Computer Techniques in Neuroanatomy

This book is the story of the marriage of a new techl}ology, computers, with an old problem, the study of neuroanatomical structures using the light microscope. It is aimed toward you, the neuroanatomist, who until now have used computers primarily for word processing but now wish to use them also to collect and analyze your laboratory data. Mter reading the book, you will be better equipped to use a computer system for data collection and analysis, to employ a programmer who might develop a system for you, or to evaluate the systems available in the marketplace. To start toward this goal, a glossary first presents commonly used terms in computer­ assisted neuroanatomy. This, on its own, will aid you as it merges the jargon of the two different fields. Then, Chapter 1 presents a historical review to describe the manual tasks involved in presenting and measuring anatomic structures. This review lays a base line of the tasks that were done before computers and the amount of skill and time needed to perform the tasks. In Chapters 2 and 3, you will find basic information about laboratory computers and programs to the depth required for you to use the machines easily and talk with some fluency to computer engineers, programmers, and salesmen. Chapters 4, 5, and 6 present the use of computers to reconstruct anatomic structures, i.e., to enter them into a computer memory, where they are later displayed and analyzed.

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.