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Neuroscience application of interactive image analysis
Source: Optical Engineering 1984 May;23(3):279-282.
Author: Toga AW, Goo RL, Murphy R, Colling RC.
Abstract:
The goal of neuroscience is to understand how different parts of the brain are wired together and how they communicate with one another. Several recently developed techniques use a method known as autoradiography to create images of brain connectivity and function. These autoradiographic methods promise to be quantitative and comprehensive. However, the data appear as gray scale images, which presents certain data analysis problems. Through a collaborative effort between neuroscientists, engineers, and computer scientists, we have developed a computer-based quantitative image analysis system. We have designed an interactive menu-driven software package. Our objective was to allow neuroscientists to quantitate, tabulate, and interpret the image data collected on autoradiographic files. A descripton of the hardware, the software package, and its application is presented. INTRODUCTION: The brain is the most complicated organ in the body. Simple inspection of its gross and microscopic structure provides no ready insight into how it functions. Over the last several years it has become possible to study how such brain circuits are actually used during an animal's behavior. When nerve cells become active, they need an increased amount of energy. To obtain this, they take up sugar from the bloodstream. By injecting radioactive analogs of glucose intravenously, an investigator can preferentially label the active areas of the brain. With this technique neuroscientists hope to discover which brain pathways are active during complex behaviors. By nature these autoradographic methods promise to be quantitative and comprehensive. OBJECTIVE: To provide a system with which an investigator can make high resolution digitized images of brain sections that can be quickly processed to yield information on brain structure and function that is both quantitative and comprehensive. Our objective was to allow users to view the image using any number of enhancements and transformaions without corrupting the integrity of the original data. APPLICATIONS: Our research interests are organized into two projects. In one we want to learn how visual experience can change the structure and function of the visual system of an animal. In the second project we want to learn how focal epilepsy travels through brain circuits to cause convulsive behavior. In brief, we induce focal epilepsy in experimental rats by placing a small amount of a convulsant chemical on the surface of the brain. When the animal is having active convulsions, we inject tracer amounts of 14C-deoxyglucose intravenously. After 40 minutes we sacrifice the animal with an overdose of sedative and then process the brain to make autoradiograms of serial sections. CONCLUSION: Computerized image processing provides neuroscientists with an analytic instrument that reduces the ambiguity of visual data by converting the data to high resolution quantitative images. Image analysis system help collect, measure, manipulate, analyze, and store visual data. The modular system we have developed allows for relatively rapid, easy, and versatile image analysis by allowing users on-line interaction withmenus of software programs.
Source: Optical Engineering 1984 May;23(3):279-282.
Author: Toga AW, Goo RL, Murphy R, Colling RC.
Abstract:
The goal of neuroscience is to understand how different parts of the brain are wired together and how they communicate with one another. Several recently developed techniques use a method known as autoradiography to create images of brain connectivity and function. These autoradiographic methods promise to be quantitative and comprehensive. However, the data appear as gray scale images, which presents certain data analysis problems. Through a collaborative effort between neuroscientists, engineers, and computer scientists, we have developed a computer-based quantitative image analysis system. We have designed an interactive menu-driven software package. Our objective was to allow neuroscientists to quantitate, tabulate, and interpret the image data collected on autoradiographic files. A descripton of the hardware, the software package, and its application is presented. INTRODUCTION: The brain is the most complicated organ in the body. Simple inspection of its gross and microscopic structure provides no ready insight into how it functions. Over the last several years it has become possible to study how such brain circuits are actually used during an animal's behavior. When nerve cells become active, they need an increased amount of energy. To obtain this, they take up sugar from the bloodstream. By injecting radioactive analogs of glucose intravenously, an investigator can preferentially label the active areas of the brain. With this technique neuroscientists hope to discover which brain pathways are active during complex behaviors. By nature these autoradographic methods promise to be quantitative and comprehensive. OBJECTIVE: To provide a system with which an investigator can make high resolution digitized images of brain sections that can be quickly processed to yield information on brain structure and function that is both quantitative and comprehensive. Our objective was to allow users to view the image using any number of enhancements and transformaions without corrupting the integrity of the original data. APPLICATIONS: Our research interests are organized into two projects. In one we want to learn how visual experience can change the structure and function of the visual system of an animal. In the second project we want to learn how focal epilepsy travels through brain circuits to cause convulsive behavior. In brief, we induce focal epilepsy in experimental rats by placing a small amount of a convulsant chemical on the surface of the brain. When the animal is having active convulsions, we inject tracer amounts of 14C-deoxyglucose intravenously. After 40 minutes we sacrifice the animal with an overdose of sedative and then process the brain to make autoradiograms of serial sections. CONCLUSION: Computerized image processing provides neuroscientists with an analytic instrument that reduces the ambiguity of visual data by converting the data to high resolution quantitative images. Image analysis system help collect, measure, manipulate, analyze, and store visual data. The modular system we have developed allows for relatively rapid, easy, and versatile image analysis by allowing users on-line interaction withmenus of software programs.