Computer-Aided Neuroanatomy: Differential Geometry of Cortical Surfaces and an Optimal Flattening Algorithm

摘要

In this article we review several computer graphics and image processing applications that help us understand the architecture of monkey and human visual cortex. Two general areas are covered. First, computer graphics methods can be used to simulate the patterns of activity that would occur at various levels of the nervous system as a result of the presence of a particular image on the retina. Current understanding of brain architecture is sufficiently advanced to make this a useful exercise. Simulations of several aspects of visual cortex architecture, using real images, are presented. Second, the technical aspects of studying brain architecture involve the reconstruction of patterns of architecture from serial sections. Computer graphics and image processing techniques can make a major contribution to this area by providing methods of reconstructing the three-dimensional surfaces derived from large numbers of serial sections, and also by providing flattened versions of these surfaces. We have termed this area of application computer aided anatomy. We illustrate this methodology by demonstrating an algorithm we have developed that flattens a 3D reconstruction of the opercular surface of monkey striate cortex while optimally preserving the metric structure of the original neural surface. As a first step in this work, we have measured the mean and Gaussian curvature at each point of the opercular surface of macaque striate cortex. Reprints. (aw)