Cant Jonathan S, Xu Yaoda
Department of Psychology, University of Toronto Scarborough, Toronto, ON, Canada.
Visions Sciences Laboratory, Department of Psychology, Harvard University, Cambridge, MA, USA.
Cereb Cortex. 2015 Nov;25(11):4226-39. doi: 10.1093/cercor/bhu145. Epub 2014 Jun 25.
Behavioral research has demonstrated that observers can extract summary statistics from ensembles of multiple objects. We recently showed that a region of anterior-medial ventral visual cortex, overlapping largely with the scene-sensitive parahippocampal place area (PPA), participates in object-ensemble representation. Here we investigated the encoding of ensemble density in this brain region using fMRI-adaptation. In Experiment 1, we varied density by changing the spacing between objects and found no sensitivity in PPA to such density changes. Thus, density may not be encoded in PPA, possibly because object spacing is not perceived as an intrinsic ensemble property. In Experiment 2, we varied relative density by changing the ratio of 2 types of objects comprising an ensemble, and observed significant sensitivity in PPA to such ratio change. Although colorful ensembles were shown in Experiment 2, Experiment 3 demonstrated that sensitivity to object ratio change was not driven mainly by a change in the ratio of colors. Thus, while anterior-medial ventral visual cortex is insensitive to density (object spacing) changes, it does code relative density (object ratio) within an ensemble. Object-ensemble processing in this region may thus depend on high-level visual information, such as object ratio, rather than low-level information, such as spacing/spatial frequency.
行为研究表明,观察者能够从多个物体的集合中提取统计概要。我们最近发现,腹侧视觉皮层前内侧的一个区域,很大程度上与对场景敏感的海马旁回位置区(PPA)重叠,参与了物体集合的表征。在此,我们使用功能磁共振成像适应技术研究了该脑区中集合密度的编码。在实验1中,我们通过改变物体之间的间距来改变密度,结果发现PPA对这种密度变化不敏感。因此,密度可能不在PPA中编码,这可能是因为物体间距未被视为集合的固有属性。在实验2中,我们通过改变构成集合的两种物体的比例来改变相对密度,并观察到PPA对这种比例变化有显著的敏感性。尽管在实验2中展示的是色彩丰富的集合,但实验3表明,对物体比例变化的敏感性并非主要由颜色比例的变化驱动。因此,虽然腹侧视觉皮层前内侧对密度(物体间距)变化不敏感,但它确实对集合内的相对密度(物体比例)进行编码。该区域的物体集合处理可能因此依赖于高级视觉信息,如物体比例,而非低级信息,如间距/空间频率。