The Effective Visual Field in Reading Chinese
May 2019
Volume 60, Issue 6
Figure 1
A schematic drawing illustrating the basic experimental pattern of the written report. A total of 26 subjects were randomly assigned to 2 groups: a control group (north = 13) and a grooming group (n = xiii). The pretest and posttest consisted of measurements of sentence-reading speed and visual-bridge profile. Subjects belonging to the control grouping received only the pretest and posttest, while each subject in the preparation group took a pretest and a posttest with an intervening grooming procedure consisting of four sessions, scheduled on 4 sequent days.
Figure ii
The stimulus ready for the trigram character-recognition task selected from the C3 grouping in Wang et al.56 Based on the perimetric complexity,57 the 700 virtually often used Chinese characters (ordered past frequency in Country Linguistic communication Piece of work Committee, Bureau of Standard, 1992) were separate into five mutually sectional groups. 20-six characters with complexity values close to the median complexity value in each grouping were chosen to plant C1 to C5 subgroups. The median complexity subgroup (C3) was selected for the trigram character-recognition chore in this study.
Figure 3
The visual-span profile measurement for Chinese characters using the trigram graphic symbol-recognition method. (A) Schematic illustration of visual-bridge profile. Top: A cord of three characters (
, 
, 
) was presented at position four in the horizontal midline. The gray numbers indicate the position of each slot, which was non presented during the test. The size of visual span was quantified using two methods: the width of the fitted split-Gaussian bend at 80% of recognition accuracy (number of characters) and the measure of the area nether the split-Gaussian bend in bits of information transmitted. Bottom: The visual-span profile was a plot of recognition accuracy by grapheme positions and then transformed to information transmitted ($.25). The recognition accurateness approached 100% at the fixation point and gradually dropped with increasing altitude from the fixation betoken. (B) Schematic illustration of visual-span measurement. After the white dot fixation stimulus was displayed at the center of the black screen for thousand ms, two vertically aligned greenish dots were presented in the heart of the screen to maintain stable fixation until the cease of each trial. Three underlines were displayed for l ms indicating the next trigram positions. After a lxx-ms duration of the two vertical green dots, the trigram stimulus was presented on the screen for 250 ms. Then, the screen went bare, and the subject was required to study the iii characters of the trigram in order, from left to right.
Figure 4
Schematic illustration of judgement-reading chore. The sentences were chosen from the reading material of Liu et al.60 Prior to the sentence-reading job, subjects were told to read the sentence as fast as possible and respond a comprehension question afterwards each sentence. Subsequently a fixation calibration, the fixation dot was displayed at the center of the screen. Subjects pressed the space bar on the keyboard to initiate the judgement presentation on the horizontal midline of the reckoner screen. Subjects pressed the space bar again to signal the completion of the sentence reading and termination of the trial. English language translations were provided for illustrative purposes and were not shown during the experiment.
Figure v
Schematic illustration of decomposition analysis. Perfect performance − standard profile = resolution/acuity consequence + crowding outcome + mislocation errors effect. Acuity outcome = perfect contour − unmarried-letter of the alphabet profile (green area). Crowding consequence = single-alphabetic character contour − mislocation profile (blueish expanse). Mislocation effect = mislocation profile − standard contour (scarlet area). Three types of visual-span profiles were plotted: a standard contour with both correct recognition of the character and its position in the trigram, a profile permitting mislocation errors, and a profile based on single-graphic symbol recognition accuracy. The losses in data transmitted resulting from limitations in visual resolution, the bear upon of crowding, and mislocation errors were computed past comparing these three types of VSPs with 100% perfect performance. The contribution of vigil was quantified by comparing 100% perfect performance and the single-character profile. The upshot of crowding was assessed past the losses of information transmitted betwixt the unmarried-character profile and mislocation errors survival profile. The bear upon of mislocations was divers by comparing the mislocation errors profile with the standardized profile.
Figure half-dozen
Visual-span profiles for pretest (dashed line) and posttest (line) in the control group and the training group. (A) Raw data. (B) Fitted split-Gaussian curve. Character recognition performance across graphic symbol positions in the command and the training groups are presented in Figure 7. The raw information (A) and fitted curve (B) of recognition accurateness for 13 trigram positions showed that the visual-bridge size in the posttest was larger than that in the pretest in the training group, suggesting an enhancement in graphic symbol identification performance across most character positions later grooming.
Figure 7
Main parameters: (A) size of the visual span in the number of Chinese characters, (B) size of the visual bridge in bits of information transmitted, and (C) reading speed betwixt the pretest and posttest in the control and preparation grouping. Error bars represent ±1 SEM. n.southward., not meaning. ***P < 0.001. The size of visual span in Chinese characters, the size of visual span in bits of information transmitted, and judgement-reading speed between pretest and posttest were similar in the command group (all Bonferroni corrected P > 0.05). In the training group, the visual-span size in the number of Chinese characters, in $.25 of information transmitted, and judgement-reading speeds were extended from 5.04 ± 0.96 to 8.41 ± i.47 characters (Bonferroni corrected P < 0.001), from 32.viii ± 3.99 to 44.4 ± 3.89 bits (Bonferroni corrected P < 0.001), and from 319.0 ± 74.ii to 484.6 ± 161.3 cpm (Bonferroni corrected P < 0.001) after 4-day grooming.
Figure 8
Parameters of visual-span profiles between pretest and posttest in the control and training groups. Error bars represent ±ane SEM. n.south., not meaning. ***P < 0.001. (A, D) showed that the changes in the peak amplitude and foveal surface area of the visual-span profiles were not statistically different betwixt pretest and posttest in the control and the training groups (all Bonferroni corrected P > 0.05). (B, C, East, F) showed significant differences between the posttest and pretest visual-span profile's parameters, including standard deviation \({\sigma _L}\) and \({\sigma _R}\), parafoveal left area, and parafoveal correct surface area in the training group (all Bonferroni corrected P < 0.001), besides as similar magnitudes in these parameters in the control group (all Bonferroni corrected P > 0.05).
Figure ix
Decomposition analysis of the visual span. Upper: Comparison of decomposition profiles in pretest and posttest. Mistake bars represent ±one SEM. due north.s., not pregnant. **P < 0.01; ***P < 0.001. Decomposition analysis of the visual bridge. The area representing the crowding effects (blue) was significantly larger than the areas representing the mislocation effects (red). A notable reduction in the surface area representing the crowding effects (blueish) from pretest to posttest was observed in the grooming group. Lower: Comparison of effects for each factor in pretest and posttest. There was a pregnant reduction in the furnishings of crowding (xiii.one bits) and a pocket-sized increase in mislocation furnishings (i.46 bits) post-obit training in the training grouping. The impact of crowding and mislocation was similar in the pretest and posttest in the control grouping (all Bonferroni corrected P > 0.05).
Table 1
Results of the Linear Mixed Model Analysis of Reading Speed, Visual-Span Size in Number of Chinese Characters, and in Information Transmitted
Tabular array 2
Results of the Linear Mixed Model Analysis of Peak Amplitude, Standard Deviation of the Left and the Right, Foveal Area, Parafoveal Correct and Left Area One-half of the Gaussian Curve, Crowding, and Mislocation Errors Effect
Copyright 2019 The Authors
Source: https://iovs.arvojournals.org/article.aspx?articleid=2734880
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