Human visual performance for identifying letters affected by physiologically-inspired scrambling

Author:

Zhu Xingqi RORCID,Hess Robert F,Baldwin Alex SORCID

Abstract

AbstractIn human vision, the retinal input is transformed into internal representations through a series of stages. In earlier stages, the signals from a particular visual field locus are passed in parallel from one visual processing area to the next. The connections at each stage may therefore introduce “error”, where incorrect or convergent projections result in a loss of spatial precision. Psychophysical and physiological studies have implicated spatial scrambling of this sort as a cause of the visual deficits in amblyopia. Several methods to measure scrambling (both in amblyopia and in healthy vision) have been developed in recent decades. In this work, we introduce a new approach. We consider two stages of visual processing where scrambling may occur: either at the input to or the output from the simple cell stage in V1. We refer to these as “subcortical” and “cortical” scrambling respectively. We investigated the impact of these two types of scrambling on a letter identification task. A physiologically-inspired decomposition and resynthesis algorithm was used to generate letter stimuli that simulate scrambling at each of these two stages. To establish a performance benchmark, we trained separate Convolutional Neural Networks (CNNs) to perform the task with each scrambling type. Comparing CNN performance against that of eight humans with normal healthy vision, we found humans exhibited greater resilience to subcortical scrambling compared to cortical scrambling. We further investigated performance by comparing confusion matrices. Compared to a simple template matching model, we found the human strategy to be more consistent with our CNNs. We conclude: i) the human resilience for subcortical scrambling suggests this may be the stage at which a greater degree of scrambling is introduced in the visual hierarchy, and ii) humans employ flexible strategies for identifying scrambled stimuli, more sophisticated than a simple template match to the expected target.

Publisher

Cold Spring Harbor Laboratory

Reference89 articles.

1. Abadi, M. , Agarwal, A. , Barham, P. , Brevdo, E. , Chen, Z. , Citro, C. , Corrado, G. S. , Davis, A. , Dean, J. , Devin, M. , Ghemawat, S. , Goodfellow, I. , Harp, A. , Irving, G. , Isard, M. , Jia, Y. , Jozefowicz, R. , Kaiser, L. , Kudlur, M. , Levenberg, J. , Mane, D. , Monga, R. , Moore, S. , Murray, D. , Olah, C. , Schuster, M. , Shlens, J. , Steiner, B. , Sutskever, I. , Talwar, K. , Tucker, P. , Vanhoucke, V. , Vasudevan, V. , Viegas, F. , Vinyals, O. , Warden, P. , Wattenberg, M. , Wicke, M. , Yu, Y. , and Zheng, X. (2015). TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems.

2. Rules of Connectivity between Geniculate Cells and Simple Cells in Cat Primary Visual Cortex

3. A psychophysical performance-based approach to the quality assessment of image processing algorithms;PLOS ONE,2022

4. What Do Contrast Threshold Equivalent Noise Studies Actually Measure? Noise vs. Nonlinearity in Different Masking Paradigms;PLOS ONE,2016

5. The equivalent internal orientation and position noise for contour integration;Scientific Reports,2017

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3