Shape Similarity, Better than Semantic Membership, Accounts for the Structure of Visual Object Representations in a Population of Monkey Inferotemporal Neurons

被引:71
作者
Baldassi, Carlo [1 ,2 ,3 ]
Alemi-Neissi, Alireza [3 ,4 ]
Pagan, Marino [5 ,6 ,7 ]
DiCarlo, James J. [5 ,6 ]
Zecchina, Riccardo [1 ,2 ,3 ]
Zoccolan, Davide [4 ,5 ,6 ]
机构
[1] Politecn Torino, Dept Appl Sci & Technol, Turin, Italy
[2] Politecn Torino, Ctr Computat Sci, Turin, Italy
[3] Human Genet Fdn HuGeF, Turin, Italy
[4] SISSA, Int Sch Adv Studies, I-34014 Trieste, Italy
[5] MIT, Dept Brain & Cognit Sci, Cambridge, MA 02139 USA
[6] MIT, McGovern Inst Brain Res, Cambridge, MA 02139 USA
[7] Univ Penn, Dept Psychol, Philadelphia, PA 19104 USA
基金
欧洲研究理事会;
关键词
INFERIOR TEMPORAL CORTEX; LONG-TERM-MEMORY; NATURAL IMAGES; HUMAN BRAIN; INFORMATION; RECOGNITION; AREA; SELECTIVITY; CATEGORY; TRANSFORMATION;
D O I
10.1371/journal.pcbi.1003167
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
The anterior inferotemporal cortex (IT) is the highest stage along the hierarchy of visual areas that, in primates, processes visual objects. Although several lines of evidence suggest that IT primarily represents visual shape information, some recent studies have argued that neuronal ensembles in IT code the semantic membership of visual objects (i.e., represent conceptual classes such as animate and inanimate objects). In this study, we investigated to what extent semantic, rather than purely visual information, is represented in IT by performing a multivariate analysis of IT responses to a set of visual objects. By relying on a variety of machine-learning approaches (including a cutting-edge clustering algorithm that has been recently developed in the domain of statistical physics), we found that, in most instances, IT representation of visual objects is accounted for by their similarity at the level of shape or, more surprisingly, low-level visual properties. Only in a few cases we observed IT representations of semantic classes that were not explainable by the visual similarity of their members. Overall, these findings reassert the primary function of IT as a conveyor of explicit visual shape information, and reveal that low-level visual properties are represented in IT to a greater extent than previously appreciated. In addition, our work demonstrates how combining a variety of state-of-the-art multivariate approaches, and carefully estimating the contribution of shape similarity to the representation of object categories, can substantially advance our understanding of neuronal coding of visual objects in cortex.
引用
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页数:21
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