Abstract

Object recognition is the ability to identify an object or category based on the combination of visual features observed. It is a remarkable feat of the human brain, given that the patterns of light received by the eye associated with the properties of a given object vary widely with simple changes in viewing angle, ambient lighting, and distance. Furthermore, different exemplars of a specific object category can vary widely in visual appearance, such that successful categorization requires generalization across disparate visual features. In this review, we discuss recent advances in understanding the neural representations underlying object recognition in the human brain. We highlight three current trends in the approach towards this goal within the field of cognitive neuroscience. Firstly, we consider the influence of deep neural networks both as potential models of object vision and in how their representations relate to those in the human brain. Secondly, we review the contribution that time-series neuroimaging methods have made towards understanding the temporal dynamics of object representations beyond their spatial organization within different brain regions. Finally, we argue that an increasing emphasis on the context (both visual and task) within which object recognition occurs has led to a broader conceptualization of what constitutes an object representation for the brain. We conclude by identifying some current challenges facing the experimental pursuit of understanding object recognition and outline some emerging directions that are likely to yield new insight into this complex cognitive process.

Highlights

  • Object recognition is one of the classic “problems” of vision[1]

  • The underlying neural substrate in humans was revealed by classic neuropsychological studies which pointed to selective deficits in visual object recognition following lesions to specific brain regions[2,3], yet we still do not understand how the brain achieves this remarkable behavior

  • The application of multivariate analysis techniques has led to broader investigation of the structure of object representationsa throughout the ventral temporal cortex[16,17] and their temporal dynamics across the whole brain[18,19]

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Summary

11 Jun 2020

Faculty Reviews are written by members of the prestigious Faculty Opinions Faculty. They are commissioned and are peer reviewed before publication to ensure that the final, published version is comprehensive and accessible. The reviewers who approved the final version are listed with their names and affiliations. Any comments on the article can be found at the end of the article

Introduction
Warrington EK
Biederman I
11. Ullman S
24. Serre T: Deep Learning
54. Martin A
83. Simoncelli EP
Full Text
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