小柯机器人

科学家绘制出灵长类下颞叶皮质的对象空间地图
2020-06-05 10:04

美国加州理工学院Doris Y. Tsao、Pinglei Bao等研究人员合作绘制出灵长类下颞叶皮质的对象空间地图。2020年6月3日,《自然》杂志在线发表了这一最新研究成果。

研究人员使用功能性MRI、微刺激、电生理学和深层网络来研究了猕猴颞下(IT)皮质组织。研究人员使用在对象分类上训练的前馈深度神经网络构建了一个低维的对象空间来描述一般对象。IT单元对大量对象的响应表明,单个IT单元将传入的对象投影到该空间的特定轴上。
 
解剖学上,根据其首选轴的前两个成分将细胞聚集成四个网络,从而形成物体空间图。在增加视图不变性的三个层次阶段重复了此图,组成这些图的单元格集体具有足够的编码能力来近似重建对象。这些结果为IT组织提供了一个统一的图谱,其中类别选择区域是对象空间的粗略地图的一部分,这些维度可以从深度网络中提取。
 
据了解,颞下皮质负责对象识别,但尚不清楚在大脑的这一部分如何组织视觉对象的表现。对于面孔、身体和场景等类别进行选择性识别的区域已被发现,但是对IT皮质的大部分区域仍缺少认知,一个关键问题是什么通用原则指导了IT组织。
 
附:英文原文

Title: A map of object space in primate inferotemporal cortex

Author: Pinglei Bao, Liang She, Mason McGill, Doris Y. Tsao

Issue&Volume: 2020-06-03

Abstract: The inferotemporal (IT) cortex is responsible for object recognition, but it is unclear how the representation of visual objects is organized in this part of the brain. Areas that are selective for categories such as faces, bodies, and scenes have been found1,2,3,4,5, but large parts of IT cortex lack any known specialization, raising the question of what general principle governs IT organization. Here we used functional MRI, microstimulation, electrophysiology, and deep networks to investigate the organization of macaque IT cortex. We built a low-dimensional object space to describe general objects using a feedforward deep neural network trained on object classification6. Responses of IT cells to a large set of objects revealed that single IT cells project incoming objects onto specific axes of this space. Anatomically, cells were clustered into four networks according to the first two components of their preferred axes, forming a map of object space. This map was repeated across three hierarchical stages of increasing view invariance, and cells that comprised these maps collectively harboured sufficient coding capacity to approximately reconstruct objects. These results provide a unified picture of IT organization in which category-selective regions are part of a coarse map of object space whose dimensions can be extracted from a deep network.

DOI: 10.1038/s41586-020-2350-5

Source: https://www.nature.com/articles/s41586-020-2350-5

Nature:《自然》,创刊于1869年。隶属于施普林格·自然出版集团,最新IF:43.07
官方网址:http://www.nature.com/
投稿链接:http://www.nature.com/authors/submit_manuscript.html


本期文章:《自然》:Online/在线发表

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