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研究发现灵长类动物视网膜具有预测物体运动的功能
2021-08-05 16:33

美国华盛顿大学Manookin, Michael B.研究组的最新研究表明预测运动编码始于灵长类动物的视网膜。相关论文于2021年8月2日发表于国际学术期刊《自然-神经科学》杂志。

研究人员发现灵长类动物视网膜中的四个并行输出通路编码了预测运动的信息,并且这种编码也存在于自然视觉中发现的几类时空相关性预测。这种预测编码可以通过已知的非线性电路机制来解释,该机制产生了近乎最佳的编码,传输的信息接近刺激本身施加的理论限制。因此,这些神经回路机制在编码过程中有效地将预测信息与非预测信息分开。

据介绍,预测运动编码是视觉引导行为的一个重要方面,它使得动物可以预估运动物体的轨迹。对运动预测的研究主要是在平移运动条件下进行的,但环境中也包含其他类型与行为相关的运动特性,例如由接近或后退物体产生的运动相关性。然而,检测和预测编码这些相关性的神经机制仍不清楚。

附:英文原文

Title: Predictive encoding of motion begins in the primate retina

Author: Liu, Belle, Hong, Arthur, Rieke, Fred, Manookin, Michael B.

Issue&Volume: 2021-08-02

Abstract: Predictive motion encoding is an important aspect of visually guided behavior that allows animals to estimate the trajectory of moving objects. Motion prediction is understood primarily in the context of translational motion, but the environment contains other types of behaviorally salient motion correlation such as those produced by approaching or receding objects. However, the neural mechanisms that detect and predictively encode these correlations remain unclear. We report here that four of the parallel output pathways in the primate retina encode predictive motion information, and this encoding occurs for several classes of spatiotemporal correlation that are found in natural vision. Such predictive coding can be explained by known nonlinear circuit mechanisms that produce a nearly optimal encoding, with transmitted information approaching the theoretical limit imposed by the stimulus itself. Thus, these neural circuit mechanisms efficiently separate predictive information from nonpredictive information during the encoding process. The authors utilize information theory to show that four of the output pathways in the primate retina encode predictive information about visual motion. They further show the nonlinear circuit mechanisms that contribute to this computation.

DOI: 10.1038/s41593-021-00899-1

Source: https://www.nature.com/articles/s41593-021-00899-1

Nature Neuroscience:《自然—神经科学》,创刊于1998年。隶属于施普林格·自然出版集团,最新IF:28.771
官方网址:https://www.nature.com/neuro/
投稿链接:https://mts-nn.nature.com/cgi-bin/main.plex


本期文章:《自然—神经科学》:Online/在线发表

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