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用航向估计模板模型模拟MST神经元的视觉感受野特性。

Emulating the visual receptive-field properties of MST neurons with a template model of heading estimation.

作者信息

Perrone J A, Stone L S

机构信息

Department of Psychology, University of Waikato, Hamilton, New Zealand.

出版信息

J Neurosci. 1998 Aug 1;18(15):5958-75. doi: 10.1523/JNEUROSCI.18-15-05958.1998.

DOI:10.1523/JNEUROSCI.18-15-05958.1998
PMID:9671682
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6793043/
Abstract

We have proposed previously a computational neural-network model by which the complex patterns of retinal image motion generated during locomotion (optic flow) can be processed by specialized detectors acting as templates for specific instances of self-motion. The detectors in this template model respond to global optic flow by sampling image motion over a large portion of the visual field through networks of local motion sensors with properties similar to those of neurons found in the middle temporal (MT) area of primate extrastriate visual cortex. These detectors, arranged within cortical-like maps, were designed to extract self-translation (heading) and self-rotation, as well as the scene layout (relative distances) ahead of a moving observer. We then postulated that heading from optic flow is directly encoded by individual neurons acting as heading detectors within the medial superior temporal (MST) area. Others have questioned whether individual MST neurons can perform this function because some of their receptive-field properties seem inconsistent with this role. To resolve this issue, we systematically compared MST responses with those of detectors from two different configurations of the model under matched stimulus conditions. We found that the characteristic physiological properties of MST neurons can be explained by the template model. We conclude that MST neurons are well suited to support self-motion estimation via a direct encoding of heading and that the template model provides an explicit set of testable hypotheses that can guide future exploration of MST and adjacent areas within the superior temporal sulcus.

摘要

我们之前提出了一种计算神经网络模型,通过该模型,在运动过程中产生的复杂视网膜图像运动模式(光流)可以由作为特定自我运动实例模板的专门探测器进行处理。在这个模板模型中,探测器通过局部运动传感器网络对视野的大部分区域的图像运动进行采样,从而对全局光流做出响应,这些局部运动传感器的特性与在灵长类动物纹外视觉皮层颞中区(MT)发现的神经元特性相似。这些探测器排列在类似皮层的地图中,旨在提取移动观察者前方的自我平移(航向)、自我旋转以及场景布局(相对距离)。然后我们推测,来自光流的航向由内侧颞上区(MST)内充当航向探测器的单个神经元直接编码。其他人质疑单个MST神经元是否能执行此功能,因为它们的一些感受野特性似乎与此作用不一致。为了解决这个问题,我们在匹配的刺激条件下,系统地比较了MST的反应与来自该模型两种不同配置的探测器的反应。我们发现,MST神经元的特征生理特性可以由模板模型来解释。我们得出结论,MST神经元非常适合通过对航向的直接编码来支持自我运动估计,并且模板模型提供了一组明确的可测试假设,可以指导未来对MST和颞上沟内相邻区域的探索。

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