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内视网膜网络如何塑造神经节细胞感受野?一项计算研究。

How Does the Inner Retinal Network Shape the Ganglion Cells Receptive Field? A Computational Study.

机构信息

Université Côte d'Azur, Inria, Biovision Team and Neuromod Institute, Sophia Antipolis, France.

Biosciences Institute, Newcastle University, Newcastle upon Tyne NE2 4HH, U.K.

出版信息

Neural Comput. 2024 May 10;36(6):1041-1083. doi: 10.1162/neco_a_01663.

DOI:10.1162/neco_a_01663
PMID:38669693
Abstract

We consider a model of basic inner retinal connectivity where bipolar and amacrine cells interconnect and both cell types project onto ganglion cells, modulating their response output to the brain visual areas. We derive an analytical formula for the spatiotemporal response of retinal ganglion cells to stimuli, taking into account the effects of amacrine cells inhibition. This analysis reveals two important functional parameters of the network: (1) the intensity of the interactions between bipolar and amacrine cells and (2) the characteristic timescale of these responses. Both parameters have a profound combined impact on the spatiotemporal features of retinal ganglion cells' responses to light. The validity of the model is confirmed by faithfully reproducing pharmacogenetic experimental results obtained by stimulating excitatory DREADDs (Designer Receptors Exclusively Activated by Designer Drugs) expressed on ganglion cells and amacrine cells' subclasses, thereby modifying the inner retinal network activity to visual stimuli in a complex, entangled manner. Our mathematical model allows us to explore and decipher these complex effects in a manner that would not be feasible experimentally and provides novel insights in retinal dynamics.

摘要

我们考虑了一个基本的内视网膜连接模型,其中双极细胞和无长突细胞相互连接,这两种细胞类型都投射到神经节细胞上,调节它们对大脑视觉区域的反应输出。我们推导出了视网膜神经节细胞对刺激的时空反应的解析公式,考虑到无长突细胞抑制的影响。这种分析揭示了网络的两个重要功能参数:(1)双极细胞和无长突细胞之间相互作用的强度,以及(2)这些反应的特征时间尺度。这两个参数对光刺激下视网膜神经节细胞反应的时空特征都有深远的综合影响。该模型的有效性通过忠实地再现通过刺激在神经节细胞和无长突细胞子类上表达的兴奋性 DREADD(专门由设计药物激活的设计受体)来获得的基因药理学实验结果得到了证实,从而以复杂、纠缠的方式修饰内视网膜网络对视觉刺激的活动。我们的数学模型允许我们以实验上不可行的方式探索和破译这些复杂的影响,并提供对视网膜动力学的新见解。

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Neural Comput. 2024 May 10;36(6):1041-1083. doi: 10.1162/neco_a_01663.
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