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A computational model of topographic mapping and cell density in the macaque lateral geniculate nucleus.

机译:猕猴外侧膝状核中的地形图和细胞密度的计算模型。

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摘要

In the primate visual system, nearby neurons in the brain represent nearby points in the visual field. These maps have been well studied in primary visual cortex (V1), but the lateral geniculate nucleus of the thalamus (LGN), which projects to V1, is far less understood. To date, efforts to study topography in the LGN have focused on one-dimensional models of magnification (the amount of neural substrate per degree of visual field), which cannot simply account for many important aspects of geniculate topography. Neither the presence of shear (angular distortion) nor differences in representation along radial segments within the visual field can be succinctly described with one-dimensional models. Efforts to study magnification are complicated by variable cell density in the LGN, which has not been well characterized. This thesis provides three contributions to the understanding of geniculate topography and magnification.;The first goal was to develop a two-dimensional model of topographic organization within the LGN. Extending the wedge-monopole model of V1 topography allows the development of a new model that jointly characterizes the six geniculate layers. Fitting this model to physiological data from macaque monkeys suggests that the geniculate displays an orderly increase in shear from innermost to outermost layers. The geniculate map structure is otherwise constant across layers.;The second goal was to develop a technique to address the variable cell density in LGN. The development of new methods to create density uniformizing maps (cartograms) allows a balance between highly-distorted cartograms and approximate cartograms with minimal shear. Applying these minimal shear transformations to the LGN enables direct comparison between LGN and V1 topography.;Finally, a manual count of neurons enabled investigation of the variability in LGN cell density across specimens. Counting a large number of cells demonstrates that previous estimates using different sample sizes are not comparable, and that commonly held views on geniculate cell distribution are likely to be incorrect.;These results demonstrate that characterization of geniculate topography is possible with a low-dimensional model, and that cell density (when correctly modeled) can be addressed in a principled way using conformal approximations to cartograms.
机译:在灵长类动物视觉系统中,大脑中附近的神经元代表视野中的附近点。这些图已经在初级视觉皮层(V1)中得到了很好的研究,但是,投射到V1的丘脑外侧膝状核(LGN)却鲜为人知。迄今为止,在LGN中研究地形的努力集中于一维放大模型(每视野度的神经底物数量),它不能简单地说明膝状地形的许多重要方面。一维模型既不能简洁地描述剪切力(角度变形)的存在,又不能沿视场内的径向线段进行表示上的差异。 LGN中可变的细胞密度使研究放大倍数的工作变得复杂,这尚未得到很好的表征。本文为对膝状地形和放大倍数的理解提供了三个方面的贡献。;第一个目标是在LGN内建立二维的地形组织模型。扩展V1地形的楔形单极模型,可以开发出一个新模型,该模型可以共同表征六个膝状体层。将该模型与猕猴的生理数据进行拟合表明,膝状体显示从最内层到最外层的剪切力有序增加。膝状图结构在各层之间是恒定的。第二个目标是开发一种技术来解决LGN中可变的细胞密度。创建密度均匀化贴图(图表)的新方法的发展,可以在最小失真的情况下在高度失真的图表和近似的图表之间取得平衡。将这些最小的剪切转换应用于LGN可以在LGN和V1地形之间进行直接比较。最后,人工计数神经元可以研究整个标本中LGN细胞密度的变化。对大量细胞进行计数表明,以前使用不同样本量进行的估算是不可比较的,并且通常关于膝状细胞分布的观点可能是不正确的;这些结果表明,利用低维模型可以表征膝状细胞的形貌,并且可以使用原理图对制图进行保形近似来解决细胞密度(正确建模时)的问题。

著录项

  • 作者

    Storer, Alex W.;

  • 作者单位

    Boston University.;

  • 授予单位 Boston University.;
  • 学科 Biology Neuroscience.
  • 学位 Ph.D.
  • 年度 2011
  • 页码 114 p.
  • 总页数 114
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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