The neural substrates of object-ensemble processing in the human brain

我们看待世界的方式对我们作为人类的生存极其重要。例如，能够找到吃的食物、社交的朋友和交配的伴侣的能力需要一个视觉系统，能够快速准确地识别任何给定环境中的物体和个人。乔纳森·坎特博士实验室的研究探索了这些问题，特别是人类大脑如何处理物体和场景。之前使用一种名为功能磁共振成像(FMRI)的现代大脑成像技术的研究表明，大脑中被称为海马旁区域(简称PPA)的一个区域在场景感知中发挥着重要作用，这是通过处理场景的3D空间结构或几何图形来实现的。然而，坎特博士最近发现，PPA不仅仅处理场景的几何图形。具体地说，他是第一个证明PPA参与处理多个对象(例如，一棵树上的所有叶子)的大型集合或集合的人。虽然我们对大脑如何处理对象集合知之甚少，但我们知道它们极其重要，因为集合处理需要将大量冗余的视觉信息压缩成一个单一的汇总特征(例如，树上所有树叶的平均大小)，从而为大脑节省大量时间和精力。如果我们的视觉系统必须逐一处理一棵树上的每一片叶子，或者一块田地里的每一片草的叶片，我们就无法有效地感知场景！因此，坎特博士目前的研究计划的目标是了解大脑如何处理多个对象的集合，以及这种类型的处理与我们在集合中挑选和识别一个对象的能力(即对单个对象的感知)之间的关系。这项研究不仅将帮助科学家了解视觉大脑是如何组织的，还将帮助工程师开发更好的机器视觉系统，因为计算机视觉系统中使用的许多设计原则的灵感来自于对人类如何在复杂场景中感知单个对象的研究(例如，数码相机识别人们在拍摄场景中所处位置的能力)。

The way in which we see the world is extremely important to our survival as human beings. For example, the ability to be able to find food to eat, friends to socialize with, and partners to mate with requires a visual system that can rapidly and accurately identify the objects and individuals in any given environment. Research in Dr. Jonathan Cant's laboratory explores these issues, in particular how the human brain processes objects and scenes. Previous research using a modern brain imaging technique known as functional magnetic resonance imaging (fMRI) has demonstrated that a region of the brain known as the parahippocampal place area (or PPA for short) plays a large role in scene perception, and does so by processing the 3D spatial structure, or geometry, of scenes. Dr. Cant has recently discovered however, that the PPA does more than just process the geometry of a scene. Specifically, he was the first to show that the PPA is involved in processing what is known as large collections, or ensembles, of multiple objects (e.g. all the leaves on a tree). While we do not know much about how the brain processes object ensembles, we do know that they are extremely important, as ensemble processing entails collapsing a lot of redundant visual information into a single summary feature (e.g. the average size of all the leaves on a tree), thereby saving the brain a lot of time and energy. We would simply not be able to perceive scenes efficiently if our visual system had to process every individual leaf on a tree one-by-one, or every individual blade of grass in a field! Thus, the goal of Dr. Cant's current research program is to understand how the brain processes ensembles of multiple objects, and how this type of processing relates to our ability to pick out and identify one object within the ensemble (that is, single-object perception). This research will not only help scientists understand how the visual brain is organized, but will help engineers develop better machine-vision systems, since many of the design principles used in computer vision systems are inspired by research on how humans perceive individual objects within complex scenes (e.g. the ability of digital cameras to recognize where people are standing in the scene you are taking a picture of).