11. DEC VAX.- 2.7. Purchasing a Computer.- 2.7.1. Clones.- 2.7.2. Compatibility.- 2.8. For Further Reading.- 3. Software in the Neuroanatomy Laboratory.- 3.1. Introduction.- 3.2. How Software is Written.- 3.2.1. Source Files.- 3.2.2. Translation and Execution.- 3.3. System Software.- 3.3.1. Operating Systems.- 3.3.2. Time-Sharing (Multiuser) Operating Systems.- 3.3.3. Language Translators.- 3.3.4. Text Editors (Word Processors).- 3.4. Applications Software.- 3.4.1. Specific Laboratory Tasks.- 3.4.2. General Laboratory Tasks.- 3.5. Common Programming Languages.- 3.5.1. C.- 3.5.2. FORTRAN.- 3.5.3. BASIC.- 3.5.4. Other Programming Languages.- 3.5.5. High-Level Proprietary Languages.- 3.6. Software Costs and Productivity.- 3.6.1. Software Costs Related to Hardware Costs.- 3.6.2. Software Costs Related to Software Level.- 3.6.3. Programs and Program Products.- 3.6.4. How to Get the Job Done.- 3.7. The Vendor’s Dilemma.- 3.8. For Further Reading.- 4. Semiautomatic Entry of Neuron Trees from the Microscope.- 4.1. Introduction.- 4.2. Principles of Semiautomatic Neuron Tracing.- 4.2.1. The Marriage of the Researcher to the Computer.- 4.2.2. A Single Pass over the Data.- 4.2.3. Identify Different Structures in Their Environment.- 4.2.4. Feedback.- 4.2.5. Work from the Best Image.- 4.3. The UNC Neuron-Tracing System.- 4.3.1. Hardware of the UNC Neuron-Tracing System.- 4.3.2. Control of the Stage.- 4.3.3. Coordinate System and Origins in the UNC Neuron-Tracing System.- 4.3.4. Outlining a Soma with the UNC System.- 4.3.5. Tracing a Dendrite with the UNC System.- 4.3.6. Locating and Outlining Other Structures.- 4.3.7. The Storage of Traced Data.- 4.3.8. Advantages of Vector Graphics in Neuron Tracing.- 4.4. Other Neuron-Tracing Techniques.- 4.4.1. Alternatives to Motorizing the Stage.- 4.4.2. Alternatives to the Computer-Generated Overlay.- 4.4.3. Alternative Stage Control Methods.- 4.5. For Further Reading.- 5. Input from Serial Sections.- 5.1. Introduction.- 5.2. History.- 5.3. Purpose of Serial Section Reconstruction.- 5.4. Entering Serial Sections into the Computer.- 5.4.1. Using a Data Tablet.- 5.4.2. Types of Images.- 5.4.3. Calibrating the Data Tablet.- 5.4.4. Entering the Data.- 5.4.5. Aligning Traced Sections.- 5.5. The Storage of Data.- 5.5.1. Compressing the Data.- 5.5.2. Organizing the Data.- 5.6. Editing of Data.- 5.7. Displays and Plots of Serial Section Reconstructions.- 5.8. Statistical Summarizations of Serial Section Reconstructions.- 5.9. For Further Reading.- 6. Video Input Techniques.- 6.1. Introduction.- 6.2. A Video-Based Anatomic Data-Collecting System.- 6.3. Extracting Vector Information from a Televised Image.- 6.3.1. Tracing a Dendrite.- 6.3.2. Outlining a Structure.- 6.4. Extracting Optical-Density Information.- 6.5. Masking of Images.- 6.6. Particle Counting.- 6.7. Automatic Focusing.- 6.8. Video Input Compared to Directly Viewed Input.- 6.8.1. Advantages of Television-Based Data Collection.- 6.8.2. Disadvantages of Television-Based Systems.- 6.9. For Further Reading.- 7. Intermediate Computations of Reconstructed Data.- 7.1. Introduction.- 7.2. Focus-Axis Problems.- 7.3. Merging of Multiple-Section Dendrites.- 7.4. Aligning One Tissue Section with Another.- 7.5. Editing.- 7.6. Mathematical Testing of the Data Base.- 7.7. Serial Inspection of Structures.- 7.8. Reordering of Trees.- 7.9. Filtering.- 7.10. Storage of Data on Disk.- 7.11. Conclusion.- 7.12. For Further Reading.- 8. Three-Dimensional Displays and Plots of Anatomic Structures.- 8.1. Introduction.- 8.2. Three-Dimensional Displays on a Two-Dimensional Screen.- 8.2.1. Smooth Rotation and Kinesthesia.- 8.2.2. Clipping.- 8.2.3. Projection onto the Two-Dimensional Screen.- 8.2.4. Zooming and Magnification.- 8.2.5. Variation of Intensity.- 8.2.6. Hidden-Line and Hidden-Surface Removal.- 8.2.7. Stereo Pairs.- 8.2.8. Line Generation.- 8.3. Vector Display of Structure.- 8.3.1. Time Constraint to Avoid Flicker.- 8.3.2. Only Wire-Frame Stick Figures without Thickness.- 8.3.3. Smooth Rotation.- 8.3.4. Spatial Resolution and Aliasing.- 8.3.5. Highlighting Vector Displays by Varying Brightness.- 8.3.6. Color Vector Graphics Systems.- 8.4. Raster Display of Structures.- 8.4.1. The Aliasing Problem in Raster Displays.- 8.4.2. Spatial Resolution.- 8.4.3. Surface-Filled Raster Displays.- 8.4.4. Current Sophisticated Image-Generation Techniques.- 8.4.5. Enriched Raster Displays.- 8.4.6. Time and Costs of Raster Displays of Anatomic Data.- 8.5. Three-Dimensional Plots of Neuroanatomical Structure.- 8.5.1. Felt-Tip Pen Plotter.- 8.5.2. Plots on a Laser Printer.- 8.6. For Further Reading.- 9. Mathematical Summarizations of Individual Neuron Structures.- 9.1. Introduction.- 9.2. Numeric Summaries of a Cell.- 9.2.1. Counting Measurements.- 9.2.2. Length-Based Measurements.- 9.2.3. Area-Based Measurements.- 9.2.4. Volume-Based Measurements.- 9.2.5. The Region of Influence of the Neuron.- 9.2.6. Measurements of the Neuron’s Center.- 9.2.7. Orientations of the Neuron.- 9.2.8. Point-Type Densities.- 9.2.9. Analysis of Dendritic Spines.- 9.3. Graphing Summaries.- 9.3.1. Distributions of Point Types.- 9.3.2. Distributions of Dendritic Length.- 9.3.3. Analysis of Branch Segments.- 9.3.4. Analysis of Branch Points.- 9.3.5. Sholl Sphere Analysis.- 9.3.6. Directional Analysis.- 9.3.7. Cluster Analysis.- 9.4. For Further Reading.- 10. Topological Analysis of Individual Neurons.- 10.1. Introduction.- 10.2. Classification of Tree Types.- 10.3. Classification Based on Different Topological Features.- 10.3.1. Classification according to the Degree of Subtree Pairs.- 10.3.2. Classification Based on Topological Distance from the Root.- 10.4. Comparison of Measures for Asymmetry of Trees.- 10.4.1. Trees with Bifurcations Only (Strictly Binary Trees).- 10.4.2. Multifurcating Trees.- 10.5. Ordering Systems for Segments.- 10.6. Analysis of Incomplete Trees.- 10.7. In Conclusion.- 10.8. Summary.- 10.9. Appendix.- 11. Statistical Analysis of Neuronal Populations.- 11.1. Introduction.- 11.2. Metrics of Somatic Size and Dendritic Segments.- 11.2.1. Somatic Size.- 11.2.2. The Size of a Dendritic Tree.- 11.2.3. Metric Analysis of Segments.- 11.3. Angular Metrics of Bifurcations.- 11.4. Spatial Orientation of Trees.- 11.4.1. Spherical and Circular Orientation Methods.- 11.4.2. Cubic Orientation Methods.- 11.4.3. Principal-Axes Method.- 11.4.4. Cartesian Grid Analysis for Dendritic Orientation and Density.- 11.4.5. Comparison of Orientation Methods.- 11.5. Statistical Evaluation of Groups of Neurons.- 11.5.1. Parametric and Nonparametric Testing.- 11.5.2. Geometric Dendritic Size and Body Size.- 11.5.3. Multivariate Comparison of Sets of Dendritic Variables.- 11.6. In Conclusion.- 11.7. Summary.- 12. Controlling the Computer System: The User Interface.- 12.1. Introduction.- 12.2. Principles of User Interface Design.- 12.3. Selecting Commands.- 12.3.1. Introduction.- 12.3.2. Menus.- 12.3.3. Command-Line Interfaces.- 12.3.4. Direct-Manipulation Systems.- 12.3.5. Command Operands, Default Values, and Parameters.- 12.4. Using Interactive Devices to Control Tracing.- 12.4.1. Introduction.- 12.4.2. Tracing with a Data Tablet.- 12.4.3. Tracing by Moving the Microscope Stage.- 12.4.4. Tracing on a Digitized Video Image.- 12.5. Data Storage.- 12.5.1. Introduction.- 12.5.2. Disk Files.- 12.5.3. Backup.- 12.6. Error Handling.- 12.7. Presentation of Output.- 12.8. Subroutine Libraries.- 12.9. User Manuals and Other Documentation.- 13. Video Enhancement Techniques.- 13.1. Introduction.- 13.2. Hardware.- 13.2.1. Image-Processing Boards.- 13.2.2. The Video Input.- 13.2.3. Video Displays.- 13.2.4. True Color Systems.- 13.2.5. Storage of Images.- 13.3. Software.- 13.4. Enhancing the Image.- 13.4.1. Analog Adjustments of the Gray Scale.- 13.4.2. Digital Manipulation of the Gray Scale.- 13.4.3. Decreasing the Noise.- 13.4.4. Delimiting the Object.- 13.4.5. Fourier Analysis of Images.- 13.4.6. Combining Images.- 13.5. Is Image Processing Legitimate?.- 13.6. For Further Reading.- 14. The Analysis of Immunohistochemical Data.- 14.1. Introduction.- 14.2. Hardware for Image Analysis.- 14.2.1. Image-Acquisition Devices.- 14.2.2. Image Memory and Processor Boards.- 14.2.3. General Information.- 14.3. Characteristics of Image Analyzers.- 14.3.1. Spatial Resolution.- 14.3.2. Gray-Scale Resolution.- 14.3.3. Dynamic Range.- 14.3.4. Image Input and Processing Speed.- 14.4. How to Evaluate and Resolve Problems with an Image-Analysis System.- 14.4.1. Photometric Uniformity in Space.- 14.4.2. Photometric Uniformity in Time.- 14.4.3. System Sensitivity and Linearity.- 14.4.4. Evaluation of Measurement Algorithms.- 14.5. How to Measure Immunocytochemically Labeled Tissue.- 14.5.1. Setting up the System.- 14.5.2. Collecting Data.- 14.6. Analysis of Immunocytochemistry Data.- 14.6.1. Field Measurements.- 14.6.2. Cell Measurements.- 14.6.3. Fiber Measurements.- 14.7. Histochemistry Procedures and Controls.- 14.7.1. Factors Affecting Labeling.- 14.7.2. Controls.- 14.7.3. Quantitative Standards.- 14.8. Summary and Additional Information.- 14.8.1. Hardware Considerations.- 14.8.2. Choice of Image Analyzer.- 14.8.3. Biological Measures.- 14.8.4. Biological Utility of the Measures.- 14.9. For Further Reading.- 15. Fully Automatic Neuron Tracing.- 15.1. Introduction.- 15.2. The Automatic Reconstruction Problem.- 15.3. A Standard of Comparison.- 15.4. The Current Art of Automatic Tracing.- 15.4.1. Automatic Neuron Tracing with a Vidisector.- 15.4.2. Automatic Neuron Tracing with a Television Camera.- 15.5. For Future Work.- 15.5.1. Bigger and Faster Computers.- 15.5.2. Better Image-Enhancement Techniques.- 15.5.3. The Confocal Microscope.- 15.6. Conclusion.- 15.7. For Further Reading.- 16. Commercially Available Computer Systems for Neuroanatomy.- 16.1. Introduction.- 16.2. Companies and Their Products.- 16.2.1. American Innovision, Inc..- 16.2.2. Analytical Imaging Concepts, Inc..- 16.2.3. Axon Instruments, Inc..- 16.2.4. Biographics, Inc..- 16.2.5. Bio Image—A Kodak Company.- 16.2.6. Bio-Rad.- 16.2.7. Burleigh Instruments, Inc..- 16.2.8. Dage-MTI, Inc..- 16.2.9. Dapple Systems.- 16.2.10. Eikonix.- 16.2.11. Eutectic Electronics, Inc..- 16.2.12. General Imaging Corporation.- 16.2.13. Image Data Systems.- 16.2.14. Imaging Research, Inc..- 16.2.15. INDEC Systems.- 16.2.16. Jandel Scientific.- 16.2.17. Joyce-Loebl.- 16.2.18. Media Cybernetics.- 16.2.19. Microscience, Inc..- 16.2.20. Olympus Corporation.- 16.2.21. Quantex Corporation.- 16.2.22. R & M Biometrics, Inc..- 16.2.23. Sarastro, Inc..- 16.2.24. Southern Micro Instruments.- 16.2.25. SPEX Industries, Inc..- 16.2.26. Technology Resources, Inc..- 16.2.27. Universal Imaging Corporation.- 16.2.28. Wild Leitz U.S.A., Inc..- References.- Selected Reading.