A compositional neural code in high-level visual cortex can explain jumbled word reading

被引:19
作者
Agrawal, Aakash [1 ]
Hari, K. V. S. [2 ]
Arun, S. P. [3 ]
机构
[1] Indian Inst Sci, Ctr BioSyst Sci & Engn, Bangalore, Karnataka, India
[2] Indian Inst Sci, Dept Elect Commun Engn, Bangalore, Karnataka, India
[3] Indian Inst Sci, Ctr Neurosci, Bangalore, Karnataka, India
基金
英国惠康基金;
关键词
MONKEY INFEROTEMPORAL CORTEX; INTERACTIVE ACTIVATION MODEL; LETTER PERCEPTION; SEARCH; SIMILARITY; FREQUENCY; CONTEXT; REPRESENTATIONS; RECOGNITION; FAMILIARITY;
D O I
10.7554/eLife.54846
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
We read jubmled wrods effortlessly, but the neural correlates of this remarkable ability remain poorly understood. We hypothesized that viewing a jumbled word activates a visual representation that is compared to known words. To test this hypothesis, we devised a purely visual model in which neurons tuned to letter shape respond to longer strings in a compositional manner by linearly summing letter responses. We found that dissimilarities between letter strings in this model can explain human performance on visual search, and responses to jumbled words in word reading tasks. Brain imaging revealed that viewing a string activates this letter-based code in the lateral occipital (LO) region and that subsequent comparisons to stored words are consistent with activations of the visual word form area (VWFA). Thus, a compositional neural code potentially contributes to efficient reading.
引用
收藏
页数:58
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