The influence of literacy on visual search

This article was downloaded by: [The University of Edinburgh] On: 10 July 2015, At: 03:36 Publisher: Routledge Informa Ltd Registered in England and Wales Registered Number: 1072954 Registered office: 5 Howick Place, London, SW1P 1WG

Visual Cognition Publication details, including instructions for authors and subscription information: http://www.tandfonline.com/loi/pvis20

The influence of literacy on visual search a

b

c

C. N. L. Olivers , F. Huettig , J. P. Singh & R. K. cd

Mishra a

Department of Cognitive Psychology, VU University Amsterdam, Amsterdam, The Netherlands b

Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands c

Centre for Behavioural and Cognitive Sciences, University of Allahabad, Allahabad, India d

Click for updates

Centre for Neural and Cognitive Sciences, University of Hyderabad, Hyderabad, India Published online: 26 Feb 2014.

To cite this article: C. N. L. Olivers, F. Huettig, J. P. Singh & R. K. Mishra (2014) The influence of literacy on visual search, Visual Cognition, 22:1, 74-101, DOI: 10.1080/13506285.2013.875498 To link to this article: http://dx.doi.org/10.1080/13506285.2013.875498

PLEASE SCROLL DOWN FOR ARTICLE Taylor & Francis makes every effort to ensure the accuracy of all the information (the “Content”) contained in the publications on our platform. However, Taylor & Francis, our agents, and our licensors make no representations or warranties whatsoever as to the accuracy, completeness, or suitability for any purpose of the Content. Any opinions and views expressed in this publication are the opinions and views of the authors, and are not the views of or endorsed by Taylor & Francis. The accuracy of the Content should not be relied upon and should be independently verified with primary sources of information. Taylor and Francis shall not be liable for any losses, actions, claims, proceedings, demands, costs, expenses, damages, and other liabilities whatsoever or howsoever caused arising directly or indirectly in connection with, in relation to or arising out of the use of the Content.

Downloaded by [The University of Edinburgh] at 03:36 10 July 2015

This article may be used for research, teaching, and private study purposes. Any substantial or systematic reproduction, redistribution, reselling, loan, sublicensing, systematic supply, or distribution in any form to anyone is expressly forbidden. Terms & Conditions of access and use can be found at http:// www.tandfonline.com/page/terms-and-conditions

Visual Cognition, 2014 Vol. 22, No. 1, 74–101, http://dx.doi.org/10.1080/13506285.2013.875498

The influence of literacy on visual search


C. N. L. Olivers1, F. Huettig2, J. P. Singh3, and R. K. Mishra3,4 1

Department of Cognitive Psychology, VU University Amsterdam, Amsterdam, The Netherlands 2 Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands 3 Centre for Behavioural and Cognitive Sciences, University of Allahabad, Allahabad, India 4 Centre for Neural and Cognitive Sciences, University of Hyderabad, Hyderabad, India (Received 16 March 2013; accepted 10 December 2013)

Currently one in five adults is still unable to read despite a rapidly developing world. Here we show that (il)literacy has important consequences for the cognitive ability of selecting relevant information from a visual display of nonlinguistic material. In two experiments we compared low to high literacy observers on both an easy and a more difficult visual search task involving different types of chicken. Low literates were consistently slower (as indicated by overall response times) in both experiments. More detailed analyses, including eye movement measures, suggest that the slowing is partly due to display wide (i.e., parallel) sensory processing but mainly due to postselection processes, as low literates needed more time between fixating the target and generating a manual response. Furthermore, high and low literacy groups differed in the way search performance was distributed across the visual field. High literates performed relatively better when the target was presented in central regions, especially on the right. At the same time, high literacy was also associated with a more general bias towards the top and the left, especially in the more difficult search. We conclude that learning to read results in an extension of the functional visual field from the fovea to parafoveal areas, combined with some asymmetry in scan pattern influenced by the reading direction, both of which also influence other (e.g., nonlinguistic) tasks such as visual search.

Keywords: Literacy; Visual search; Attention.

Please address all correspondence to R. K. Mishra, Center for Neural and Cognitive Sciences. University of Hyderabad, C R Rao Road, Hyderabad, AP, India 500046. Email: [email protected] This work was supported by an NWO Open Competition grant 404-10-321 awarded to CNLO and FH and a Cognitive Science Initiative grant from the Department of Science and Technology, India, awarded to RKM. © 2014 Taylor & Francis


LITERACY VISUAL SEARCH

75

The rapid economic rise of many developing countries puts increasing demands on the cognitive skills of their citizens (Hanushek & Woessmann, 2008; Ranis, Stewart, & Ramirez, 2000). At the same time, levels of literacy are lagging behind, as investments of the economic returns in schooling only come at a delay or are impeded by entrenched social divisions (UNESCO, 2008). Researchers have been interested in whether literacy is associated with differences in cognitive processes other than reading per se. This is not relevant only from the perspective of human development, but also from the perspective of fundamental cognitive neurosciences, which seek to map out the relationships between the different mechanisms of perception, memory, and language—including their plasticity and long-term changes. The current study shows that literacy also affects the way we sample the visual world in general when we are looking for target objects among competing information—a process referred to as selective visual attention. The vast majority of studies on the cognitive consequences of (il)literacy has focused on linguistic skills. These have revealed that, although low level speech perception is little influenced by formal literacy, illiterate adults have difficulty with tasks that require phonological awareness (i.e., awareness that all words can be decomposed into smaller segments), phonological short-term memory, phonological fluency, and online phonological word-object mapping (Adrian, Alegria, & Morais, 1995; Bertelson, de Gelder, Tfouni, & Morais, 1989; Huettig, Singh, & Mishra, 2011; Kosmidis, Tsapkini, Folia, Vlahou, & Kiosseoglou, 2004; Lukatela, Carello, Shankweiler, & Liberman, 1995; Mishra, Singh, Pandey, & Huettig, 2012; Morais, Bertelson, Cary, & Alegria, 1986; Morais, Cary, Alegria, & Bertelson, 1979; Morais, Castro, Scliar-Cabral, Kolinsky, & Content, 1987; Petersson, Reis, Askelof, Castro-Caldas, & Ingvar, 2000; Read, Zhang, Nie, & Ding, 1986; Reis & Castro-Caldas, 1997; Serniclaes, Ventura, Morais, & Kolinsky, 2005). Luria (1976) has argued that schooling in general has consequences for categorical and taxonomic understanding, especially when abstract geometric stimuli are concerned. However, illiterates are able to categorize objects with little trouble when common objects and categories are used (Scribner, 1974). Literacy affects memory: Illiterates have been reported to perform well on immediate sentence recall and spatial retention, but to be impaired on memory for digits (Ardila, Rosselli, & Rosas, 1989; Reis, Guerreiro, & Petersson, 2003; Silva, Faisca, Ingvar, Petersson, & Reis, 2012). Apart from linguistic and semantic processes, reading involves visual skills. To date there is no evidence that literacy affects low level visual processing (Kolinsky, Morais, & Verhaeghe, 1994; Le Carret et al., 2003)—unlike some forms of dyslexia, which have been linked to visual impairments (Stein & Walsh, 1997). Illiterates perform well in picture naming tasks, as long as the pictures consist of full colour photographs and not of more schematic black and white drawings (Reis, Castro-Caldas, Ingvar, & Petersson, 2000; Reis, Faisca, Ingvar, & Petersson, 2006). It is likely that general schooling plays a role, rather than


76

OLIVERS ET AL.

purely the ability to read. Note in this regard that schooling and literacy are very difficult to dissociate. Most authors reject the notion that it is possible to draw a strict distinction between schooling and literacy (Goody, 1987; Olson, 1994; but see Scribner & Cole, 1981, for a different view). After all, schooling is a literate institution and thus to investigate the effect of literacy one has to study it in its institutional context (see Goody, 1987, for further discussion). Important for the present investigation, a number of studies suggest that literacy affects the consistency of scanning a display of multiple objects. Literates predominantly scan according to the reading direction (or may adopt other consistent trajectories), whereas illiterates appear to scan more randomly (Bramao et al., 2007; Brucki & Nitrini, 2008; Byrd, Jacobs, Hilton, Stern, & Manly, 2005; Le Carret et al., 2003; Ostrosky-Solis, Efron, & Yund, 1991; Padakannaya, Devi, Zaveria, Chengappa, & Vaid, 2002). The directionality of reading also appears to transfer to the perception of actions and events. Left-toright readers prefer to perceive (in a sentence matching task) or place (in a drawing task) the agents on the left and the consequences on the right, whereas for right-to-left readers this is the other way around (Chatterjee, 2001; Dobel, Diesendruck, & Boelte, 2007; Maass & Russo, 2003). Such left-to-right directionality should be dissociated from the general left hemifield (or right hemisphere) advantage in fine discrimination that appears to exist for nonlinguistic stimuli (Jewell & McCourt, 2000; Kimura, 1966; Landau & Fries, 2012; Nicholls & Roberts, 2002). Another important spatial bias that is caused by reading is the development of a considerable amount of parafoveal information processing, such that when the current word is fixated, some properties of the next word are analysed (see Rayner, 1998, for a review). This parafoveal perceptual span grows with reading experience in childhood (Forgays, 1953; Rayner, 1986). Furthermore, the span seems to have its own directionality, as it extends more to the right than to the left for left-to-right readers, and vice versa for right-to-left readers (de Buurman, Roersema, & Gerrissen, 1981; McConkie & Rayner, 1975, 1976; Pollatsek, Bolozky, Well, & Rayner, 1980; Rayner, Well, & Pollatsek, 1980). A similar extension of the parafoveal field of view has been found in visual detection and visual search tasks with letter targets (Bertera & Rayner, 2000; Bouma, 1973). However, there have been no studies examining the influence of eccentricity on perceptual processing in high versus low literacy populations. Although these studies suggest some literacy-related changes in selectively attending to relevant stimuli, they leave some important questions unresolved. For one, we do not know whether performance in these studies reflects a general differentiation in attentional skills, or is specific to the abstract geometric (and occasionally even letter-like) shapes used in studies so far. Due to their shorter school careers, low literates are likely to have had less experience with such stimuli. Second, so far studies have used regularly structured spatial lay-outs. Again, this may have put populations that have experience with structured visual



77

arrays at an advantage. We emphasize that this does not negate the important conclusion that reading skills are associated with efficient scanning strategies. But it does not answer the question whether there may be more general changes in the way visual attention is deployed. Third, it remains unclear to what extent the performance costs relative to literates reflect attention or processes that occur at other stages of processing, especially after target selection has taken place. Poorer task representations might also affect decision and response selection processes after a target has been selected. To separate visual selection from other processes one needs to systematically vary the level of competition within the visual display, for example through manipulations of set size (e.g., Treisman & Gelade, 1980) or target-distractor similarity (e.g., Duncan & Humphreys, 1989). No studies have done this in the context of literacy. To investigate whether literacy influences visual attention in general, we compared high and low literates on a set of visual search tasks. All participants spoke Hindi and were recruited from the Allahabad University community in the northern Indian state of Uttar Pradesh. Note that Hindi is written in left-to-right Devanagari script (which like all Indian scripts has its origin in the left-to-right Brahmic script). High literates were postgraduate university students. Low literates were people of similar age working in support services on or near university campus (mainly in catering and cleaning), and were well integrated in society. Low literacy levels in the Uttar Pradesh region of India are mainly due to poverty and other socioeconomic factors rather than deficiencies in individual social or cognitive abilities. In the Method sections we describe a number of other characteristics of these populations. Experiment 1 provided a first test of the effects of literacy on visual search. Specifically, we were interested if illiterates would differ from literates in overall response times, search efficiency, and specific spatial biases. Experiment 2 then extended the findings with eye movement measures. Figure 1 shows two examples of the visual search displays we used. So as to not put low literates at an immediate disadvantage, the search arrays consisted of colour pictures of chickens rather than abstract geometrical shapes. It goes without saying that all participants readily recognized the chickens as such. We systematically varied the set size of the search array, as this provides us with a measure of search efficiency: The more efficient the search, the smaller the slope of the Set size × Response time (RT) function. We also varied the difficulty of the search by making the target more or less salient relative to the nontargets. In the easy search task, observers were required to find a red chicken among green chicken. Here there is expected to be little competition between target and distractors, and the target should be detected largely in parallel. In the difficult search task, observers were required to find the skinny chicken among fat chickens. Here search was expected to be less efficient, involving a serial component. These manipulations allowed us to dissociate search processes, before and leading up to target selection, from postselection processes occurring after the target has been found, such as response selection. Whereas the search


78

OLIVERS ET AL.

Figure 1. Example visual search displays. The left panel shows an easy search task in which the target is a red among green chicken (here set size 8), the right panel a difficult search task in which the target is a skinny chicken among fat chickens (here set size 16). To view this figure in colour, please see the online issue of the Journal.

process itself should be sensitive to the set size, particularly in the case of more serial search, any target or response-related processes occurring after the target has been selected should be independent of set size and search difficulty. Finally, the chickens were pseudorandomly scattered across the screen from trial to trial, to avoid an obvious scanning strategy. Those studies suggesting a role for scanning strategies invariably used regularly spaced displays that were often densely filled with abstract geometrical shapes. Moreover, the spatial layout of these items remained identical from trial to trial. As has been shown in the eye movement literature (cf. Gilchrist & Harvey, 2006), this is likely to invite observers to adopt a consistent scanning strategy, especially if they have had experience with similar structures during schooling (such as tables, matrices, or other types of grids). In contrast, in our experiment we used displays of randomly scattered items, with little to no consistent spatial structure and repetition from trial to trial. Such random displays are more likely to induce random scan paths. Nevertheless, we included analyses of performance as a function of target position to see if there were any biases in search direction. Importantly, we also examined search performance as a function of eccentricity, to assess the extent to which central vision plays a role.

EXPERIMENT 1 Method Participants. Twenty participants of high literacy and 20 participants of low literacy took part in the experiment. Participants were from Allahabad and data was collected at the Center for Behavioural and Cognitive Sciences, Allahabad. The top half of Table 1 shows a number of relevant characteristics for these groups. None of the participants showed any signs of neurological disease or any apparent cognitive deficits.


79

TABLE 1 Group characteristics for Experiments 1 and 2 High literacy group


Experiment 1 Mean age (yrs) Sex Years of schooling Raven’s progressive matrices Word reading scores (for mono-, di-, trisyllabic words) Phonological awareness (phoneme deletion, phoneme substitution, syllable deletion, syllable substitution) Experiment 2 Mean age (yrs) Sex Years of schooling Raven’s progressive matrices Word reading scores (for mono-, di-, trisyllabic words) Phonological awareness (phoneme deletion, phoneme substitution, syllable deletion, syllable substitution)

Low literacy group

23.2 (21–30) F =7; M = 13; 16.1 (14–17) 45.7/60 (42–49) 30/30, 29.9/30, 29.9/30 21.6/25, 23.4/25, 23.7/25, 23.7/25

21.7 (17–32) F = 0; M = 20; 4.1 (1–5)*** 42.5/60 (30–49)* 24.3/30, 23.7/30, 20.3/30*** 11.8/25, 13.5/25, 16.0/25, 14.7/25***

20.9 (19–25) F = 8; M =9 15.5 (14–18) 49.2/60 (43–54) 30/30, 29/30, 29.1/30 22.2/25, 22.8/25, 23.4/25, 23.2/25

24.7 (16–33)** F = 0; M = 20 1.8 (0–5)*** 34.6/60 (28–43)*** 12.5/30, 11.0/30, 9.4/30*** 11.7/25, 10.1/25, 11.6/25, 11.2/25***

*p < .05, **p < .01, ***p < .001.

Stimuli, design, and procedure. Participants sat at a desktop computer running E-Prime 2.0 (Psychology Software Tools, Inc.) in a dark room. Stimuli were presented on a 17-inch monitor with 1024 × 768 screen resolution, at approximately 70 cm distance. They were first familiarized with the task and the stimuli through verbal instruction, followed by a practice session of 25 trials per task. In all tasks, observers were asked to find a target chicken as quickly as possible while ignoring all other chickens, and then indicate which way the target chicken was facing (left or right), by pressing the corresponding arrow key on the standard keyboard. Note that this involves a quite natural stimulus– response mapping that does not require knowledge of the concepts of left and right, just the knowledge that the chicken may be facing one side or the other. Instructions were given verbally in both groups and stressed both speed and accuracy. Search items were based on a colour photograph of a real chicken but were manipulated by image software to create two main conditions: In the easy search task, the target chicken was reddish, while the distractor chickens were greenish (by upping the respective R and G channels in the image), resulting in a clear colour difference. In the difficult search condition, the chicken retained its original (brown) colour, but now the task was to find a skinny chicken among fat chickens. The background was always white. The chicken were approximately 2.8° × 2.2° visual angle in size and were randomly placed within a virtual grid of 6 cells wide × 5 cells tall (totalling about 18° × 13° visual angle), centred on the

80

OLIVERS ET AL.


middle of the screen. Within each cell of the grid there was some additional spatial jitter (maximum 0.5°) in order to prevent grouping by alignment. The number of chickens was varied between 4, 8, and 16, randomly mixed across trials. The displays were presented until response, were preceded by a 750 ms fixation cross and followed by a 750 ms blank display. The main tasks (easy, difficult) were run in two main blocks in counterbalanced order, each consisting of six subblocks of 48 trials. This resulted in 96 trials for each Task × Set size combination. Half of these involved a left-facing target chicken, the other half a right-facing target chicken. These trial numbers also enabled us to split up the analyses according to target position.

Results and discussion One high literacy participant performed at chance level (50%) and was excluded from the analyses. Regardless of literacy, all other participants scored at least 92% correct overall, showing that they understood the tasks well. As would be expected, the high and low literacy groups differed considerably on word reading and phonological awareness tests (see Table 1). The groups also differed in their score on the Raven’s progressive matrices test of nonverbal intelligence. In this test participants have to fill in the missing cell of a matrix of at least three by three. We note that many of the items in the test involve some form of counting, and all of them involve the analysis of, and reasoning based on, abstract geometrical shapes. Furthermore, the logic of these matrices is typically constructed in a left to right and top to bottom fashion, with the missing cell always being the bottom-right one. All these aspects are likely to benefit from schooling (Byrd et al., 2005; Le Carret et al., 2003), and indeed, in general, intelligence tests benefit from education (Neisser, 1998). Given the fact that all observers understood the task well, we reject the possibility that the results in the present study are simply caused by differences in general intelligence (other than related to literacy). This will be further supported by the results, which revealed a spatially specific effect on visual search, whereas performance in other regions was comparable for both groups. Overall effects. Trials on which responses were incorrect (2.3% for the high literates, 1.8% for the low literates, ns), or deviated more than three standard deviations from the mean of the respective cell for each subject (1.8% for the high literates, 2.1% for the low literates, ns) were excluded from the RT analyses. All analyses were performed with a criterion of α = .05. Figure 2 shows the mean RTs for the high and low literacy groups, as a function of search difficulty and set size. The same data was entered in an initial mixed factors ANOVA with literacy (high, low) as a between-subjects factor, and search difficulty (easy, difficult) plus set size (4, 8, 16) as within-subjects factors. For both levels of literacy, search RTs increased with search difficulty, F(1, 37) = 57.26, p < .001,


81

1300


Correct Search RT (ms)

1200

Low literacy Easy search

1100

Low literacy Difficult search

(21)

High literacy Easy search

1000 900

(5)

800

(17)

700

High literacy Difficult search

(3)

600 500 400

0

4

8 12 Set Size

16

20

Figure 2. Results of Experiment 1. Search RTs as a function of set size for easy search (red among green chicken) and difficult search (skinny among fat chickens), and for the two levels of literacy. Search slope values are shown in parentheses (in ms/item).

and increased with search set size, F(2, 74) = 216.87, p < .001, but mainly so in the difficult search condition, as indicated by the interaction of difficulty and set size, F(2, 74) = 120.61, p < .001. The slope values suggest parallel search in the colour condition, and a serial component in the shape condition. This replicates findings from many earlier studies. The low literacy group was overall slower, by about 260 ms on average, F(1, 37) = 16.54, p < .001. Furthermore, search in the low literacy group was less efficient than in the high literacy group, as evidenced by a Literacy × Set size interaction, F(2, 74) = 4.48, p < .02. Overall accuracy was high, at 97.7% for the high literacy group versus 98.2% for the low literacy group (F < 1.2, ns). The only accuracy difference involving literacy was a Literacy × Search difficulty interaction, F(1, 37) = 6.89, p < .02, as the high literates were somewhat less accurate than the low literates (97.2% vs. 98.4% on average) in the difficult task, but not in the easy task (98.1% vs. 98.2% on average). The low literacy group scored 97.%, 98.3%, and 98.1% for set sizes 4, 8, and 16 in the easy search task, and a respective 98.2%, 98.2%, and 98.8% in the difficult search task. The high literates scored 98.2%, 98.4%, and 98.1% in the easy search, and 97.6%, 96.3%, and 97.6% in the difficult search. As accuracy was high overall, errors were not analysed further. Spatial biases. Subsequent analyses investigated whether there were any literacy-related differences in spatial processing. For example, a reading-based scanning strategy might induce a bias towards the top left quadrant of the display, while reading skills may also improve parafoveal vision. Table A1 (see the Appendix) presents the data set split up according to whether the target


82

OLIVERS ET AL.

appeared on the right or on the left (side), and whether it appeared in the top two rows of the display, the middle row, or the bottom two rows (altitude). An ANOVA revealed a main effect of altitude, F(2, 74) = 24.76, p < .001, which did not interact with literacy (p > 0.45). RTs were overall fastest for targets presented in the middle row (780 ms), which makes sense given the more central position. This was followed by the bottom section (819 ms), which did not differ significantly from the top section (823 ms). There was a Side × Set size × Literacy interaction that approached significance, F(2, 74) = 2.99, p = .056. Table A1 suggests that low literates were less efficient on the right, whereas high literates were, if anything, more efficient on the right. There was also a complex Altitude × Side × Search difficulty × Literacy interaction, F(2, 74) = 6.79, p < .01. To aid in its interpretation, Figures 3A and 3B show the RT benefits for the high literacy group relative to the low literacy group (i.e., the RT[low literacy] – RT[high literacy]), for each of the left/right and top/middle/bottom sections, and colour-coded. It shows the largest literacy-related benefit for targets right of the centre in the easy, pop-out search task. In contrast, in the more serial search the largest benefits were towards the left, followed by top left and bottom right. The first would be consistent with a right visual field benefit, while the latter could be consistent with a scanning strategy that starts at the top left. However, we are cautious to not over interpret these findings here, as the middle row was based on rather few datapoints per cell. Moreover, RTs reflect many different processes that develop during a trial, and it remains unclear when certain biases occur. In Experiment 2, therefore, we included more trials and also measured participants’ eye movements while they performed the search task. To assess the role of central vision, we divided the 6 wide × 5 tall search array into an inner 4 × 3 area (near eccentricity, within approximately 4° to 6° visual angle, both for the left and the right; 20 trials per cell) versus the remaining 6 × 5 ring (far eccentricity, beyond 6° visual angle, both for the left and the right; 28 trials per cell). Table A2 shows the mean RTs and slopes. An ANOVA with side (left, right) and eccentricity (near, far) as additional factors again revealed that across groups, RTs slowed with increasing eccentricity, F(1, 37) = 240.98, p < .001, especially in the difficult search task, Eccentricity × Difficulty, F(1, 37) = 9.18, p < .005. Important for the present purpose were the interactions of literacy and eccentricity, F(1, 37) = 4.53, p < .05, literacy, eccentricity, and set size, F(2, 74) = 4.11, p = .02, and literacy, eccentricity, search difficulty, and set size, F(2, 74) = 3.64, p < .05. Table A2 shows how the high literacy group benefited relatively more from centrally presented targets than the low literacy group in terms of overall RTs as well as efficiency—despite the fact that the latter group left more room for improvement. This was strongest for the difficult search task, for which a separate analysis indeed revealed a robust Literacy × Eccentricity × Set size interaction, F(2, 74) = 5.11, p < .01. Figures 3C to 3F show a spatial map of the differences between high and low literacy RTs, as well as the ratios of the search slopes, for easy and difficult search.

83



Figure 3. Results of Experiment 1. Difference in search RTs (in ms, Panels A–D) between high and low literates for easy search (left panels) and difficult search (right panels). Panels A and B show the RT differences as a function of display section (top left, top right, middle left, middle right, bottom left, bottom right). Notice the rightward bias in the easy search, and the leftward bias in the difficult search. Panels C and D show the same, but now as a function of eccentricity (left centre, left eccentric, right centre, right eccentric). Panels E and F show the ratios of the low over the high literacy search slopes for the same central and eccentric display areas. To view this figure in colour, please see the online issue of the Journal.

84

OLIVERS ET AL.

EXPERIMENT 2 Method The method was the same as in Experiment 1, except for the following.


Participants. Twenty new low literates and 17 new high literates were recruited from the Allahabad community, data was collected at the center for Behavioral and Cognitive Sciences, University of Allahabad. Table 1 shows the characteristics also of these high and low literacy groups. Stimuli, design, and procedure. Stimulus presentation and response recording was now done using Presentation (ver. 16.1) software (Neurobehavioral Systems), and the target display was now followed by a 1000 ms instead of 750 ms blank display. There were now two set sizes, instead of three: 6 and 16. As before, the two main tasks (easy, difficult) were again run in two main blocks in counterbalanced order, but now consisted of six subblocks of 60 trials each. The first 20 trials of each main task were considered as practice. This resulted in 170 trials for each Task × Set size combination. Eye movement recording and preprocessing. Eye movements were measured using a 1250 Hz SMI high speed eye tracker (SMI Teltow, Berlin; claimed spatial resolution 0.01°), in combination with a chinrest. Eye movement samples were parsed into saccades and fixations using the standard Be Gaze 3.0 (SMI) thresholds of 40°/s for peak saccade velocity, 8000°/s2 for saccade acceleration, minimum 0.1° initial displacement, minimum saccade duration 22 ms, and minimum fixation duration 50 ms. When necessary, a post hoc drift correction was applied to each block on the basis of any systematic deviations in the initial central fixation. Only trials on which the initial fixation fell within 3°) from the centre of the display were included in the eye movement analyses. This amounted to 78% of the trials in the low literate group, and 91% of the trials in the high literate group. Of these trials we considered the eye movements up to the manual response. We categorized these into initial saccade (the first saccade away from initial fixation), target fixation and target saccade (the first fixation that fell within 1.5° of the centre of the target and that was not the initial fixation, and the saccade leading up to it), or elsewhere (which could be fixations on distractors or empty parts of the display—we did not store each distractor location). This also allowed us to distinguish fixations prior to the first target fixation from those following the first target fixation.

Results and discussion No participants were excluded from analyses. Regardless of literacy, each of the participants scored at least 79% correct, showing that they understood the task.


85

Unsurprisingly, as shown in Table 1, the high and low literacy groups differed on word reading and phonological awareness tests, as well as on the Raven’s progressive matrices test of nonverbal intelligence.

Manual responses. The manual response data were analysed as in Experiment 1. Trials on which responses were incorrect (3.1% for the high literates, 4.3% for the low literates, ns) were excluded from the RT analyses. RTs that deviated more than three standard deviations from the mean of the respective cell for each subject (1.2% for the high literates, 1.5% for the low literates, ns) were also excluded. Figure 4 shows the mean RTs for the high and low literacy groups, as a function of search difficulty and set size. A mixed factors ANOVA with literacy (high, low) as a between-subjects factor, and search difficulty (easy, difficult) plus set size (6, 16) as within-subjects factors confirms what can be seen from the figure: Search RTs increased with search difficulty, F(1, 35) = 73.97, p < .001, and increased with search set size, F(1, 35) = 251.64, p < .001, but mainly so in the difficult search condition, as indicated by the interaction of difficulty and set size, F(2, 74) = 156.49, p < .001. Figure 4 also clearly shows that the low literacy group was overall slower, by 176 ms on average, F(1, 35) = 22.27, p < .001. This replicates Experiment 1. However, in contrast to Experiment 1, the current group of low literates was no less efficient than the high literates, as search slopes did not increase. 1200 1100 Correct Search RT (ms)


Overall effects.

(16) 1000 Low literacy Easy search

900 800

(4)

Low literacy Difficult search

(18)

High literacy Easy search High literacy Difficult search

700 (3)

600 500 400 0

4

8 12 Set Size

16

20

Figure 4. Results of Experiment 2. Search RTs as a function of set size for easy search (red among green chicken) and difficult search (skinny among fat chickens), and for the two levels of literacy. Search slope values are shown in parentheses (in ms/item).

86

OLIVERS ET AL.


In terms of accuracy, the low literacy group scored 94.9%, and 94.7% for set sizes 6 and 16 in the easy search task, and a respective 95.9% and 95.8% in the difficult search task. The high literates scored 97.8% and 97.7% in the easy search, and 95.5% and 95.5% in the difficult search. There were no significant differences. As accuracy was overall high, errors were not analysed further. Eye movements. What causes this overall slowing in manual response? The fact that this occurred across search difficulty and across set size a priori suggests that it does not stem from the search process itself, as that would have affected the slope of the RT × Set size function. Instead, it appears to stem from a process prior to search, a process after completing the search, or both. To investigate the start of search, we compared the average latency of the first saccade that left central fixation. This measured 324 ms for the high literates, and 301 ms for the low literates, which did not differ significantly. We then assessed target fixation latency as an indicator of when the target was found. The pattern remains the same when taking saccadic latency rather than fixation latency as a measure (on average, the saccade towards the target preceded fixation by approximately 50 ms across the board). As would be expected, target fixation latency was shorter for easy search than for difficult search, F(1, 35) = 120.08, p < .001, and increased with set size, especially for difficult search; Difficulty × Set size, F(1, 35) = 66.13, p < .001. None of this interacted reliably with literacy, nor was there a main effect of literacy. However, a closer examination did reveal that for the easy colour search, high literates (471 ms) were significantly faster than low literates (512 ms) in fixating the target, F(1, 35) = 8.3, p < .01.1 No such difference was found for shape search (631 ms vs. 637 ms respectively, ns). The fact that high literates found the target more rapidly in the easy search was also reflected in the number of fixations up to the target fixation. On average, high literates required 1.5 eye movements to find the colour target, whereas the low literates required 1.9 eye movements, a difference that was highly significant, F(1, 35) = 19.55, p < .001. For the more difficult shape search, there was no significant difference, as high literates required 2.3 eye movements on average, whereas low literates required 2.4. This difference between tasks resulted in a Search difficulty × Literacy interaction, F(1, 35) = 4.60, p < .05. It suggests that although finding a colour pop-out target still occurs in parallel for low literates (as indicated by their search slopes), this parallel process is overall somewhat slowed, resulting in an occasional spurious eye movement elsewhere. However, the slowing in detecting a colour target cannot explain the entire manual RT effect, nor does it explain the overall slowing in the shape search: 1

We report F-tests rather than t-tests because set size was typically also included as a factor in these analyses. We only report on set size effects when they deviate from what has already been reported in the main analysis.



87

There target fixation latencies were equal for the two literacy groups, whereas manual RTs differed. By logic then, the remainder of the time difference must occur after the initial target fixation. Indeed, the low literates showed more posttarget eye movements before they initiated a manual response (0.76 on average) than the high literates (0.33 on average), a difference that was highly reliable F(1, 35) = 19.76, p < .001. One possibility is that low literates dwell longer on the target. A further analysis revealed that for the low literates, on average 0.30 (of the 0.76, which is 39%) additional fixations were spent on the target, whereas high literates only spent an additional 0.13 (of the 0.33, which is also 39%) fixations before they pressed the button, F(1, 35) = 9.07, p < .01. As a result, total target dwell time was 450 ms for the low literates, and 385 ms for the high literates, F(1, 35) = 5.28, p < .05. So indeed, in absolute terms, the low literates spend more time on the target. In relative terms, both groups spent an equal proportion of post target fixations on the target (39%). In sum, it appears that the overall RT difference between high and low literates stems partly from processes that lead to target detection in parallel across the visual field but to the largest extent from processing stages after finding the target. Spatial biases. Altitude and side effects. Table A3 presents the data set split up according to whether the target appeared on the right or on the left (side), and to whether it appeared in the top two rows of the display, the middle row, or the bottom two rows (altitude). This yielded approximately 67 trials for each combination of side, altitude and set size, except for the middle row, for which it was approximately 34 trials. The analysis revealed a main effect of altitude, F(2, 70) = 74.00, p < .001, which did not interact with literacy (p > .9). RTs were overall fastest for targets presented in the middle row (798 ms), which makes sense given the more central position. This was followed by the bottom section (841 ms), and the top section (862 ms). The 21 ms difference between top and bottom was reliable: When the middle section was left out of the ANOVA, a main effect of altitude remained, F(1, 35) = 12.34, p = .001. Faster detection for the lower visual field has been found before (He, Cavanagh, & Intriligator, 1997; Rezec & Dobkins, 2004), and is thought to reflect the visual system’s adaptation to the fact that the bottom half of the visual world is richer in relevant information (e.g., when walking, or looking for an object on a table). The only interaction involving literacy was between search difficulty, side, and literacy, F(1, 35) = 6.26, p < .05 when the middle altitude was included, and F(1, 35) = 4.24, p < .05 when the middle row was excluded). To facilitate the interpretation of this interaction, Figures 5A and 5B show the RT differences between low and high literates for each of the areas. The pattern looks quite similar to that found in Experiment 1 (compare Figure 3). In the easy search task, the benefits for the high literates

88

OLIVERS ET AL.

EASY SEARCH

DIFFICULT SEARCH


A. Side & altitude effects: ΔRT

B. Side & altitude effects: ΔRT

173

173

173

173

173

173

196

196

196

154

154

154

173

173

173

173

173

173

196

196

196

154

154

154

153

153

153

172

172

172

205

205

205

181

181

181

170

170

170

183

183

183

187

187

187

162

162

162

170

170

170

183

183

183

187

187

187

162

162

162

C. Eccentricity effects: ΔRT

D. Eccentricity effects: ΔRT

172

172

172

172

172

172

192

192

192

134

134

134

172

164

164

183

183

172

192

198

198

206

206

134

172

164

164

183

183

172

192

198

198

206

206

134

172

164

164

183

183

172

192

198

198

206

206

134

172

172

172

172

172

172

192

192

192

134

134

134

E. Eccentricity: Slope ratios

F. Eccentricity: Slope ratios

1.1

1.1

1.1

1.7

1.7

1.7

0.9

0.9

0.9

0.8

0.8

0.8

1.1

1.1

1.1

1.1

1.1

1.7

0.9

0.9

0.9

1.0

1.0

0.8

1.1

1.1

1.1

1.1

1.1

1.7

0.9

0.9

0.9

1.0

1.0

0.8

1.1

1.1

1.1

1.1

1.1

1.7

0.9

0.9

0.9

1.0

1.0

0.8

1.1

1.1

1.1

1.7

1.7

1.7

0.9

0.9

0.9

0.8

0.8

0.8

Figure 5. Results of Experiment 2. Difference in search RTs (in ms, Panels A through D) between high and low literates for easy search (left panels) and difficult search (right panels). Panels A and B show the RT differences as a function of display section (top left, top right, middle left, middle right, bottom left, bottom right). Notice the rightward bias in the easy search, and the leftward bias in the difficult search. Panels C and D show the same, but now as a function of eccentricity (left centre, left eccentric, right centre, right eccentric). Panels E and F show the ratios of the Low over the high literacy search slopes for the same central and eccentric display areas. To view this figure in colour, please see the online issue of the Journal.



89

were quite evenly spread across the display, but if anything were largest on the right. For the difficult search, the largest literacy-related benefits are again to be found on the left, and then predominantly the top left section. The pattern was largely mirrored in eye movements. Target fixation latency was overall fastest for the middles row (519 ms), followed by the bottom half of the display (566 ms), and then the top half (586 ms), F(2, 70) = 54.43, p < .001. An ANOVA without the middle row revealed that the 20 ms difference between top and bottom half was reliable, F(1, 35) = 15.57, p < .001. The same analysis revealed an Altitude × Literacy interaction, F(1, 35) = 13.60, p = .001. The relative benefits for the bottom half of the visual display were larger for the low literates than for the high literates. This was also reflected in the number of eye movements leading up to the target: The low literacy group required on average across tasks 2.3 eye movements to find the target in the top rows, and 2.1 eye movements for the bottom rows. For high literates this was 2.0 for both halves, also here resulting in an Altitude × Literacy interaction, F(1, 35) = 9.20, p < .01. The pattern is interesting, as it suggests that high literates may compensate for altitude differences by making more initial eye movements towards the top of the display (and therefore fewer eye movements are needed to find a target there), consistent with a reading-based scanning strategy. Also consistent with this, the interaction between search difficulty, side, and literacy was reliable: F(1, 35) = 9.01, p < .01 when the middle altitude was included, and F(1,35) = 7.10, p < .05 when the middle row was excluded. Whereas low literates were faster in fixating targets on the right than on the left in difficult search, for the high literates this was the other way around: They showed a bias towards the left. To further investigate scan strategy in the difficult shape search, we calculated, for each of the literacy groups, the fixation density, which is shown in Figure 6. That is, we computed proportion of fixations falling on each item position in the search array, as a function of fixation order. Fixation 0 represents initial central fixation, which is followed by the first fixation away from central fixation, and so forth. Later fixations are collapsed to increase numbers per cell. Figure 6a shows how for the high literacy group, fixations first cluster around the centre, and then move towards the top left quadrant. After this the pattern appears to diverge, with a large part of the eye movements being directed towards the top right, while others go via the bottom half. Finally, most fixations end up on the far right. For the low literacy group, shown in Figure 6b, the pattern looks somewhat different. They show a more symmetrical and more widespread pattern, first around fixation, and then towards the top of the display, if anything more often ending on the left rather than on the right. Figure 6c shows the difference between the high and low literacy groups. This difference is most expressed at the top left quadrant in the beginning of search, and the bottom right quadrant towards the end of search. This top-left / bottom-right pattern is highly suggestive of a scan pattern that is influenced by reading.

90

A. HIGH LITERACY Fixation 1

Fixation 2

Fixation 3&4

Fixation 5, 6 & 7

Fixation 8 and up

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.01

0.02

0.03

0.02

0.01

0.02

0.03

0.04

0.05

0.03

0.02

0.03

0.04

0.04

0.05

0.04

0.04

0.03

0.05

0.03

0.05

0.06

0.04

0.06

0.00

0.03

0.14

0.05

0.03

0.00

0.00

0.05

0.03

0.00

0.00

0.01

0.03

0.09

0.07

0.02

0.01

0.02

0.04

0.06

0.04

0.03

0.02

0.03

0.04

0.03

0.03

0.03

0.02

0.02

0.03

0.03

0.02

0.02

0.04

0.01

0.01

0.02

0.02

0.03

0.04

0.00

0.00

0.40

0.43

0.00

0.00

0.01

0.05

0.22

0.12

0.03

0.01

0.03

0.05

0.07

0.04

0.03

0.02

0.03

0.04

0.03

0.03

0.03

0.03

0.03

0.03

0.02

0.02

0.02

0.02

0.01

0.01

0.02

0.03

0.04

0.04

0.00

0.00

0.03

0.05

0.00

0.00

0.01

0.03

0.06

0.04

0.02

0.01

0.02

0.04

0.05

0.04

0.02

0.02

0.03

0.03

0.04

0.03

0.03

0.03

0.03

0.03

0.02

0.03

0.04

0.03

0.00

0.01

0.01

0.00

0.04

0.05

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.01

0.02

0.01

0.01

0.00

0.01

0.02

0.02

0.02

0.01

0.01

0.02

0.03

0.03

0.02

0.02

0.02

0.03

0.03

0.03

0.03

0.04

0.01

0.04

0.05

0.01

0.05

0.02

0.03

0.03

0.03

0.02

0.04

0.04

0.04

0.04

0.04

0.05

0.06

0.06

0.04

0.05

0.04

0.05

0.07

0.04

0.05

0.10

0.02

0.02

+

+

+

+

+

+

B. LOW LITERACY Fixation 0

Fixation 1

Fixation 2

Fixation 3&4

Fixation 5, 6 & 7

Fixation 8 and up

0.00

0.00

0.00

0.00

0.00

0.00

0.01

0.02

0.02

0.02

0.01

0.01

0.03

0.03

0.03

0.00

0.00

0.07

0.06

0.00

0.00

0.01

0.03

0.06

0.05

0.03

0.01

0.02

0.04

0.04

0.04

0.04

0.03

0.03

0.03

0.03

0.03

0.03

0.02

0.04

0.03

0.03

0.02

0.02

0.03

0.12

0.03

0.05

0.03

0.01

0.00

0.00

0.00

0.27

+0.40

0.00

0.00

0.01

0.05

0.14

+0.14

0.04

0.02

0.02

0.05

0.05

+0.05

0.04

0.03

0.02

0.03

0.03

+0.03

0.02

0.03

0.03

0.03

0.03

+0.03

0.03

0.02

0.04

0.02

0.03

+0.01

0.02

0.01

0.00

0.00

0.08

0.11

0.00

0.00

0.01

0.04

0.07

0.07

0.03

0.01

0.02

0.04

0.04

0.04

0.03

0.02

0.03

0.03

0.03

0.02

0.03

0.03

0.02

0.02

0.01

0.01

0.02

0.03

0.04

0.02

0.01

0.00

0.00

0.01

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.01

0.02

0.01

0.01

0.01

0.02

0.03

0.03

0.02

0.02

0.02

0.02

0.03

0.03

0.02

0.02

0.02

0.02

0.03

0.02

0.02

0.02

0.02

0.02

0.04

0.01

0.00

0.02

0.00

0.00

0.00

0.00

–0.01 0.00

0.02

0.02

0.00

0.00

0.03

0.01

0.00

0.00

0.02

0.01 –0.01 –0.01

C. DIFFERENCE Fixation 0

Fixation 1 0.00

Fixation 2

Fixation 3&4

0.00

0.00

0.00

0.00

0.00

0.00

0.01

0.01

0.00

0.00 –0.02 –0.02 0.00

0.00

0.00

0.00

0.03

0.02 –0.01 0.00

0.00

0.00

+

0.00

0.00

0.00

0.00

0.07 –0.02 –0.01 0.00

+

0.01

0.01

0.02

0.00

0.00 –0.05 –0.07 0.00

0.00

0.00 –0.01 –0.01 –0.03 –0.01 0.00

0.00

0.01

0.00

0.00

0.00

0.00

0.00

0.00 –0.01 –0.01 0.00 –0.01 0.00

0.13

0.00

0.03

0.00

0.00

0.00

0.00

0.00 –0.01 0.00

Fixation 5, 6 & 7

Fixation 8 and up

–0.01 0.00

0.01

0.01

0.00 –0.01

–0.03 –0.01 –0.01 0.00

0.02 –0.02

0.00 –0.04 –0.02 0.04

0.00

0.00

0.00

0.01

0.00

0.00

–0.02 0.00

0.00

0.00

–0.11 –0.02 –0.03 –0.01 0.02

0.00 –0.01 –0.01

0.01

0.01

0.01

0.00

0.00

0.00

0.00

0.00

0.00

0.00 –0.01 –0.01

0.00

0.01

0.02

0.00

0.00 –0.01

0.01

0.01

–0.01 0.00

0.00

0.00

0.00 –0.01

0.01

0.00

+

+

0.00

0.01

+

+

0.04

0.00 –0.01 0.00

–0.03 –0.01 –0.01 0.02

0.02

0.03

0.01

0.02

0.02

–0.04 –0.01 0.00

0.00

0.04

0.04

0.01

0.01

0.02 –0.01

0.02

0.05

0.00

0.03

0.00

0.01

0.00

Figure 6. Fixation densities as a function of fixation number. Fixation 0 is the initial central fixation. Panel C shows the difference between high (Panel A) and low (Panel B) literates. (Results of Experiment 2.) To view this figure in colour, please see the online issue of the Journal.

OLIVERS ET AL.


Fixation 0



91

The initial bias towards top and left parts in the high literacy group was further confirmed by an analysis of the first two fixations (provided that the fixation was prior to response). We calculated the proportions of these that went to each of the quadrants of the search display—regardless of where the target was. We took the first two fixations since any biases would be expected to be most pronounced early in the search. Table A4 shows these proportions. The pattern suggests an overall preference for the left and top halves of the display in the high literacy group, with what appears to be a particular preference for the top left quadrant especially in the difficult search. An ANOVA with side (left, right) and altitude (top, bottom) as within-subject factors and literacy as between-subject factor indeed revealed an effect of side, F(1, 35) = 7.66, p < .01, and a Side × Literacy interaction, F(1, 35) = 4.78, p < .05. There was also an Altitude × Literacy interaction, F(1, 35) = 8.26, p < .01. A separate analysis on high literates showed a main effect of side, F(1, 16) = 8.81, p < .01, and a main effect of altitude, F(1, 16) = 6.32, p < .05, and a hint of an interaction, F(1, 16) = 3.85, p = .067. No reliable effects were present for the low literacy group (ps > .15). Taken together, the findings indeed suggests an initial upwards and leftwards eye movement bias for the more experienced readers, when search is more serial in nature. At the very least, the result points towards a more consistent scanning strategy for this group, and one that is compatible with would be expected on the basis of reading. Eccentricity analyses. Table A5 shows the mean manual RTs and search slopes now as a function of side and eccentricity. An ANOVA with side (left, right) and eccentricity (near, far) as additional factors revealed first of all a main effect of eccentricity, F(1, 35) = 261.01, p < .001, and an Eccentricity × Set size interaction, F(1, 35) = 31.14, p < .001. As would be expected, search was slower and less efficient for more eccentric targets. In addition, there were interactions between search difficulty, side, and literacy, F(1, 35) = 4.17, p < .05, and between search difficulty, eccentricity, and literacy, F(1, 35) = 4.25, p < .05. To facilitate interpretation, Figures 5C–F show the differences in RTs and the slope ratios between low and high literates as a function of eccentricity and side. The pattern that is again quite similar to that found in Experiment 1 (compare Figure 3C–F), as the relatively greatest literacy-related RT benefits were found for the right central areas. Separate analyses showed that for the easy colour search, the effects involving literacy were not significant (all ps > .15), except for the earlier mentioned main effect on overall RTs. The shape search revealed a Eccentricity × Literacy interaction, F(1, 35) = 4.82, p < .05, which was further modulated by side, F(1, 35) = 10.59, p < .01. Table A5 and Figures 5E and 5F suggest a similar interaction for the search slopes, such that the eccentricity had a larger effect on slopes for the high literates than for the low literates, especially on the right. However, at p = .13 the Eccentricity × Set size × Literacy interaction was not significant (nor did this interact further with side). We note that although overall the interaction pattern was the same for Experiments 1 and 2, the underlying


92

OLIVERS ET AL.

effects driving these interactions differ somewhat: In Experiment 1 the high literates performed relatively better than low literates in (right) central areas, whereas in Experiment 2, the high literates performed relatively worse in (right) eccentric areas, at least in terms of search slopes. It is difficult to determine what the cause may be, other than just an overall performance difference between different groups of subjects. The important result though is the finding of differential spatial effects as a function of literacy. The eye movements again largely mirrored the pattern of RTs. Target fixation latencies are shown in Table A6. An ANOVA revealed no effects involving literacy in the easy colour search task (ps > .14). For the more difficult shape search, we found significant Side × Literacy and Eccentricity × Literacy interactions, F(1, 35) = 6.63, p < .05 and F(1, 35) = 4.87, p < .05. In the low literate group, The Side × Literacy interaction is the same as reported in the previous analysis and reflects slower target fixation latencies on the left for low literates. The important additional finding here is the greater eccentricity effect for high literates. For them, the benefit for more central targets relative to more eccentric targets was 122 ms on average. For the low literacy group, it was 80 ms on average. No other effects involving literacy were significant. Consistent with this pattern, a similar Eccentricity × Literacy effect could also be observed for the number of fixations leading up to the target, although this just failed to reach significance, F(1, 35 = 3.25, p < .08. For the high literates, central target required on average 0.63 fewer fixations than eccentric targets, whereas for low literates the difference was an average of 0.45 fixations. To further trace the source of the differential eccentricity effect, we analysed the direction of the first two fixations per trial, regardless of target position. This revealed a significant Side × Eccentricity × Literacy interaction, F(1, 35) = 6.03, p < .05. As shown in Table A7, a relatively large proportion of initial eye movements went left of the centre, but more so in the high literacy group. This largely reflects the same bias as found in the quadrant analysis, as reading-based scanning strategies may drive initial search towards the left side of the display. Note that the largest literacy-related eccentricity effects for manual RTs were found on the right side. Thus, this analysis indicates that the relative benefit for right central targets is not due to a general tendency to fixate there first—quite the opposite. What would then explain those increased eccentricity effects on the right? Taken together, the pattern of findings suggests the following scenario: Experienced readers can rely on improved central vision, especially on the right. This means that relatively few eye movements are necessary for finding right central targets. With the right central area covered, the system can safely head for the (top) left, in line with what might be expected on the basis of a reading-related scanning strategy. But heading towards the left means that the eyes will, on average, arrive last at the far right areas. This then results in the relatively longer RTs for right eccentric targets, especially when compared to right central areas. This scenario is indeed what emerges from Figure 6, where


93

central left areas are shown to be visited first and eccentric right areas last. In other words, according to this scenario, the enlarged eccentricity effects on the right are the not simply the result of better parafoveal vision, nor the result of scanning strategy alone, but of a combination of the two.


GENERAL DISCUSSION The present study shows that long-term experience with reading has consequences also for the way we sample nonlinguistic visual arrays. We used visual search displays that, unlike previous studies, did not involve any abstract, symbolic, or geometric stimuli—stimuli for which schooling in general may generate an advantage. Moreover, the present displays were irregularly spaced, in order to prevent obvious scanning strategies. Yet despite this, illiteracy resulted in a disadvantage in search. This indicates that literacy has real consequences not only for reading and language-related processes, but also for other, attentional skills. We report a number of important findings. The first main finding is that low literacy was associated with substantially longer RTs in both experiments. A similar slowing was found in a previous visual search study by Bramao et al. (2007) for their illiterate group, although their design did not allow them to dissociate it from set size effects. In Experiment 1, the low literates were also overall less efficient (as indicated by stronger set size effects), but this did not replicate in Experiment 2. What causes this overall slowing? Experiment 2 suggests that part of it may be due to some slowing in display-wide (i.e., parallel) sensory processing, as the low literacy group was slower in making an eye movement towards the pop out target in the colour search. The largest part however appears to lie in postselection processes, after the target has been found, as low literates needed more time between fixating the target and generating the manual response. Postselection processes include target verification (is the item I have selected really the target?), stimulus–response mapping, and actual response execution. Any of these could be influenced by literacy. For example, low literates may use a more serial task strategy, in which they first solve one step of the task (find the target chicken) and only then turn to the next step (respond to which way it is facing). The high literates may adopt a more integrated or cascadic processing approach in which the accumulation of evidence for the whereabouts of the target is also used for determining its identity, and thus for which response is required. This would be in line with the idea that illiteracy may be associated with reduced working memory capacity or executive control function (Ardila et al., 1989; Le Carret et al., 2003; Reis et al., 2003). More mundane factors may also play a role here. For example, the low literacy observers may have less experience in making left versus right decisions. Even though the task itself did not require knowledge of the concepts of left and right, such concepts may nevertheless help in deciding


94

OLIVERS ET AL.

what to respond to. The low literates may also have less experience with computerized tasks, which may make them more careful before pressing a button. Whatever the cause of this postselection slowing, an important result of Experiment 2 in this respect is that, in the difficult search, although low literates were slower in pressing the button, they were not overall slower in finding the target. This indicates that the worse performance for the low literates does not just reflect a general deficit as might for example be associated with lower intelligence, motivation, or familiarity. Instead, and this is the second main finding, the high and low literacy groups differed in the way search performance was distributed across the visual field. In terms of RTs, literates were relatively better when the target was presented closer to the fixation point, especially on the right. At the same time, high literacy was associated with a more general bias towards the top and left, especially in the more serial shape search. This latter bias emerged from RT comparisons, but was predominantly expressed in the eye movement patterns. In the high literacy group, more initial; eye movements were directed towards the top left of the display than to other areas. Later eye movements ended up in bottom right areas, consistent with a reading-based scan strategy. We hasten to say that these biases were relatively coarse, and also the low literates appeared to have some initial preference for the top (and also left). Search seldom followed a systematic horizontal item-by-item scan from top left to bottom-right, probably also because the display layout was not ideal for such a strategy. Instead, all else being equal, readers appear to have a preference for a left to right and top to bottom direction The findings extend earlier evidence for differences in scanning strategies as induced by literacy (Bramao et al., 2007; Brucki & Nitrini, 2008; Byrd et al., 2005; Le Carret et al., 2003; Ostrosky-Solis et al., 1991; Padakannaya et al., 2002). Whereas this previous work has shown consistent scanning for regular and densely filled arrays with abstract geometrical shapes, our work shows that these also occur for irregular, nonlinguistic, and nongeometric displays. Third, the results suggest that the literacy-related and right-lateralized eccentricity effects are the result of a combination of at least sufficient vision for rapidly detecting targets in (right) parafoveal areas, in combination with a scanning strategy that starts on the left, and ends in right eccentric areas. Thus, it appears that the development of reading skills leads to an extension of the functional visual field from the fovea to parafoveal areas, combined with some asymmetry towards the reading direction, consistent with earlier findings from the reading literature (Rayner, 1998). What might be the neurophysiological correlate of the literacy-related spatial bias in visual search? Recent studies using the PET and fMRI techniques suggest a shift in cortical responses as a function of literacy. When using verbal stimuli, Petersson, Silva, Castro-Caldas, Ingvar, and Reis (2007) repeatedly found more activity in left inferior parietal areas (Brodmann areas 39 and 40, including the temporoparietal junction) for literates, as compared to illiterates. This is to be



95

expected, as these areas are thought to be predominantly involved in the integration of auditory and visual (linguistic) information. The same group of readers also showed a clear reduction in the same areas in the right hemisphere, when compared to the nonreaders. The illiterates showed exactly the opposite pattern, with higher activation in right inferior parietal areas than in the same areas on the left side. The right inferior parietal region is strongly involved in the direction of spatial attention (Yantis et al., 2002), and when lesioned often results in spatial neglect of the left side (Halligan, Fink, Marshall, & Vallar, 2003). Although any link to performance in the current study will remain highly speculative, these studies raise the possibility that the differences in attentional biases that we found between high and low literates relates to the shift in balance between left and right hemisphere spatial orienting networks. Such shifts also occur in more occipital and ventral sites. Dehaene and colleagues (2010) found literacy to correlate with increased specialization of cortical networks even to nonlinguistics stimuli such as houses and faces. With reading experience, the balance in responses to houses and faces shifted more towards the right hemisphere (which is already specialized in these types of stimuli), as the equivalent left hemisphere regions became more responsive to visual word form instead. Most interesting for the present report, Dehaene and colleagues also examined more detailed retinotopic responses in early visual cortex, and found that, even for simple checkerboard patterns, increased literacy led to increased activation on and around the horizontal visual meridian (i.e., along the reading direction). Moreover, this reading-related response to a nonlinguistic stimulus was stronger in the left hemisphere, consistent with the rightward extension of the functional field of view. We conclude that learning to read has two main consequences with regard to visual search abilities, (1) a shift in the distribution of covert visual attention to central and right parts of the visual field that goes beyond the skill of reading alone, and (2) the adoption of certain scanning strategies that are roughly compatible with reading direction. The invention of writing systems is, on an evolutionary scale, a very recent event. Throughout most of human history cognitive processing was not influenced by the processing of written language. Here we have shown that literacy levels have important cognitive consequences that go beyond the processing of orthographic stimuli, by showing that reading changes the spatial distribution of visual search even for nonlinguistic materials. Thus, cultural inventions such as reading shape general cognitive processing in nontrivial ways, causing lasting changes in visual information processing.

REFERENCES Adrian, J. A., Alegria, J., & Morais, J. (1995). Metaphonological abilities of Spanish illiterate adults. International Journal of Psychology, 30(3), 329–353. doi:10.1080/00207599508246574


96

OLIVERS ET AL.

Ardila, A., Rosselli, M., & Rosas, P. (1989). Neuropsychological assessment in illiterates— visuospatial and memory abilities. Brain and Cognition, 11(2), 147–166. doi:10.1016/02782626(89)90015-8 Bertelson, P., de Gelder, B., Tfouni, L. V., & Morais, J. (1989). Metaphonological abilities of adults illiterates: New evidence of heterogeneity. European Journal of Cognitive Psychology, 1(3), 239– 250. doi:10.1080/09541448908403083 Bertera, J. H., & Rayner, K. (2000). Eye movements and the span of the effective stimulus in visual search. Perception and Psychophysics, 62(3), 576–585. doi:10.3758/BF03212109 Bouma, H. (1973). Visual interference in parafoveal recognition of initial and final letters of words. Vision Research, 13(4), 767–782. doi:10.1016/0042-6989(73)90041-2 Bramao, I., Mendonca, A., Faisca, L., Ingvar, M., Petersson, K. M., & Reis, A. (2007). The impact of reading and writing skills on a visuo-motor integration task: A comparison between illiterate and literate subjects. Journal of the International Neuropsychological Society, 13(2), 359–364. doi:10.1017/S1355617707070440 Brucki, S. M. D., & Nitrini, R. (2008). Cancellation task in very low educated people. Archives of Clinical Neuropsychology, 23(2), 139–147. Byrd, D. A., Jacobs, D. M., Hilton, H. J., Stern, Y., & Manly, J. J. (2005). Sources of errors on visuoperceptual tasks: Role of education, literacy, and search strategy. Brain and Cognition, 58(3), 251–257. doi:10.1016/j.bandc.2004.12.003 Chatterjee, A. (2001). Language and space: Some interactions. Trends in Cognitive Sciences, 5(2), 55–61. doi:10.1016/S1364-6613(00)01598-9 de Buurman, R., Roersema, T., & Gerrissen, J. F. (1981). Eye movements and the perceptual span in reading. Reading Research Quarterly, 16(2), 227–235. doi:10.2307/747557 Dehaene, S., Pegado, F., Braga, L. W., Ventura, P., Nunes, G., Jobert, A., … Cohen, L. (2010). How learning to read changes the cortical networks for vision and language. Science, 330(6009), 1359– 1364. doi:10.1126/science.1194140 Dobel, C., Diesendruck, G., & Boelte, J. (2007). How writing system and age influence spatial representations of actions: A developmental, cross-linguistic study. Psychological Science, 18(6), 487–491. doi:10.1111/j.1467-9280.2007.01926.x Duncan, J., & Humphreys, G. W. (1989). Visual search and stimulus similarity. Psychological Review, 96, 433–458. doi:10.1037/0033-295X.96.3.433 Forgays, D. G. (1953). the development of differential word recognition. Journal of Experimental Psychology, 45(3), 165–168. doi:10.1037/h0053888 Gilchrist, I. D., & Harvey, M. (2006). Evidence for a systematic component within scan paths in visual search. Visual Cognition, 14(4–8), 704–715. doi:10.1080/13506280500193719 Goody, J. (1987). The interface between the oral and the written. Cambridge, UK: Cambridge University Press. Halligan, P. W., Fink, G. R., Marshall, J. C., & Vallar, G. (2003). Spatial cognition: Evidence from visual neglect. Trends in Cognitive Sciences, 7(3), 125–133. doi:10.1016/S1364-6613(03)00032-9 Hanushek, E. A., & Woessmann, L. (2008). The role of cognitive skills in economic development. Journal of Economic Literature, 46(3), 607–668. doi:10.1257/jel.46.3.607 He, S., Cavanagh, P., & Intriligator, J. (1997). Attentional resolution. Trends in Cognitive Sciences, 1, 115–121. doi:10.1016/S1364-6613(97)89058-4 Huettig, F., Singh, N., & Mishra, R. K. (2011). Language-mediated visual orienting behavior in low and high literates. Frontiers in Psychology, 2, 285. doi:10.3389/fpsyg.2011.00285 Jewell, G., & McCourt, M. E. (2000). Pseudoneglect: A review and meta-analysis of performance factors in line bisection tasks. Neuropsychologia, 38(1), 93–110. doi:10.1016/S0028-3932(99) 00045-7 Kimura, D. (1966). Dual functional asymmetry of brain in visual perception. Neuropsychologia, 4(3), 275–285. doi:10.1016/0028-3932(66)90033-9



97

Kolinsky, R., Morais, J., & Verhaeghe, A. (1994). Visual separability: A study on unschooled adults. Perception, 23(4), 471–486. doi:10.1068/p230471 Kosmidis, M. H., Tsapkini, K., Folia, V., Vlahou, C. H., & Kiosseoglou, G. (2004). Semantic and phonological processing in illiteracy. Journal of the International Neuropsycholical Society, 10(6), 818–827. Landau, A. N., & Fries, P. (2012). Attention samples stimuli rhythmically. Current Biology, 22(11), 1000–1004. doi:10.1016/j.cub.2012.03.054 Le Carret, N., Rainville, C., Lechevallier, N., Lafont, S., Letenneur, L., & Fabrigoule, C. (2003). Influence of education on the benton visual retention test performance as mediated by a strategic search component. Brain and Cognition, 53(2), 408–411. doi:10.1016/S0278-2626(03)00155-6 Lukatela, K., Carello, C., Shankweiler, D., & Liberman, I. Y. (1995). Phonological awareness in illiterates: Observations from Serbo-Croatian. Applied Psycholinguistics, 16(4), 463–487. doi:10.1017/S0142716400007487 Luria, A. R. (1976). The working brain: An introduction to neuropsychology. London: Penguin. Maass, A., & Russo, A. (2003). Directional bias in the mental representation of spatial events: Nature or culture? Psychological Science, 14(4), 296–301. doi:10.1111/1467-9280.14421 McConkie, G. W., & Rayner, K. (1975). Span of effective stimulus during a fixation in reading. Perception and Psychophysics, 17(6), 578–586. doi:10.3758/BF03203972 McConkie, G. W., & Rayner, K. (1976). Asymmetry of perceptual span in reading. Bulletin of the Psychonomic Society, 8(5), 365–368. doi:10.3758/BF03335168 Mishra, R. K., Singh, N., Pandey, A., & Huettig, F. (2012). Spoken language-mediated anticipatory eyemovements are modulated by reading ability—Evidence from Indian low and high literates. Journal of Eye Movement Research, 5, 1–10. Morais, J., Bertelson, P., Cary, L., & Alegria, J. (1986). Literacy training and speech segmentation. Cognition, 24(1–2), 45–64. doi:10.1016/0010-0277(86)90004-1 Morais, J., Cary, L., Alegria, J., & Bertelson, P. (1979). Does awareness of speech as a sequence of phones arise spontaneously? Cognition, 7(4), 323–331. doi:10.1016/0010-0277(79)90020-9 Morais, J., Castro, S. L., Scliar-Cabral, L., Kolinsky, R., & Content, A. (1987). The effects of literacy on the recognition of dichotic words. Quarterly Journal of Experimental Psychology, 39A(3), 451–465. doi:10.1080/14640748708401798 Neisser, U. (1998). The rising curve: Long term gains in IQ and related measures. Washington, DC: American Psychological Association. Nicholls, M. E. R., & Roberts, G. R. (2002). Can free-viewing perceptual asymmetries be explained by scanning, pre-motor or attentional biases? Cortex, 38(2), 113–136. doi:10.1016/S0010-9452 (08)70645-2 Olson, D. R. (1994). The world on paper: The conceptual and cognitive implications of writing and reading. Cambridge, UK: Cambridge University Press. Ostrosky-Solis, F., Efron, R., & Yund, E. W. (1991). Visual detectability gradients: Effect of illiteracy. Brain and Cognition, 17(1), 42–51. doi:10.1016/0278-2626(91)90065-G Padakannaya, P., Devi, M. L., Zaveria, B., Chengappa, S. K., & Vaid, J. (2002). Directional scanning effect and strength of reading habit in picture naming and recall. Brain and Cognition, 48(2–3), 484–490. Petersson, K. M., Reis, A., Askelof, S., Castro-Caldas, A., & Ingvar, M. (2000). Language processing modulated by literacy: A network analysis of verbal repetition in literate and illiterate subjects. Journal of Cognitive Neuroscience, 12(3), 364–382. doi:10.1162/089892900562147 Petersson, K. M., Silva, C., Castro-Caldas, A., Ingvar, M., & Reis, A. (2007). Literacy: A cultural influence on functional left-right differences in the inferior parietal cortex. European Journal of Neuroscience, 26(3), 791–799. doi:10.1111/j.1460-9568.2007.05701.x Pollatsek, A., Bolozky, S., Well, A. D., & Rayner, K. (1980). Asymmetries in the perceptual span for Israeli readers. Bulletin of the Psychonomic Society, 16(3), 170–170.


98

OLIVERS ET AL.

Ranis, G., Stewart, F., & Ramirez, A. (2000). Economic growth and human development. World Development, 28(2), 197–219. doi:10.1016/S0305-750X(99)00131-X Rayner, K. (1986). Eye-movements and the perceptual span in beginning and skilled readers. Journal of Experimental Child Psychology, 41(2), 211–236. doi:10.1016/0022-0965(86)90037-8 Rayner, K. (1998). Eye movements in reading and information processing: 20 years of research. Psychological Bulletin, 124(3), 372–422. doi:10.1037/0033-2909.124.3.372 Rayner, K., Well, A. D., & Pollatsek, A. (1980). Asymmetry of the effective visual-field in reading. Perception and Psychophysics, 27(6), 537–544. doi:10.3758/BF03198682 Read, C., Zhang, Y. F., Nie, H. Y., & Ding, B. Q. (1986). The ability to manipulate speech sounds depends on knowing alphabetic writing. Cognition, 24(1–2), 31–44. doi:10.1016/0010-0277(86) 90003-X Reis, A., & Castro-Caldas, A. (1997). Illiteracy: A cause for biased cognitive development. Journal of the International Neuropsychological Society, 3(5), 444–450. Reis, A., Castro-Caldas, A., Ingvar, M., & Petersson, K. M. (2000). Illiteracy influences 2D but not 3D visual object naming. International Journal of Psychology, 35(3–4), 211–212. Reis, A., Faisca, L., Ingvar, M., & Petersson, K. M. (2006). Color makes a difference: Twodimensional object naming in literate and illiterate subjects. Brain and Cognition, 60(1), 49–54. doi:10.1016/j.bandc.2005.09.012 Reis, A., Guerreiro, M., & Petersson, K. M. (2003). A sociodemographic and neuropsychological characterization of an illiterate population. Applied Neuropsychology, 10(4), 191–204. doi:10.1207/s15324826an1004_1 Rezec, A. A., & Dobkins, K. R. (2004). Attentional weighting: A possible account of visual field asymmetries in visual search? Spatial Vision, 17(4–5), 269–293. doi:10.1163/1568568041920203 Scribner, S. (1974). Developmental aspects of categorized recall in a West African society. Cognitive Psychology, 6, 475–494. doi:10.1016/0010-0285(74)90022-X Scribner, S., & Cole, M. (1981). The psychology of literacy. Cambridge, MA: Harvard University Press. Serniclaes, W., Ventura, P., Morais, J., & Kolinsky, R. (2005). Categorical perception of speech sounds in illiterate adults. Cognition, 98(2), B35–B44. doi:10.1016/j.cognition.2005.03.002 Silva, C., Faisca, L., Ingvar, M., Petersson, K. M., & Reis, A. (2012). Literacy: Exploring working memory systems. Journal of Clinical and Experimental Neuropsychology, 34(4), 369–377. doi:10.1080/13803395.2011.645017 Stein, J., & Walsh, V. (1997). To see but not to read; The magnocellular theory of dyslexia. Trends in Neurosciences, 20(4), 147–152. doi:10.1016/S0166-2236(96)01005-3 Treisman, A., & Gelade, G. (1980). A feature-integration theory of attention. Cognitive Psychology, 12, 97–136. doi:10.1016/0010-0285(80)90005-5 UNESCO. (2008). Literacy statistics: A review of concepts, methodology, and current data. Montreal: Author. Yantis, S., Schwartzbach, J., Serences, J. T., Carlson, R. L., Steinmetz, M. A., Pekar, J. J., & Courtney, S. M. (2002). Transient neural activity in human parietal cortex during spatial attention shifts. Nature Neuroscience. 5(10), 995–1002.


99

APPENDIX TABLE A1 Results of Experiment 1. Average RTs and average slopes (between parentheses) for each group and each task, as a function of target side (L = left; R = right), and altitude (top, middle, bottom); Av is average across left and right or across top and bottom Search difficulty


Easy search

Difficult search

High literacy

Display section (altitude/side)

L

R

Top Middle Bottom Av Top

642 607 642 630 753

(4) (3) (3) (3) (19)

Middle Bottom Av

688 (14) 757 (18) 732 (18)

641 598 633 624 753

(3) (3) (2) (2) (18)

699 (13) 745 (17) 732 (17)

Low literacy Av 641 (4) 602 (3) 626 (3) 753 (19) 693 (14) 751 (17)

L 864 822 865 850 1045

R (3) (5) (2) (3) (24)

868 850 840 853 1015

1012 (23) 1032 (20) 1030 (22)

Av (7) (5) (6) (6) (25)

966 (32) 1039 (15) 1007 (24)

866 (5) 836 (5) 853 (4) 1030 (25) 989 (27) 1035 (18)

TABLE A2 Results of Experiment 1. Average RTs and average slopes (in parentheses) for each group and each task, as a function of target side and eccentricity High literacy Search difficulty Easy search

Difficult search

Eccentricity Far Near Av Far Near Av

L 652 609 631 780 685 732

(3) (4) (3) (20) (14) (17)

R 650 599 625 773 686 730

(3) (3) (3) (20) (13) (16)

Low literacy Av 651 (3) 604 (3) 777 (20) 685 (13)

L 882 822 852 1067 973 1020

R (2) (5) (3) (23) (22) (22)

L = left; R = right; Av is average across left and right or across eccentricity.

861 843 852 1029 990 1009

Av (6) (6) (6) (18) (28) (23)

871 (4) 843 (5) 963 (20) 914 (25)

100

OLIVERS ET AL.

TABLE A3 Results of Experiment 2. Average RTs and average slopes (between parentheses) for each group and each task, as a function of target side (L = left; R = right), and altitude (top, middle, bottom); Av is average across left and right or across top and bottom High literacy Search difficulty

Display section (altitude/side)


Easy search

Difficult search

L

R

Top Middle Bottom Av Top

699 654 681 678 851

(3) (1) (4) (3) (19)

Middle Bottom Av

760 (14) 831 (19) 814 (17)

699 652 670 674 856

(3) (3) (3) (3) (21)

774 (17) 832 (20) 821 (19)

Low literacy Av

L

675 (4) 653 (2) 699 (3)

872 806 851 843 1047

753 (19) 693 (14) 751 (17)

R (3) (2) (4) (3) (16)

965 (16) 1018 (16) 1010 (16)

872 824 853 850 1010

Av (5) (3) (4) (4) (18)

955 (12) 994 (16) 1007 (24)

872 (4) 815 (3) 852 (4) 1028 (17) 960 (14) 1006 (16)

TABLE A4 Results of Experiment 2. Proportion of the first two eye movements as directed to each of the quadrant in the display (regardless of target position) High literacy

Easy search

Top Bottom Top Bottom

Difficult search

Low literacy

L

R

L

R

0.286 0.245 0.291 0.271

0.280 0.189 0.252 0.186

0.237 0.270 0.228 0.277

0.257 0.235 0.234 0.262

L = left; R = Right.

TABLE A5 Results of Experiment 2. Average RTs and average slopes (in parentheses) for each group and each task, as a function of target side and eccentricity High literacy Search difficulty Easy search

Difficult search

Eccentricity Far Near Av Far Near Av

L 704 650 677 869 758 813

(4) (2) (3) (21) (14) (17)

R 703 639 671 891 740 816

(3) (4) (3) (24) (14) (19)

Low literacy Av 704 (3) 645 (3) 880 (22) 749 (14)

L 876 815 846 1061 955 1008

R (4) (2) (3) (18) (12) (15)

874 822 848 1026 946 986

L = left; R = Right; Av is average across left and right or across eccentricity.

Av (5) (4) (4) (18) (14) (16)

875 (4) 819 (3) 1044 (18) 951 (13)


101

TABLE A6 Results of Experiment 2. Average target fixation latencies for each group and each task, as a function of target side and eccentricity High literacy Search difficulty Easy search


Difficult search

Low literacy

Eccentricity

L

R

Av

L

R

Av

Far Near Av Far Near Av

492 438 465 665 561 613

496 437 466 697 559 628

494 438

540 470 505 685 599 642

536 470 503 650 575 612

538 470

681 560

667 587

L = left; R = Right; Av is average across left and right or across eccentricity.

TABLE A7 Results of Experiment 2. Proportion of the first two eye movements as a function of side and eccentricity (regardless of target position) High literacy

Easy search Difficult search

L = left; R = right.

Far Near Far Near

Low literacy

L

R

L

R

0.309 0.222 0.395 0.166

0.229 0.240 0.257 0.180

0.307 0.201 0.320 0.184

0.282 0.211 0.297 0.199