Neuro-computational modeling of perisaccadicvisual perception and attention

在自然视觉期间，人类和非人类灵长类动物每秒进行几次扫视眼球运动，导致视网膜输入的巨大变化。尽管有这些戏剧性的变化，我们的视觉感知仍然非常稳定，我们可以很容易地注意到和指导运动动作对我们的视觉环境中的物体。大量的实验数据描述了不同形式的感受野动力学，我们的目标是通过设计和开发神经计算模型来更好地理解。我们将研究连接视觉，注意力和视觉规划的神经回路，这些神经回路在自然视觉期间稳定感知和注意力表征。这种神经模型最初将主要用于更好地理解大脑中的过程，但从长远来看，它也将指导我们设计受大脑启发的主动视觉系统。

During natural vision humans and non-human primates make several saccadic eye movements each second that result in large changes in the retinal input. Despite these often dramatic changes, our visual percept remains remarkably stable and we can readily attend to and direct motor actions towards objects in our visual environment. A large set of experimental data describes different forms of receptive field dynamics which we aim to better understand by the design and development of neuro-computational models. We will investigate the neural circuits linking vision, attention and oculomotor planning that stabilize perceptual and attentional representations during natural vision. This neural model will be initially primarily used to better understand the processes in the brain, but in the long run, it will also guide us to design brain-inspired, active vision systems.