The Character Position Encoding of Parafoveal Semantic Previews Is Flexible in Chinese Reading.

Behav Sci (Basel)

Department of Applied Psychology, School of Education Science, Nantong University, Nantong 226019, China.

Published: July 2025


Category Ranking

98%

Total Visits

921

Avg Visit Duration

2 minutes

Citations

20

Article Abstract

Extant Chinese studies have documented that transposing characters within two-character words (e.g., suit) yields greater parafoveal preview benefits for target words compared to replacing the characters with unrelated ones (e.g., a nonword), i.e., the Chinese character transposition effect. This effect has been interpreted as evidence for flexible positional encoding in parafoveal processing, whereby readers tolerate character order disruptions. Alternatively, it has been attributed to morpheme-to-word activation. The present study aims to further clarify the mechanism of the transposition effect. We manipulated four preview conditions of target words in a sentence, identical, semantic, transposed semantic, and control preview, using an eye tracker to record eye movements. Experiment 1 employed reversible word pairs (e.g., tie- lead) as semantical and transposed previews for targets (e.g., suit). Experiment 2 used non-reversible word pairs (e.g., shirt- a nonword). The results revealed comparable processing for both the semantic and transposed semantic preview conditions. Critically, the transposed semantic preview yielded a processing advantage over the unrelated preview. These findings demonstrated that Chinese readers efficiently extract semantic information from the parafoveal region even when character order is disrupted, indicating flexible character position encoding.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC12292683PMC
http://dx.doi.org/10.3390/bs15070907DOI Listing

Publication Analysis

Top Keywords

transposed semantic
12
character position
8
position encoding
8
encoding parafoveal
8
character order
8
preview conditions
8
semantic transposed
8
word pairs
8
semantic preview
8
semantic
7

Similar Publications

Glass largely blurs the boundary between the real world and the reflection. The special transmittance and reflectance quality have confused the semantic tasks related to machine vision. Therefore, how to clear the boundary built by glass, and avoid over-capturing features as false positive information in deep structure, matters for constraining the segmentation of reflection surface and penetrating glass.

View Article and Find Full Text PDF

The Character Position Encoding of Parafoveal Semantic Previews Is Flexible in Chinese Reading.

Behav Sci (Basel)

July 2025

Department of Applied Psychology, School of Education Science, Nantong University, Nantong 226019, China.

Extant Chinese studies have documented that transposing characters within two-character words (e.g., suit) yields greater parafoveal preview benefits for target words compared to replacing the characters with unrelated ones (e.

View Article and Find Full Text PDF

On lexical and sublexical contributions to transposed-phoneme priming effects.

Atten Percept Psychophys

July 2025

Centre de Recherche en Psychologie Et Neurosciences, Aix-Marseille Université & CNRS, Aix-en-Provence, France.

Speech input like [byt] has been shown to facilitate not only the subsequent processing of an identical target word /byt/ but also that of a target word /tyb/ that contains the same phonemes in a different order. In the TISK model of spoken word recognition (Hannagan et al., Frontiers in psychology, 4, 563, 2013), this transposed-phoneme priming effect could result from the activation of shared position-independent phonemes (i.

View Article and Find Full Text PDF

Semantic segmentation is an important branch of image processing and computer vision. With the popularity of deep learning, various convolutional neural networks have been proposed for pixel-level classification and segmentation tasks. In practical scenarios, however, imaging angles are often arbitrary, encompassing instances such as water body images from remote sensing and capillary and polyp images in the medical domain, where prior orientation information is typically unavailable to guide these networks to extract more effective features.

View Article and Find Full Text PDF

With the rapid development of lightweight network models and efficient hardware deployment techniques, the demand for real-time semantic segmentation in areas such as autonomous driving and medical image processing has increased significantly. However, realizing efficient semantic segmentation on resource-constrained embedded platforms still faces many challenges. As a classical lightweight semantic segmentation network, ENet has attracted much attention due to its low computational complexity.

View Article and Find Full Text PDF