摘要: 在一个封闭的轮廓线上拐角的数量被认为是形状探测和区分的关键。现有研究的目的是检查拐角数量和拐角之间角度的相对贡献，以形成对复杂视觉场景的区分，也为了确定基于这些具体特点出现与否的眼球图形处理过程的时间进程和神经基质。在实验1中，事件诱发电位被记录下来，然而参加者区分出由相同最大局部曲率确定拐角的两种径像频率（radial frequency，RF）模式，但是这些拐角变化排列。结果显示，在区分的过程中，区分拐角的角度比拐角的总数更重要。增强的负性（posterior N220）在枕叶被引出，跟着一个有三调节周期/圈（RF3）的RF出现，但是没有跟着一个周期/圈，这意味着posterior N220在轮廓线上曲率易于变化。在实验2中，我们确定了拐角出现对于posterior N220的首因效应，增强了刺激以包括由纹理确定的形状。定位于N170和N220的来源在实验2中进行，位于皮质V4区的来源被定位。这些发现意味着拐角包含了重要的区分形状的信息。另外，这项研究显示，知觉特征和神经解剖学基础可以使用电生理学检查检测。
The number of corners on the boundary of a closed contour is thought to be particularly critical for shape detection and discrimination. The aim of the current study was to examine the relative contribution of the number of corners and the angle between corners to shape discrimination in complex visual scenes as well as to determine the time course and neural substrates of global shape processing based on the presence or absence of these specific features. In Experiment 1， event-related potentials were recorded while participants discriminated between two radial frequency (RF) patterns with the same maximum local curvature defining corners but varying arrangements of those corners. The results showed that the angle separating corners was more critical than the overall number of corners for discrimination performance. An enhanced negativity (posterior N220) over the occipital lobe was elicited following the presentation of an RF with three modulation cycles (RF3) but not following a circle， suggesting that the posterior N220 is sensitive to variation in curvature on a contour. In Experiment 2， we confirm the primary effect of the presence of corners on the amplitude of the posterior N220 component and extend the stimuli to include shapes defined by texture. Source localization on the N170 and N220 components was conducted in Experiment 2， and a source in cortical area V4 was identified. These findings suggest that corners contain vital information for the discrimination of shapes. Additionally， this study shows that the perceptual characteristics and neuroanatomical substrates can be detected using electrophysiological measures.