The participants were instructed to write down 42 two-character words after hearing a word read to them in each trial by the experimenter. One point was given for each correct character written by the participants.
This subtest from HKT-P III measured rapid automatized naming of highly familiar visual stimuli, a task that closely predicts literacy performance across difference languages The participants were presented with a matrix of 8 rows of 5 digits arranged in random sequences, and were instructed to name aloud the digits in serial order as quickly and as accurately as possible.
They were instructed to perform the task twice, and the score was the average time taken for the two trials.
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They also are in line with the conception of the visual word form area as a region that subserves expert parallel processing of letters [28]. According to this dual stream model, native speakers would use this ventral route for real words and the dorsal route for pseudowords. Individuals with less expertise may rely more on the dorsal stream, or on more posterior regions of the ventral stream. Our study represents one of the few attempts to bridge the literature on holistic processing between words and other objects of expertise by using a common paradigm see also Farah et al.
The composite paradigm captures one type or aspect of holistic processing: the obligatory attention to multiple parts. Although there are other ways to assess holistic processing [11] , [54] , [55] , [56] , this paradigm has been used for many other object categories [3] , [4] , [5] , [6] , [7] , and thus is an ideal method for identifying general principles of neural plasticity in object perception.
Previous studies on other object categories have emphasized the need for subordinate-level discrimination for development of holistic processing [7]. It is not clear whether this principle also applies to expert word recognition, which at some level, at least, is thought to involve coarser, basic-level processing that is more part-based [7] , [32] , [33]. Of course, a limitation of our study is that we did not test the same participants on both words and a category involving subordinate-level expertise typically faces and compare their holistic processing effects.
And even if the same paradigm shows similar magnitudes of holistic processing for two categories, one cannot conclude that the effects are of a similar nature. Future studies should therefore compare not only the magnitudes of but also the neural loci of and factors modulating holistic processing for different object categories. We would like to thank Kathryn Roberts and Jessica Miller for their assistance in developing the stimuli and data collection.
Analyzed the data: ACNW. Browse Subject Areas? Click through the PLOS taxonomy to find articles in your field. Abstract Perceptual expertise has been studied intensively with faces and object categories involving detailed individuation. Introduction Recent years have seen a surge of interest in the study of perceptual expertise for different object categories, such as faces [1] , [2] , cars [3] , [4] , fingerprints [5] , music notes [6] , and novel computer-generated objects [7] , [8].
Download: PPT. Methods Experiment 1 Ethics Statement. Experiment 2 Ethics Statement. Discussion In two experiments, we showed robust holistic processing for words: matching target parts of a word was interfered by the irrelevant parts, and such interference was reduced when the parts were misaligned.
Supporting Information. Table S1. Word stimuli in Experiment 1. Table S2. Word stimuli in Experiment 2. Acknowledgments We would like to thank Kathryn Roberts and Jessica Miller for their assistance in developing the stimuli and data collection. References 1. Journal of Cognitive Neuroscience — View Article Google Scholar 2. Psychological Science.
Nature Neuroscience 6: — View Article Google Scholar 4. View Article Google Scholar 5. Busey TA, Vanderkolk JR Behavioral and electrophysiological evidence for configural processing in fingerprint experts.
Vision Research — View Article Google Scholar 6. Wong YK, Gauthier IHolistic processing of musical notation: Dissociating failures of selective attention in experts and novices. Psychological Science — View Article Google Scholar 8. View Article Google Scholar 9. View Article Google Scholar Hole GJ Configurational factors in the perception of unfamiliar faces. Perception 65— Trends Cogn Sci 6: — Robbins R, McKone E No face-like processing for objects-of-expertise in three behavioural tasks.
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Cognitive Neuropsychology — Grainger J, Whitney C Does the huamn mnid raed wrods as a wlohe? The behavioral data for adults from this fMRI study has been published Collins et al. All subjects had normal or corrected-to-normal visual acuity and normal color vision.
For Dataset 2 all subjects were right-handed as required for the fMRI study. No participants reported neurological or psychiatric diagnoses, learning disability, medical conditions, or pregnancy.
Children provided assent and a parent provided informed consent before participating. Children and adults were compensated for participation but some adults received course credit instead of compensation. Although Dataset 2 did not manipulate orientation, the data were used in a supplementary analysis to increase sample size and assess the reliability of the effects obtained with only Dataset 1.
Twenty-four faces or houses were initially constructed so that none of the features overlapped across these 24 stimuli. These were used as the basis for making featural changes and constructing stimulus pairs that varied in similarity.
Sim0—sim3 faces respectively shared 0—3 common features with the target face. The feature changed for each sim level was counterbalanced across all stimulus pairs so that feature replacement was not confounded with sim level.
The same procedures were used for house features door, steps, lower-level and upper-level windows. For faces, an initial spacing of 2 SD from the norms published by Farkas, was used, but was changed to a 3 SD spacing after 2 SD was identified as being too difficult to detect. The house changes were: a horizontal distance between the centroid of both lower windows, b horizontal distance between the centroid of both upper windows, c vertical distance between center of lower windows and bottom of roof, and d vertical distance between center of upper windows and bottom of roof.
Again, the relation changed for each sim level was counterbalanced across all pairs to avoid confounding with sim level. Some of the pairs used for upright trials 38 different pairs and 10 same pairs were also used for inverted trials, with the remaining inverted trials consisting of unique stimulus pairs that were not used on upright trials.
Each subject received a random order of the trials, which were broken up into four blocks of 80 trials providing rest periods for the participants. On each trial, participants saw either two faces or two houses for ms followed by a fixation interval for ms. Participants indicated whether the two stimuli were the same index finger or different middle finger using a serial response box.
Participants could respond at any point during the trial. The duration and trial length were fixed because we conducted the behavioral and fMRI study in parallel and wanted to equate the designs of the two studies and fMRI studies necessarily require a fixed interval for responding.
We also wanted a brief period in between trials to present a blank screen; otherwise the stimuli would appear in a consecutive stream which would greatly increase the difficulty of the task. No feedback was given about performance because the major goal was to study perception of faces rather than learning. For Dataset 2 each participant completed trials broken up into four runs of 64 trials each. Two of the runs were face matching and two runs were house matching.
The order of the four runs was counterbalanced across subjects. Participants had rest breaks between blocks and between runs.
Reaction time on each correct trial was log 10 transformed logRT to meet the assumption of normality for multivariate tests. Outliers were determined separately for each age group and processing type and defined by logRTs that were more than 3 SD above or below the mean. Outliers accounted for 0. Errors were defined as incorrect responses or response omissions and the average error rate per condition was used in analyses.
Analyzing logRT across age groups for Hypotheses 1 and 2 as a function of similarity needs to address the concern of interpreting scale-dependent interactions Salthouse and Hedden, Specifically, differences in logRT as a function of age group or experimental condition cannot be interpreted unless those differences occur at the same parts of the RT scale. Given that children and adults usually perform at different parts of the RT scale, we addressed this in each analysis in the following ways.
First, in the analyses for Hypotheses 1 and 3, each age group and processing type was analyzed separately so concerns about age differences in RT did not need to be accounted for directly in the analyses.
Second, in the analysis for Hypotheses 2a and 2b, which compared age groups directly, an ANCOVA approach was used in which logRT or errors in the sim0 condition served as the covariate, similarity sim1—sim3 was the repeated factor and age group was the between-subjects factor. Sim0 is the best candidate for a covariate because it represents a baseline level of performance in which all features or relations are different between the stimuli, but the RT would still reflect other cognitive operations such as orientation to the stimuli, response selection and response execution that may differ across age groups.
The design used in this study Dataset 1 was a full factorial design with three within-subjects variables category, orientation and similarity and two between-subjects variables age, processing type. First, there were not enough degrees of freedom to estimate the four-way and five-way interactions given the number of subjects in each age group at least for the featural condition.
Second, the ANCOVA approach used sim0 as the covariate for a given condition such as upright faces or inverted houses. Therefore, each hypothesis was tested with analyses for some subset of the variables described for each hypothesis below.
When interactions with similarity were present, simple effects analysis Keppel and Zedeck, of similarity was conducted. The simple effects analysis would indicate whether the similarity function was significant for a given condition. Polynomial contrasts were then conducted to indicate whether the similarity function followed a linear trend. Although error rates are not necessarily subject to the same concern of scale-dependent interactions but see Salthouse and Hedden, , we used the same ANCOVA approach for the analysis of error rates to keep the analyses consistent.
However, we used the RT measure in order to examine serial versus parallel processing as that is the most typical measure used to estimate these processes.
Following other findings in the literature, adults and older children were expected to show a stronger face inversion effect than younger children. This analysis only used data from Dataset 1 as that was the only dataset with an inversion manipulation.
In addition, featural and 2 nd order conditions were analyzed separately given that initial inspection of error rates revealed that 2 nd order matching was more difficult. Repeated measures ANOVAs with logRT and errors as dependent variables and category face, house and orientation inverted, upright were conducted separately for adults, older children and younger children.
As shown in Figure 3A adults and older children showed a trend for a greater inversion effect for featural faces than for featural houses with respect to errors, but younger children did not show this interaction. Face and house matching performance as a function of inversion in each age group and for each processing type.
A Shows error rates top and logRT bottom for each age group in the featural condition. B Shows error rates top and logRT bottom for each age group in the 2 nd order condition. Error bars are SE of the mean. For 2 nd order configural faces and houses, all three age groups showed a trend for a face inversion effect with respect to errors Figure 3B. Face and house matching error rates as a function of inversion, similarity, and age group for the featural condition.
A Results for upright faces. B Results for inverted faces. C Results for upright houses. D Results for inverted houses. Error bars are not shown given the complexity of the graphs. Face and house matching error rates as a function of inversion, similarity, and age group for the 2 nd order condition. In summary, although there were no specific hypotheses with respect to error rates, this analysis was presented to show that adults perform the task more accurately than children, as expected.
However, there were few age differences in similarity functions for either featural or 2 nd order faces. Only upright featural houses and upright 2 nd order faces showed interactions with age. One important point from this analysis was that, even though error rates were quite high for some conditions, the primary analysis used RT only on correct trials. Therefore, in subsequent analyses, speed-accuracy tradeoffs are not driving the effects.
This analysis was conducted to test Hypothesis 2a, which predicts that adults and older children should engage a serial comparison process as a function of similarity of the face pairs and show more sloped similarity functions with a positive linear trend whereas younger children should show more evidence for parallel processing and show flatter similarity functions and no positive linear trend.
When this interaction was significant, simple main effects Keppel and Zedeck, of similarity for each age group were also examined to determine whether the similarity function was positive and linear as an indication of serial processing.
The linear trend was assessed using planned polynomial contrasts. Results are presented first for Dataset 1, which manipulated orientation in addition to similarity and category. Parallel processing seems to persist across inversion and category manipulations. In contrast, similarity functions for adults have steeper slopes than those for children, especially for face stimuli. Older children show a pattern that is intermediate to adults and younger children for upright faces, but that is similar to younger children for inverted faces.
Older children look similar to adults for house stimuli. Face and house matching logRT as a function of inversion, similarity, and age group for the featural condition. However, the simple effect of similarity was not significant for any age group. However, this effect was driven by sim3 having faster RTs than the other sim levels Figure 6B so the linear trend was in the negative direction, which is not consistent with serial processing.
Adults always showed the highest RT but older children were similar to adults for inverted houses , a pattern suggesting a trend toward serial exhaustive search. Data from Dataset 2 were combined with the data from Dataset 1 and analyses were rerun. As mentioned, these analyses only applied to upright stimuli as Dataset 2 did not manipulate orientation.
Younger children again show flatter similarity functions, or even negative-going patterns for some conditions, compared to older children and adults. Older children show functions that have similar slopes to adults across all conditions. Face and house matching logRT as a function of inversion, similarity, and age group for the 2 nd order condition.
Similar to the finding for featural faces, adults always have a longer RT on same trials than on different trials and younger children have an RT on same trials that is comparable to or faster than different trials.
The interpretation of positively sloped similarity functions as evidence for serial processing may be questioned if log-transformed RTs are used, as in the present study. In other words, a log transformation is a non-linear transformation, so the relation between similarity and RT cannot necessarily assumed to be linear, which is an important assumption for serial processing.
To address this, we conducted the analyses for Hypothesis 2a using the raw, untransformed RT only for correct responses and with outliers removed, as was the case for log-transformed RTs and the results are fundamentally the same see Supplement. Importantly, the log-transformed and untransformed RT values yield a similar pattern of similarity functions with respect to age group. Because the log-transformed RTs lead to the same conclusions we would have reached using untransformed RTs, the remaining analyses were conducted using log-transformed RTs.
Hypothesis 2b states that when serial processing is present for upright faces indicating holistic representations , houses and inverted faces will induce a bias toward parallel processing or weaker serial processing. However, that analysis compared similarity functions across age but did not directly compare categories or orientations. The analysis for Hypothesis 2b requires comparing similarity functions across categories or across orientation conditions.
These analyses were thus conducted within each age group that showed some evidence for serial processing of upright faces; namely, adults and older children but the effect in older children was marginal and the linear trend did not reach significance. Also, because different age groups were not compared with each other in this analysis, sim0 was not a covariate but instead was included as a level of the independent variable of similarity.
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