School of Mathematics and Information Sciences, Yantai University, Yantai, 264005, China.
State Key Laboratory of Mechanics and Control of Mechanical Structures, Institute of Nano Science and Department of Mathematics, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, China.
Sci Rep. 2023 Jan 27;13(1):1517. doi: 10.1038/s41598-023-28326-4.
Visual perception can be modified by the surrounding context. Particularly, experimental observations have demonstrated that visual perception and primary visual cortical responses could be modified by properties of surrounding distractors. However, the underlying mechanism remains unclear. To simulate primary visual cortical activities in this paper, we design a k-winner-take-all (k-WTA) spiking network whose responses are generated through probabilistic inference. In simulations, images with the same target and various surrounding distractors perform as stimuli. Distractors are designed with multiple varying properties, including the luminance, the sizes and the distances to the target. Simulations for each varying property are performed with other properties fixed. Each property could modify second-layer neural responses and interactions in the network. To the same target in the designed images, the modified network responses could simulate distinguishing brightness perception consistent with experimental observations. Our model provides a possible explanation of how the surrounding distractors modify primary visual cortical responses to induce various brightness perception of the given target.
视觉感知可以被周围环境所改变。具体来说,实验观察表明,视觉感知和初级视觉皮层的反应可以被周围干扰物的特性所改变。然而,其潜在的机制仍不清楚。为了模拟初级视觉皮层的活动,我们设计了一个 k-胜者全取(k-WTA)尖峰网络,其反应是通过概率推理产生的。在模拟中,具有相同目标和不同周围干扰物的图像作为刺激。干扰物具有多种不同的特性,包括亮度、大小和与目标的距离。每种特性的模拟都是在其他特性固定的情况下进行的。每种特性都可以改变网络中的第二层神经反应和相互作用。对于设计图像中的相同目标,经过修改的网络反应可以模拟与实验观察一致的不同亮度感知。我们的模型为周围干扰物如何改变初级视觉皮层的反应以引起给定目标的各种亮度感知提供了一种可能的解释。