Dynamical systems modeling of Continuous Flash Suppression
Dynamical systems modeling of Continuous Flash Suppression
复制标题
连续闪光抑制的动力系统建模
DOI：
10.1016/j.visres.2011.01.009
复制
发表时间：
2012
期刊：
影响因子：
1.8
通讯作者：
K.
中科院分区：
文献类型：
--
作者：
Shiaoka;D.;Kaneko;K.
连续闪光抑制（CFS）是一种技术，其中一只眼睛中的静止图像可以通过在另一只眼睛中快速呈现不同的闪光图像来可靠地抑制。在本文中，我们解决为什么闪光刺激调制的刺激的可见性。我们确定，特别是，哪种类型的神经网络是足够的调制的优势持续时间，假设元素单位被赋予相互抑制和适应。我们表明，由Wilson（2007）介绍的模型再现了闪光抑制，这被认为是参与CFS，但没有再现CFS。然后，我们扩展模型，包括一个刺激功能的尺寸。通过这种扩展，我们发现该模型解释了CFS中观察到的可见性调制。此外，该模型捕捉到了CFS的一些定义特性，如对闪光间隔和抑制深度的依赖性。我们的研究结果表明，一个网络的抑制和适应，包括功能的尺寸提供了一个重要的机制调制的优势持续时间在CFS。
Continuous Flash Suppression (CFS) is a technique in which a stationary image in one eye can be reliably suppressed by rapid presentation of different flashing images in the other. In this paper we address why flashing stimuli modulate the visibility of the stimuli. We determine, in particular, which type of neural network is sufficient for the modulation of the dominance duration, assuming that elemental units are endowed with reciprocal inhibition and adaptation. We show that the model introduced by Wilson (2007) reproduces flash suppression, which is considered to be involved in CFS, but does not reproduce CFS. We then extend the model by including a stimulus feature dimension. With this extension, we found that the model accounts for the modulation of visibility observed in CFS. In addition, this model captured some defining characteristics of CFS such as dependence on flash interval and the depth of suppression. Our findings suggest that a network with inhibition and adaptation including feature dimension provides a crucial mechanism for the modulation of the dominance duration in CFS.