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将超分辨率和层析成像概念应用于识别视网膜中的感受野亚单位。

Applying Super-Resolution and Tomography Concepts to Identify Receptive Field Subunits in the Retina.

机构信息

University Medical Center Göttingen, Department of Ophthalmology, Göttingen, Germany.

Bernstein Center for Computational Neuroscience Göttingen, Göttingen, Germany.

出版信息

PLoS Comput Biol. 2024 Sep 3;20(9):e1012370. doi: 10.1371/journal.pcbi.1012370. eCollection 2024 Sep.

Abstract

Spatially nonlinear stimulus integration by retinal ganglion cells lies at the heart of various computations performed by the retina. It arises from the nonlinear transmission of signals that ganglion cells receive from bipolar cells, which thereby constitute functional subunits within a ganglion cell's receptive field. Inferring these subunits from recorded ganglion cell activity promises a new avenue for studying the functional architecture of the retina. This calls for efficient methods, which leave sufficient experimental time to leverage the acquired knowledge for further investigating identified subunits. Here, we combine concepts from super-resolution microscopy and computed tomography and introduce super-resolved tomographic reconstruction (STR) as a technique to efficiently stimulate and locate receptive field subunits. Simulations demonstrate that this approach can reliably identify subunits across a wide range of model variations, and application in recordings of primate parasol ganglion cells validates the experimental feasibility. STR can potentially reveal comprehensive subunit layouts within only a few tens of minutes of recording time, making it ideal for online analysis and closed-loop investigations of receptive field substructure in retina recordings.

摘要

视网膜神经节细胞的空间非线性刺激整合是视网膜进行各种计算的核心。它源于神经节细胞从双极细胞接收的信号的非线性传输,双极细胞由此构成了神经节细胞感受野内的功能亚单元。从记录的神经节细胞活动中推断这些亚单元有望为研究视网膜的功能结构提供新的途径。这需要有效的方法,为进一步研究已确定的亚单元留出足够的实验时间来利用所获得的知识。在这里,我们结合超分辨率显微镜和计算机断层扫描的概念,并引入超分辨率断层重建(STR)作为一种有效刺激和定位感受野亚单元的技术。模拟表明,这种方法可以在广泛的模型变化范围内可靠地识别亚单元,并且在灵长类伞形神经节细胞记录中的应用验证了实验的可行性。STR 可以在仅数十分钟的记录时间内潜在地揭示全面的亚单元布局,使其成为视网膜记录中感受野亚结构的在线分析和闭环研究的理想选择。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1bd4/11398665/89106a13beb7/pcbi.1012370.g001.jpg

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