Quantitative characterization of the human retinotopic map based on quasiconformal mapping.
Quantitative characterization of the human retinotopic map based on quasiconformal mapping.
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DOI：
10.1016/j.media.2021.102230
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发表时间：
2022-01
影响因子：
10.9
通讯作者：
Wang Y
中科院分区：
文献类型：
--
作者：
Ta D;Tu Y;Lu ZL;Wang Y
视网膜视图描绘了视网膜上皮层神经元对视觉刺激的反应，对我们理解人类视觉系统有重要贡献。虽然高场功能性磁共振成像（fMRI）的最新进展已经能够生成非常详细的体内视网膜定位图，但量化该图仍然具有挑战性。现有的量化方法不保留表面拓扑结构，并且经常对地图引入大的几何失真。在这项研究中，我们开发了一个新的框架的基础上计算共形几何和准共形Teichmüller理论来量化的视网膜拓扑图。具体来说，我们介绍了一个通用的管道，包括皮质表面保形参数化，表面样条为基础的皮质激活信号平滑，和顶点贝尔特拉米系数为基础的地图描述。在纠正了大多数违反拓扑条件的情况后，结果是一个“Beltrami系数图”（Beltrami coefficient map），它通过量化每个视野位置处的局部准共形映射失真来严格和完整地表征视网膜映射图。他们提供了拓扑和完全可重建的视网膜拓扑图。我们成功地应用了新的框架来分析来自人类连接组项目（n=181）的V1视网膜定位图，这是目前最大的最先进的视网膜定位数据集。以前所未有的精度，我们发现，V1 retinotopic地图是quasiconformal和本地映射失真是相似的观察者。新的框架可以应用于其他视觉领域和retinotopic地图的个人和没有眼睛疾病，并提高我们的理解视觉皮层组织在正常和临床人群。
The retinotopic map depicts the cortical neurons’ response to visual stimuli on the retina and has contributed significantly to our understanding of human visual system. Although recent advances in high field functional magnetic resonance imaging (fMRI) have made it possible to generate the in vivo retinotopic map with great detail, quantifying the map remains challenging. Existing quantification methods do not preserve surface topology and often introduce large geometric distortions to the map. In this study, we developed a new framework based on computational conformal geometry and quasiconformal Teichmüller theory to quantify the retinotopic map. Specifically, we introduced a general pipeline, consisting of cortical surface conformal parameterization, surface-spline-based cortical activation signal smoothing, and vertex-wise Beltrami coefficient-based map description. After correcting most of the violations of the topological conditions, the result was a “Beltrami coefficient map” (BCM) that rigorously and completely characterizes the retinotopy map by quantifying the local quasiconformal mapping distortion at each visual field location. The BCM provided topological and fully reconstructable retinotopic maps. We successfully applied the new framework to analyze the V1 retinotopic maps from the Human Connectome Project (n=181), the largest state of the art retinotopy dataset currently available. With unprecedented precision, we found that the V1 retinotopic map was quasiconformal and the local mapping distortions were similar across observers. The new framework can be applied to other visual areas and retinotopic maps of individuals with and without eye diseases, and improve our understanding of visual cortical organization in normal and clinical populations.
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