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How Does the Brain Solve Visual Object Recognition?

Author(s)
Zoccolan, Davide; Rust, Nicole C.; DiCarlo, James
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Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.

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Abstract
Mounting evidence suggests that ‘core object recognition,’ the ability to rapidly recognize objects despite substantial appearance variation, is solved in the brain via a cascade of reflexive, largely feedforward computations that culminate in a powerful neuronal representation in the inferior temporal cortex. However, the algorithm that produces this solution remains poorly understood. Here we review evidence ranging from individual neurons and neuronal populations to behavior and computational models. We propose that understanding this algorithm will require using neuronal and psychophysical data to sift through many computational models, each based on building blocks of small, canonical subnetworks with a common functional goal.
Date issued
2012-02
URI
http://hdl.handle.net/1721.1/92249
Department
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences; McGovern Institute for Brain Research at MIT
Journal
Neuron
Publisher
Elsevier
Citation
DiCarlo, James J., Davide Zoccolan, and Nicole C. Rust. “How Does the Brain Solve Visual Object Recognition?” Neuron 73, no. 3 (February 2012): 415–434. © 2012 Elsevier Inc.
Version: Final published version
ISSN
08966273
1097-4199

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