National Key Laboratory for Multimedia Information Processing, School of Computer Science, Peking University, Beijing, China.
National Biomedical Imaging Center, College of Future Technology, Peking University, Beijing, China.
Invest Ophthalmol Vis Sci. 2024 Jul 1;65(8):39. doi: 10.1167/iovs.65.8.39.
A retinal mosaic, the spatial organization of a population of homotypic neurons, is thought to sample a specific visual feature into the feedforward visual pathway. The purpose of this study was to propose a universal modeling approach for precisely generating retinal mosaics and overcoming the limitations of previous models, especially in modeling abnormal mosaic patterns under disease conditions.
Here, we developed the optimization-based pairwise interaction point process (O-PIPP). It incorporates optimization techniques into previous simulation approaches, enabling directional control of the simulation process according to the user-designed optimization target. For the convenience of the community, we implemented the O-PIPP approach into a Python package and a website application.
We showed that the O-PIPP can generate more precise neural spatial patterns of healthy and diseased mosaics compared to previous phenomenological approaches. Notably, through modeling the retinal neural circuitry with O-PIPP-simulated retinitis pigmentosa cone mosaics, we elucidated how the cone mosaic rearrangement impacted the information processing of ganglion cells.
The O-PIPP provides a precise and universal tool to simulate realistic mosaics, which could help to investigate the function of retinal mosaics in vision.
视网膜镶嵌，即同型神经元群体的空间组织，被认为是将特定的视觉特征采样到前馈视觉通路中。本研究的目的是提出一种通用的建模方法，精确地生成视网膜镶嵌，并克服以前模型的局限性，特别是在模拟疾病条件下异常镶嵌模式方面。
在这里，我们开发了基于优化的成对相互作用点过程（O-PIPP）。它将优化技术纳入到以前的模拟方法中，根据用户设计的优化目标，实现了对模拟过程的方向控制。为了方便社区使用，我们将 O-PIPP 方法实现到一个 Python 包和一个网站应用程序中。
我们表明，与以前的唯象方法相比，O-PIPP 可以生成更精确的健康和病态镶嵌的神经空间模式。值得注意的是，通过使用 O-PIPP 模拟的色素性视网膜炎锥体镶嵌来模拟视网膜神经回路，我们阐明了锥体镶嵌重排如何影响神经节细胞的信息处理。
O-PIPP 提供了一种精确和通用的模拟真实镶嵌的工具，这有助于研究视网膜镶嵌在视觉中的功能。
