Ординатура / Офтальмология / Английские материалы / Eye Movements A Window on Mind and Brain_Van Gompel_2007

Abstract

It is commonly assumed that eye movements in reading are determined with respect to word entities, and that the distribution of initial landing sites in words derives from a strategy of aiming at specific parts of peripherally located target words. The current study investigated the oculomotor processes responsible for the determination of saccade length and initial landing sites. Distributions of saccade length during pseudo-reading and normal reading were analyzed. Strategy-based, visually guided and corrective saccades were qualitatively identified after examining the influence of launch site, word length and saccade latency. Gaussian mixture models were implemented to approximate the frequency of the three groups of saccades. The distributions of saccade length in pseudoreading and normal reading were simulated; the percentages of saccade frequency for the three groups varied in relation to saccade latency, word length and launch distance. Both simulated and empirical data showed that strategy-based saccades of a relatively constant length were favored at early time intervals whereas visually guided saccades became more likely at later times during a fixation; the former were more frequent in reading compared with pseudo-reading. It was concluded that eye guidance in reading is the result of dynamic coding of saccade length instead of cognitively based aiming strategies.

Saccadic eye movements have long been considered ballistic and goal-oriented (Jurgens, Becker, & Kornhuber, 1990; Robinson, 1975). In reading research, many models of eyemovement control assume such properties (e.g., Engbert, Nuthmann, Richter, & Kliegl, 2006; Just & Carpenter, 1980; Morrison, 1984; Reichle, Pollatsek, Fisher, & Rayner, 1998; Reichle, Rayner, & Pollatsek, 2003). These models postulate that the gaze is continuously shifted from one processed word to the next, aiming specifically at certain parts of peripheral target words for various reasons (McConkie, Kerr, Reddix, & Zola, 1988; O’Regan & Lévy-Schoen, 1987; Reichle, Rayner, & Pollatsek, 1999). Variations in the targeting strategy may occur when there is a need to refixate a word, to skip a word, or to make a regressive saccade to a previously fixated word. We will refer to this as “word-based eye guidance”.

The most cited finding for supporting word-based eye guidance is the observation of the “preferred viewing position” effect. The effect can be seen when one plots the distribution of initial landing sites in a word. The typical Landing Site (LS) curve shows that, despite a great variability of initial landing sites, the eyes most often land at a position slightly to the left of the center of words, with the amount of deviation being a function of word length (McConkie et al., 1988; O’Regan, 1979; Rayner, 1979; Vitu, O’Regan, & Mittau, 1990). This phenomenon has been repeatedly demonstrated in numerous studies and few researchers question the influence of word length on initial landing sites.

Other phenomena further argue for word-based eye guidance (see Inhoff, Radach, Eiter, & Juhasz, 2003). These include the influence of launch site (or distance of the eyes to the beginning of a word) on initial landing site (McConkie, Kerr, Reddix, Zola, & Jacobs, 1988; Radach & McConkie, 1998). The effect shows that the eyes tend to overshoot the center of words when they are launched from a close distance and undershoot the center with distant launch sites. In addition, when mean initial landing sites are expressed with respect to the center of words and are plotted against center-based launch site (the distance of the launch site to the center of the word), they exhibit a linear relationship (mean center-based landing site increases with center-based launch distance) and the effect of word length is strongly reduced.

Commonly held explanations for the LS curve and the launch site effect rely on the assumption that readers aim for the center (or the optimal viewing position) of peripherally located target words in order to expedite word processing (O’Regan, 1990, 1992; O’Regan & Lévy-Schoen, 1987; McConkie et al., 1988). A word is more easily recognized when the eyes initially fixate near the center of the word than when they fixate at the beginning or end of the word (Brysbaert, Vitu, & Schroyens, 1996; O’Regan, 1990; O’Regan & Jacobs, 1992; O’Regan, Lévy-Schoen, Pynte, & Brugaillère, 1984; Nazir, O’Regan, & Jacobs, 1991). The great variability of initial landing sites in words and the fact that many saccades do not land near the center of words would result from oculomotor aiming errors. In particular, the influence of launch site would result from systematic oculomotor range error (Kapoula, 1985; McConkie et al., 1988; Radach & McConkie, 1998; but see Vitu, 1991a–b), that the eyes would be biased towards making saccades of a constant length (i.e., the length that corresponds to the center of the range of saccade lengths associated with the task).

Two different views are held with respect to the mechanism responsible for determining the saccade-target word in peripheral vision. The first view envisages saccade-target selection as the result of low-level visuomotor processes, assuming that it is not related to ongoing word identification processes. This will be referred to as the “stimulus-based” hypothesis. In this, words are nothing more than visual blobs and the selected target word is either the next word (McConkie et al., 1988; O’Regan, 1990; Radach & McConkie, 1998) or the next long word (Reilly & O’Regan, 1998).

Alternatively, as proposed in recent models of eye-movement control, the saccadetarget word may be defined with respect to ongoing word identification processes; this view will be referred to as the “processing-based” hypothesis. For instance, the E-Z reader model proposes that in reading, words are processed serially due to sequential attention shifts (Reichle et al., 2003). A saccade within the fixated word (refixation) is first programmed as a default and the refixation probability depends on word length. If an intermediate level of processing associated with the fixated word (i.e., word familiarity check) is reached before the refixation saccade is ready to be triggered, the refixation is cancelled and the programming of a saccade to the next word begins. However, again, if processing of the next word reaches the intermediate processing level before saccade programming enters a stage of no return, the saccade is cancelled and a new saccade is planned toward the following word, hence skipping the initial target word. Thus, in this model, a processing-based targeting mechanism is used to guide the eyes. The SWIFT model is another example of processing-based models, although it relies on a slightly different saccade-target selection mechanism. In this model, words are processed in parallel, and each word/letter receives a certain amount of attractiveness depending on the level of processing associated with the word at a given point in time (Engbert et al., 2006; Kliegl et al., 2003). When a word is completely processed, the weight of each letter in this word is set to zero, while the attractiveness of each letter in a word that is not yet identified increases as the processing of that word progresses. A saccade is sent to the letter with maximal attractiveness when a random waiting time for saccade initiation is reached. Although these two versions of the processing-based hypothesis differ in the unit of targeting (word vs letter), they are similar in that the level of linguistic processing for a word determines where the eyes are sent. Both assume that information from the word-processing mechanism can directly determine the location of the saccade target. The oculomotor system merely executes the decision of language processes, although subject to oculomotor errors.

In recent studies, alternatives of the above-mentioned word-based hypotheses were proposed. These proposals reject the assumption that eye guidance in reading relies predominantly on a saccade-targeting mechanism. For instance, Vitu (2003) in a commentary of the E-Z reader model pointed out the great similarity of the effects of launch site on the likelihood of word skipping and the distributions of initial landing sites in words. This particular finding is inconsistent with a processing-based hypothesis that attributes variations in both word skipping and initial landing sites to different mechanisms, namely ongoing word identification processes and oculomotor aiming errors. She proposed that the eyes move toward the center of gravity of the peripheral text configuration, thus

without aiming for a specific target location. The eyes would be pulled by the visual stimuli in the forward peripheral region and the stimuli closer to the fovea would have greater weight (see also, Vitu, 1991a,b).

Yang and McConkie (2001, 2004) proposed a different view on the determination of saccade length, although sharing the assumption that word-based eye guidance is not the general rule. Their rationale was the following: If the detection of word boundaries, and in the extreme case the identification of peripheral words, were necessary for eye guidance in reading, as assumed in processingand stimulus-based hypotheses, reading should be impaired in the absence of clear visual boundaries between individual words. Without proper word segmentation, word identification would become extremely laborious and its processing time very lengthy. In addition, the process of isolating visual word units for the purpose of aiming at any particular part of words would also be particularly difficult and time consuming. Reading under those conditions should break down somehow. Yang and McConkie (2004) showed that this is not the case. In their study, during randomly selected saccades, the normal text was replaced with un-spaced nonwords or unbroken homogenous letter strings for a single (critical) fixation and the normal text was returned during the immediate following saccade. Thus, during the critical fixation, no word boundaries were available. If the localization of the to-be-fixated word was essential for guiding the eyes, saccade initiation should be greatly postponed or at least altered in this condition. Results showed instead that lacking clearly defined word boundary for a single fixation did not significantly alter the length of the immediate following saccade. Only a slight shift of the distribution of saccade length toward smaller lengths was observed; the length of many late saccades (initiated 225 ms or later during the critical fixation) was shortened by one or two letters, but the length of earlier saccades remained unaffected. Thus, it seemed that the lack of spatial segmentation did not systematically disrupt or postpone saccade initiation.

To account for the above observations, Yang and McConkie proposed the competition/interaction (or C/I) model of eye-movement control in reading. In this model, the oculomotor system encodes the impending saccade using a population-coding scheme. Many neurons optimally representing different saccadic metrics (direction and length) are activated to collectively signal the precise landing location (Lee, Rohrer, & Sparks, 1988). The variability of saccade length results from the varying distribution of movement-coding activity from saccade to saccade. Two main factors affect the coding of saccade length: At earlier time intervals, saccades occur independently of the visual input; eye guidance is propelled by strategy-based activation encoded in the oculomotor system. The current visual input has its influence at later time intervals; it changes the pattern of activation in population coding. This influences in turn saccade metrics and allows the eyes to be sent to a specific location (such as the center of words, or a position slightly left of it) without employing any specific aiming strategy. The term “strategy-based activation” here refers to the tendency for the oculomotor system to generate experience-dependent activation in the neural region that actually computes the metrics of saccadic eye movements. In reading English, readers move their eyes with an average forward saccade length of 7–8 letters. Yang and McConkie hypothesized that, for skilled readers, at the beginning of

each fixation there is an anticipatory activity that is built up gradually in the neural regions to signify the preferred saccade length. Recent oculomotor research has estimated that the onset time of the anticipatory activity is around 60–70 ms after fixation onset (Dorris et al., 1999). This strategy-based activation persists throughout the fixation, and the coding of the movement itself is continuously updated. As the new information about current visual stimuli becomes available, it can be integrated into the ongoing movement computation. Any time when the threshold for movement is reached, a saccade based on the currently coded movement activity is initiated. Effectively, the C/I model is a revision of stimulus-based models. It adds the strategy-based activation to the oculomotor system to allow saccades to occur despite the lack of any useful visual segmentation. The C/I model accepts that saccade length is affected by the visual configuration or even by the saliency of individual words because of their frequency in the language; however, it rejects the notion that eye guidance is uniquely controlled by a saccade-targeting mechanism which systematically sends the eyes to a specific location in a specific word depending on visual or ongoing language processing.

The current study was an attempt to account for the frequency distribution of saccade length in both pseudo-reading and normal reading based on the C/I model. It aimed at testing the idea that strategy-based activation is responsible for eye guidance during the initial part of a fixation and that it continues to influence eye guidance even when visual input becomes available. Three predictions on the “where” decision in reading arise from the C/I model. First, saccades initiated at earlier times during fixation (before visual input is available for computing saccade length) are mostly strategy-based and have a constant length. The landing site of the resulting saccades should deviate from the visually preferred location (e.g., the center of a word) and it should be greatly influenced by launch site. Second, saccades with a later onset time should be sent closer to the preferred location in a word; these should be relatively independent of the launch site, as the location of word/letter units becomes available for the computation of saccade amplitude. However, due to the continuing existence of strategy-based activation, the landing sites may still be biased toward a preferred saccade length. Third, when late-onset saccades are not made accurately enough, they are more likely corrected with a following saccade. The correction is based on the comparison between the current landing site in a word and the visually preferred landing site in relation to that word. Early-onset saccades with the same amount of deviation would be less likely to result in correction, as they are triggered by strategy-based activation and do not initially aim at a specific location (therefore requiring no correction).

By adopting the oculomotor range error assumption, processingand stimulus-based hypotheses also predict that the length of some saccades (most likely the early ones) is independent of the location of the target word (Engbert et al., 2006; Reichle et al., 2003). Saccade programming would favor the execution of saccades of a preferred length (Kapoula, 1985; McConkie et al., 1988; Radach & McConkie, 1998); however, the bias should not be toward the mean length of saccades usually observed in reading as proposed by the C/I model but toward the center of the range of saccade lengths executed in the experiment.

1. Study one: Pseudo-reading

In reading, the length of words varies greatly and often one or even two words are skipped. For any particular fixation, it is difficult to assert whether the eyes landed on the intended word and whether they landed at the aimed-for location in that word. When refixations on the same word occur, it is also difficult to examine whether they are oculomotoror linguistically based. To discern the oculomotor mechanism underlying the “where” decision from other confounding factors, we conducted a pseudo-reading study designed to examine the oculomotor processes hypothesized in the C/I model. In the study, subjects were asked to read pages of multiple-line pseudo-text (homogenous X-letter strings). Participants were asked to shift their gaze horizontally along the lines (from left to right) as in normal reading and to fixate the center of each letter string (hereafter pseudo-word). Each pseudo-word consisted of 11 X letters, with either the central letter or the whole letter string being capitalized. Examples of both center-uppercased and all-uppercased text are shown in Figure 1a. The length of X-letter strings was chosen so as to create noticeable difference between the average saccade length usually observed in normal reading (7–8 letters) and the expected length of visually guided saccades in the current study (12-letter distance between the centers of adjacent pseudo-words), and hence to favor the occurrence of landing position errors and the subsequent oculomotor responses to such error. The C/I model predicts that early saccades would be biased toward an average length of 7–8 letters, while both processingand stimulus-based hypotheses predict a bias toward the average length of 12 letters in the task, with the latter being due to systematic oculomotor range effect.

Thirty-one adults who were native English speakers with normal or corrected-to-normal vision participated in the experiment. They were seated in a quiet room with controlled fluorescent light and their eyes were about 80 cm from the screen. At this distance, there were 2.8 letters per degree of visual angle. An SR Eyelink eye-tracker was mounted onto the head of the participant and a chin-rest was used to help stabilize the head. Participants used a button box to control the progress of the experiment.

1.1. Results

All forward saccades, excluding the first and last ones on a line, were analyzed. Figure 1b shows the frequency distributions of saccade length regardless of launch distance or fixated location in a pseudo-word. It reveals that, when reading both centerand alluppercased text, the frequency distribution of saccade length was bimodal, with the frequency of smaller saccades peaking at 3 letters and larger saccades peaking at 11 letters. This is quite different from the usual unimodal distribution observed in reading, which usually peaks at around 7- to 8-letter saccade lengths. The similarity of the distributions of saccade length in centerand all-uppercase conditions suggests that the oculomotor system does not need a well-defined visual cue to fixate at the center of pseudo-words. This could also reflect the fact that localization of the target position was not crucial in

these three time intervals are determined by different mechanisms (Yang & McConkie, 2001). The duration of the intervals was defined to make the saccade frequency of the latter two groups roughly equal (there were far fewer cases in the early saccade group). These groups were also separated from each other in time so as to enhance the distinction between the groups. Figure 1c shows the resulting distributions of saccade length for the three saccade-latency groups. In the figure, the frequency of saccade length in each time interval was not divided by the total frequency of each group but by the combined frequencies of the three groups. This allowed direct comparisons of saccade frequency for different groups at each time interval. Similar calculation was applied to other pseudo-reading figures. Figure 1c reveals that when saccades were initiated within the first 150 ms of fixation their frequency of length had a broad unimodal distribution that peaked at 7- to 8-letter saccade lengths. The distribution of late saccades showed one main peak at a length of 11 letters, and a minor peak at 3- to 4-letter lengths. The frequency of intermediate-latency saccades, meanwhile, formed a bimodal distribution, having a peak at 8- to 9-letter saccade lengths and the other at 3- to 4-letter saccade lengths respectively.

The above results show that, in reading pseudo-words, early-triggered saccades were more variable in length than later saccades, and their length did not reflect the distance between the centers of adjacent pseudo-words but was more similar to that in normal reading. Later saccades were more likely to have the predicted saccade length of 12 letters, consistent with earlier findings that late saccades are more accurate (Coëffé & O’Regan, 1987; McConkie et al., 1988; Radach & Heller, 2000). In addition, there was an overall rightward shift of saccade lengths (for the major peak of the distributions) as saccade latency increased.

To ensure that this was not due to launch site being not controlled for, the distributions of initial landing sites in pseudo-words were plotted for the three latency intervals, but only in instances where saccades were launched from the central region of the previous pseudoword (letter positions 9–12 in the strings). This also served to exclude most occurrences of refixations within pseudo-words. As shown in Figure 1d, early saccades landed at the very beginning of the pseudo-word, or on the space in front of it, instead of its center. For saccades of an intermediate latency, the LS curve was shifted further to the right, peaking at a distance of 3–4 letters from the center of the pseudo-word. For late saccades, the LS curve peaked very close to the center of pseudo-words. Thus, the landing position distribution shifted toward the center of pseudo-words as saccade latency increased, even when launch site was controlled for and refixations were minimized. The later a saccade was made, the more accurately it landed around the center of the pseudo-word.

1.3. Corrective saccades and saccade latency

As shown in Figure 1b, there were many small-length saccades in the groups of intermediateand late-latency saccades. Since there was no benefit from refixating pseudo-words for linguistic reasons and since there were no pseudo-words shorter than 11 letters, these small-length saccades most likely were made in order to correct “inaccurate” saccades sent to an off-center position. Previous studies have suggested that corrective

302 Shun-nan Yang and F. Vitu

saccades having a very short latency are based on corollary discharge computed in the cerebellum (Optican & Robinson, 1980; May, Hartwich-Young, Nelson, Sparks, & Porter, 1990); visually guided corrective saccades require a longer latency, usually longer than 150 ms (Vitu, McConkie, & Yang, 2003). Most likely, the small-length saccades observed in the present study were visually driven as they occurred mainly after 175 ms.

In the C/I model, visually guided corrective saccades occur following a saccade that aims at a specific location but actually fails to land at that location; thus, they are presumably more likely following long-latency saccades since these allow the encoding of the target location. In contrast, early saccades do not rely on visual input; they should not be corrected. In other words, the likelihood of corrective saccades N should be a function of how frequently the eyes landed away from the target location following a late saccade N−1. To test this prediction, we selected cases where saccade N was preceded by either a short- (shorter than 150 ms) or long-latency (300–400 ms) saccade N −1 and plotted the frequency of length for the three latency groups of saccade N . The results revealed that the percentage of small-length saccades was greatly reduced when preceded by short-latency saccades N −1 (a 32% reduction for all three groups combined compared to those reported in Figure 1b). In contrast, when saccade N −1 had a longer latency (300–400 ms), the frequencies of small-length saccades N for the three latency groups of saccade N increased by about 24%. Thus, consistent with the C/I model, small-length saccades were more likely when the latency of the preceding saccade was longer.

These results are at odd with previous reports suggesting an increase of saccade accuracy with saccade latency in general (Coëffé & O’Regan, 1987; Viviani & Swensson, 1982). This would predict less corrective saccades N following lately triggered saccades N −1. To examine the respective contributions of latency and accuracy of saccade N −1 to the likelihood that saccade N was a corrective saccade, the percentage of small-length saccades N (2–5 letters long) for individual subjects was plotted against the percentage of saccades N−1 that landed in the central region of pseudo-words (letter positions between 9 and 12 in the strings) and were initiated at earlier (200–300 ms) or later (longer than 300 ms) time interval, as shown in Figure 2. These two time intervals were chosen to include comparable frequencies of center-fixating saccades; according to the C/I model, the earlier time interval should contain much less visually guided saccades than the later time interval. If saccades in these two latencies were both visually guided, the relation between the frequency of corrective saccades N and the frequency of center-fixating saccade N−1 should be the same regardless the latency of saccade N−1. Figure 2 reveals that when saccade N−1 had a latency longer than 300 ms, the percentage of center-fixating saccades N −1 was negatively correlated with the percentage of small-length saccades N (2- to 5-letter length), r = 711, p < 0005. In contrast, there was no significant correlation when the latency of center-fixating saccade N−1 was between 200 and 300 ms, r = 152, p = 94. This shows that the likelihood of corrective saccades following shorter-latency saccades N−1 (200–300 ms) was unrelated to the landing site of saccade N−1 in relation to the center of pseudo-words, whereas the likelihood of corrective saccades following long-latency saccades depended on it. Therefore, the occurrence of small-length saccades