Evans Benjamin D, Stringer Simon M
Oxford Centre for Theoretical Neuroscience and Artificial Intelligence, Department of Experimental Psychology, University of Oxford, Oxford, UK,
Biol Cybern. 2015 Apr;109(2):215-39. doi: 10.1007/s00422-014-0637-z. Epub 2014 Dec 9.
Learning to recognise objects and faces is an important and challenging problem tackled by the primate ventral visual system. One major difficulty lies in recognising an object despite profound differences in the retinal images it projects, due to changes in view, scale, position and other identity-preserving transformations. Several models of the ventral visual system have been successful in coping with these issues, but have typically been privileged by exposure to only one object at a time. In natural scenes, however, the challenges of object recognition are typically further compounded by the presence of several objects which should be perceived as distinct entities. In the present work, we explore one possible mechanism by which the visual system may overcome these two difficulties simultaneously, through segmenting unseen (artificial) stimuli using information about their category encoded in plastic lateral connections. We demonstrate that these experience-guided lateral interactions robustly organise input representations into perceptual cycles, allowing feed-forward connections trained with spike-timing-dependent plasticity to form independent, translation-invariant output representations. We present these simulations as a functional explanation for the role of plasticity in the lateral connectivity of visual cortex.
学习识别物体和面孔是灵长类动物腹侧视觉系统所面临的一个重要且具有挑战性的问题。一个主要困难在于，尽管物体投射到视网膜上的图像因视角、比例、位置以及其他保持身份的变换而存在巨大差异，但仍要识别该物体。腹侧视觉系统的几种模型已成功应对了这些问题，但通常一次仅接触一个物体。然而，在自然场景中，由于存在多个应被视为不同实体的物体，物体识别的挑战通常会进一步加剧。在本研究中，我们探索了一种可能的机制，通过利用编码在可塑性侧向连接中的类别信息对不可见（人工）刺激进行分割，视觉系统或许能够同时克服这两个困难。我们证明，这些由经验引导的侧向相互作用能够有力地将输入表征组织成感知循环，使通过依赖于尖峰时间的可塑性进行训练的前馈连接形成独立的、平移不变的输出表征。我们将这些模拟结果作为对可塑性在视觉皮层侧向连接中作用的一种功能性解释呈现出来。
