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A separable neural code in monkey IT enables perfect CAPTCHA decoding

Katti, H and Arun, SP (2022) A separable neural code in monkey IT enables perfect CAPTCHA decoding. In: Journal of Neurophysiology, 127 (4). pp. 869-884.

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Official URL: https://doi.org/10.1152/jn.00160.2021


Reading distorted letters is easy for us but so challenging for the machine vision that it is used on websites as CAPTCHA (Completely Automated Public Turing Test to tell Computers and Humans Apart). How does our brain solve this problem? One solution is to have neurons selective for letter combinations but invariant to distortions. Another is for neurons to encode letter distortions and longer strings to enable separable decoding. Here, we provide evidence for the latter possibility using neural recordings in the monkey inferior temporal (IT) cortex. Neural responses to distorted strings were explained better as a product (but not sum) of shape and distortion tuning, whereas by contrast, responses to letter combinations were explained better as a sum (but not product) of letters. These two rules were sufficient for perfect CAPTCHA decoding and were also emergent in neural networks trained for word recognition. Thus, a separable neural code enables efficient letter recognition. © 2022 the American Physiological Society.

Item Type: Journal Article
Publication: Journal of Neurophysiology
Publisher: American Physiological Society
Additional Information: The copyright for this article belongs to the Authors.
Keywords: animal experiment; article; Haplorhini; inferior temporal cortex; nerve cell; nerve potential; nonhuman; word recognition; animal; Haplorhini; pattern recognition; physiology; reading; software; temporal lobe, Animals; Haplorhini; Neural Networks, Computer; Pattern Recognition, Visual; Reading; Software; Temporal Lobe
Department/Centre: Division of Biological Sciences > Centre for Neuroscience
Date Deposited: 20 Jun 2022 11:43
Last Modified: 20 Jun 2022 11:43
URI: https://eprints.iisc.ac.in/id/eprint/73700

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