Centre for BioSystems Science & Engineering, Indian Institute of Science, Bangalore, India.
Department of Electrical Communication Engineering, Indian Institute of Science, Bangalore, India.
Elife. 2020 May 5;9:e54846. doi: 10.7554/eLife.54846.
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.
我们毫不费力地读懂乱序单词,但这种非凡能力的神经关联仍知之甚少。我们假设,看到一个乱序单词会激活一个视觉表示,然后与已知单词进行比较。为了验证这一假设,我们设计了一个纯粹的视觉模型,其中对字母形状敏感的神经元以组合的方式对更长的字符串进行调谐,通过线性地将字母响应相加。我们发现,该模型中字母串之间的差异可以解释人类在视觉搜索中的表现,以及在阅读任务中对乱序单词的反应。脑成像显示,在外侧枕叶(LO)区域,看到一个字符串会激活这种基于字母的代码,而随后与存储的单词进行的比较与视觉单词形式区域(VWFA)的激活一致。因此,组合的神经代码可能有助于高效阅读。