Examining the activity-distribution model of visual ...

Read as Keyed THE QUARTERLY JOURNAL OF EXPERIMENTAL PSYCHOLOGY, 2002, 55A (2), 627–641

Examining the activity-distribution model of visual attention with exogenous cues and targets Jay Pratt and Lena Quilty University of Toronto, Toronto, Canada LaBerge and his co-workers (e.g., LaBerge & Brown, 1986, 1989; LaBerge, Carlson, Williams, & Bunney, 1997) used an experimental method consisting of three rapid successive displays, each requiring a difficult letter discrimination, to show that visual attention is best accounted for with an activity-distributio n model rather than a moving-spotlight model. The present study sought to further this line of investigation by inserting exogenous cues and targets, often used in studies that have found support for the moving-spotlight model, into the basic method used by LeBerge and colleagues. The results from three experiments were consistent with the activity-distribution model and not with the moving-spotlight model.

By selectively attending to limited portions of the visual field, visual information important to the task at hand is committed for processing whereas irrelevant or distracting information is ignored. Because the ability to attend selectively to visual information is critical to our daily interactions with our environment, a considerable amount of research effort has been spent on understanding exactly how this orientation of attention takes place. For over 20 years, the dominant theoretical perspective has been based on the metaphor of a unitary moving spotlight of attention (e.g., Posner, Synder, & Davidson, 1980; Shulman, Remington, & MacLean, 1979; Sperling & Weichselgartner, 1995). However, LaBerge and his colleagues (LaBerge & Brown, 1986, 1989; LaBerge, Carlson, Williams, & Bunney, 1997) have suggested that the allocation of attention is best conceived of as the result of a distribution of attentional activity. LaBerge et al. tested two versions of the moving-spotlight model and their activitydistribution model in a series of experiments in which participants were required to make a series of difficult letter discriminations. Over these three experiments, they consistently found support for the activity-distribution model. The present set of experiments continues this comparison of the two types of models by inserting simple exogenous cues and targets (similar to the kind used in studies supporting the moving-spotlight model) into the task used Requests for reprints should be sent to Jay Pratt, Department of Psychology, 100 St. George Street, University of Toronto, Toronto, Ontario, Canada, M5S 3G3. Email: [email protected] This research was supported by operating and equipment grants by the Natural Sciences and Engineering Council of Canada to Jay Pratt. The authors would like to thank two anonymous reviewers for their helpful comments. Ó 2002 The Experimental Psychology Society http://www.tandf.co.uk/journals/pp/02724987.html DOI:10.1080/02724980143000398

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by LaBerge et al. Details of the rationale for these experiments are presented later, after a brief review of the moving-spotlight and activity-distribution models of attention. Posner et al. (1980) stated that attention “can be likened to a spotlight that enhances the efficiency of detection of events within its beam” (p. 172). This conclusion arose from several experiments in which participants were given advance information about the most likely target location in an upcoming trial. Sometimes this information was presented at the beginning of a block of trials, and sometimes it varied from trial to trial through the use of a centrally presented arrow cue (also termed an endogenous cue). The basic finding was that, compared to a neutral baseline, detection reaction times (RTs) were faster when the target appeared in the predicted location (valid trial) and slower when the target appeared in a non-predicted location (invalid trial). Because the participants remained fixated throughout each trial, this pattern of RTs was thought to be due to the movement of attention from the fixated location to the cued location. Thus, faster RTs on valid trials occurred because the target appeared under the beam of attention while slower RTs on invalid trials occurred because the beam of attention had to be moved from the cued location to the target location. Consequently, the pattern of RTs has come to be referred to as attentional “benefits” (the benefit of attending to the target location, as compared to a neutral baseline) and “costs” (the cost of not-attending to the target location, as compared to a neutral baseline). Such benefits and costs are also found with peripheral (or exogenous) cues, such as a brief appearance of an object in the visual field (e.g., Posner & Cohen, 1984). Unlike an endogenous cue, an exogenous cue can produce attentional benefits and costs even if it contains no information about the upcoming target location. However, this facilitatory effect of non-informative exogenous cues is of a relatively short duration, unlike either type of informative cue. Over the past 20 years, although some properties of the moving spotlight of attention have reached general acceptance, other properties remain controversial. Perhaps the most basic property of the spotlight is that it is a single unitary beam of attention. Originally thought to be a fixed size of approximately 1° of visual angle (Eriksen & Eriksen, 1974), work by Eriksen and colleagues (e.g., Eriksen & Yeh, 1985) showed that the spotlight diameter could vary in size. Moreover, it seemed to function much like a zoom lens, with a high concentration of attention when the beam was small and a diffuse concentration of attention when the beam was large. In addition, within the spotlight, attention was found to be most concentrated at the centre of the beam, with decreasing concentration toward the periphery of the beam. Although the unitary nature of the beam is traditionally considered to be the fundamental property of the moving-spotlight model, the manner in which the beam moves through the visual field has yet to be resolved. Initially, the beam was thought to move in an analogue manner across the visual field, such that locations on the way to the cue would temporally become attended to as the beam passed over (e.g., Shulman et al., 1979). Adopting the analogue movement of the spotlight, Tsal (1983) estimated a constant attentional velocity of 1°/ms and speculated that little information is collected as the beam of attention is moving. Later, Remington and Pierce (1984; see also Kwak, Dagenbach, & Egeth, 1991) proposed that attentional movement is time invariant, and that the attentional mechanism adjusts its velocity in proportion to the distance to be travelled, resulting in a nearly constant travel time for a wide range of different distances. There is also evidence that the beam of attention essentially “turns off” during movement, creating the appearance of a discrete switching of attention from location to

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location (e.g., Briand & Klein, 1987). As Eriksen and Murphy (1987) note in their review of the literature at the time, there are many experimental problems and few converging results to suggest how the spotlight of attention is moved from location to location. Perhaps one of the most appealing aspects of the moving-spotlight model of attention is that the hypothesized movement of the beam of attention is very similar to what is known about how we move the focus of our gaze across the visual field. Indeed, it is well known that saccadic eye movements tend to result in corresponding movements of attention (e.g., Deubel & Schneider, 1996; Fischer, 1999; Hoffman & Subramaniam, 1995; Shepard, Findlay, & Hockey, 1986). In fact, one version of the moving-spotlight model, premotor theory, suggests that movements of attention are planned but unexecuted saccadic eye movements (e.g., Rizzolatti, Riggio, Dascola, & Umiltá, 1987). However, several tests of premotor theory have resulted in equivocal findings (e.g., Fischer, 1997; Hodgson & Müller, 1995). A very different model from the moving-spotlight model, the activity-distribution model of attention, has been proposed by LaBerge and his colleagues (LaBerge & Brown, 1986, 1989; LaBerge et al., 1997). The activity-distribution model suggests that attention shifts do not result from the discrete or analogue movement of a beam of attention, but from the opening of a channel at a new location as a channel at a previous location is closed. A channel is defined as an area of more confined activity within an activity distribution, itself defined as a “prolonged, spatially diffuse preparatory state” (LaBerge et al., 1997, p. 1381). The time taken for attention to shift from one location to another then is not a function of the distance between the two locations, but rather depends on how much attentional activity exists at the location just before the appearance of a target. Targets that appear in areas of high activity are responded to quickly, whereas targets that appear in areas of low activity are responded to more slowly. The preparatory attentional activity is distributed across the range of recently attended locations and can therefore be manipulated through a series of targets. A series of target displays is, in fact, how LaBerge and co-workers have examined the activity-distribution model (LaBerge & Brown, 1986, 1989; LaBerge et al., 1997). Their basic experimental method involves a series of four successive stimulus displays. The following trial sequence is taken from LaBerge et al. The first display contains a warning signal (#####* #####) for 1000 ms. It is then replaced by the first target display (T1), which consists of a series of letters (e.g., GQGQGOGQGQGQ) presented for 116 ms. Participants are instructed to determine whether the centre letter in T1 is an O, C, or 0. Following a 50-ms delay, the second target display (T2) then replaces T1 and consists of three letters (e.g., VRV). It is presented for 167 ms at one of three locations (left of centre, centre, right of centre of the overall display). Participants are instructed to determine whether the centre letter of this display is an R, K, or P. The third display (T3) replaces T2 and consists of three letters (e.g., GOQ) presented for 133 ms at one of five locations ranging from left of centre to right of centre. Participants were instructed to determine whether the centre letter of this display was an O, C, or 0. A keypress response was made only if the centre letters for T1, T2, and T3 were O, R, and O, respectively. The warning signal and T1 served to build up the activity gradient at the centre location, and T2 served to shift the gradient slightly from the centre, with the difficult discrimination and flankers ensuring that this gradient had a narrow and high peak. Therefore, although the peak of the gradient at the onset of T3 would be T2’s previous location, some residual activity

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would remain at the centre location. Both the moving-spotlight and activity-distribution models predict that the fastest RT will occur when T3 occurs at the previous location of T2; the moving-spotlight model does so because the spotlight does not need to move, and the activity-distribution model does so because the peak of resources is at that location. However, the moving-spotlight model predicts that RT will increase linearly with distance the further T3 is from the previous location of T2. The activity-distribution model similarly predicts that RT will increase the further T3 is from T2’s previous location; however, the RT when T3 appears at the centre location will be facilitated due to the build-up of resources at that location by the warning signal and T1. Therefore, the moving spotlight model predicts a symmetrical V-shaped curve with the fastest RT at the previous T2 location and linearly increasing RTs the further T3 is from T2’s location. The activity-distribution model predicts an asymmetrical V-shaped curve with the fastest RT at the previous T2 location and a shallower arm corresponding to the direction in which the warning signal and T1 had previously appeared. Over the course of several studies, LaBerge and co-workers (e.g., LaBerge & Brown, 1986, 1989; LaBerge et al., 1997) have consistently found evidence supporting the notion that the time to shift attention depends on the general form of the underlying preparatory activity distribution. It is clear that the evidence supporting each model comes from vastly different experimental methods. On the one hand, the moving-spotlight model has been developed from experiments that have presented a single exogenous or endogenous cue followed by a target (e.g., Eriksen &Yeh, 1985; McCormick & Klein, 1990; Posner & Cohen, 1984; Posner et al., 1980). The activity-distribution model, on the other hand, has been developed by LaBerge and colleagues (LaBerge et al., 1997) from experiments with rapid multiple sequential displays. This wide difference in methodologies may be the root cause of the different findings. The purpose of the present study is to find some common ground between these two methodologies to test further the moving-spotlight and activity-distribution models. In the first experiment, we replicate the basic pattern of results found by LaBerge and co-workers with a conceptual replication of their method. In the second experiment, T2 is replaced by a single exogenous target to examine how this “moving-spotlight method cue” affects the distribution of attentional activity. In the final experiment, to examine how the distribution of attentional activity might affect responses to a “moving-spotlight cue,” T3 is replaced by a single exogenous target. To preview our findings, all three experiments support the activity-distribution model of attention.

EXPERIMENT 1 Experiment 1 was designed to replicate the pattern of results supporting the activitydistribution model found by LaBerge et al. (1997). This pattern of results has two distinctive features: (1) a V-shaped pattern of RTs with the apex of the V occurring when T3 is presented in the same location as T2; and (2) a V that is asymmetrical, with T3 RTs faster on the T1 side of the apex than on the more peripheral side. The moving-spotlight model, on the other hand, would predict a symmetrical V pattern of RTs centred at the T2 location.

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Method Participants Participants were 15 undergraduates from the University of Toronto. All participants had normal or corrected-to-normal vision, and they received course credit for their participation.

Apparatus A PC computer controlled the presentation of stimulus displays on a VGA monitor that was located 44 cm from the eyes of the participants. This distance was maintained by an adjustable chin rest and headrest. The testing room was dimly lit, and each participant was tested individually.

Stimuli and procedure The stimuli and procedures were very similar to that used by LaBerge et al. (1997). The displayed characters were white letters on a black screen, each subtending approximately 0.38° of visual angle with a character centre-to-centre, distance of approximately 0.44°. Each trial consisted of four successive displays: a warning signal, T1, T2, and T3 (the basic trial sequence is shown in Figure 1). All displays were presented at the same horizontal level near the centre of the visual monitor. The warning signal was a string of 10 number signs with an asterisk in the centre (i.e., #####*#####), which was displayed for 1000 ms and then removed. After a delay of 100 ms, T1 was presented for 150 ms and then removed. T1 was a string of 11 alternating Gs and Qs with either an O or a C in the centre (e.g., GQGQGOGQGQG). Following a delay of 50 ms, T2 was presented for 200 ms and then removed. T2 was a string of three letters (VRV or VKV), presented in one of three possible locations: two spaces to the left, the centre, or two spaces to the right (Locations 2, 0, +2, respectively). Following another 50-ms delay, T3 was presented for 150 ms and then removed. T3 was a string of three letters (GOQ or GCQ), presented in one of five possible locations: two or four spaces to the left, the centre, or two or four spaces to the right (Locations –4, –2, 0, +2, +4, respectively). Participants were instructed to respond only if the middle character of T1 was an O, the middle character of T2 was an R, and the middle character of T3 was an O. They were instructed to withhold their response until all four displays had been presented. The intertrial interval was 750 ms. In addition, the participants were instructed to remain fixated throughout each trial. The small overall size of the display (at most, 1.76° from fixation to T3) made eye movements and eccentricity effects on RT unlikely. Participants completed a practice block of 15 trials and then 5 test blocks of 75 trials each. For any given display, there was a 75% chance the central character would be a target (O for T1 & T2, R for T2). Thus, for each participant, about half of the trials were appropriate for responses. Short rest periods were inserted between the blocks. The computer emitted an error tone immediately following any incorrect responses (i.e., a missed response, a false positive response, or if the RT was less than 100 ms).

Results and discussion The mean RTs appear in Figure 2 and were analysed using a 3 (T2 location: –2, 0, + 2) × 5 (T3 location: –4, –2, 0, + 2, + 4) analysis of variance (ANOVA). There was a main effect of T3 location, F(4, 56) = 7.693, p < .01, with the fastest mean RT at the 0 location and the slowest at the –4 and +4 locations. No main effect for T2 locations was found, F(2, 28) < 1. The interaction between T2 and T3 locations was significant, F(8, 112) = 5.962, p < .01. As can be seen in Figure 2, RTs were fastest when T3 occurred at the same location as T2, regardless of whether T2 occurred at the –2, 0, or +2 locations. As noted earlier, this pattern of RTs is consistent

Figure 1. The trial sequence used in Experiment 1, based on the sequence used by LaBerge et al. (1997). The sequence shows T2 at Location –2 and T3 at Location 0 (see the text for details). Experiments 2 and 3 used variations of this basic sequence.

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Figure 2. Experiment 1 mean reaction times for the five T3 locations (–4, –2, 0, 2, 4) when T2 location was –2 (filled dots), 0 (open dots), and +2 (filled triangles). Error bars represent standard error. The distance between each T3 location was approximately 0.88 degrees (see the text for details).

with both the activity-distribution and the moving-spotlight models of visual attention. However, by examining the shape of the V-shaped RTs, it is possible to distinguish between the predictions of the two models. To examine the shape of the V patterns of RTs, slopes were calculated for the left and right arms at the three T2 locations (–2, 0, +2). For the zero T2 location, the slopes were calculated by comparing the most peripheral T3 locations (–4, +4) to the central (0) T3 location. For the peripheral T2 locations, the slopes were calculated by comparing the adjacent locations to the –2 T2 location (Locations –4, 0) and the +2 T2 location (Locations +4, 0). These slopes were calculated for each participant and then averaged to create a mean slope for each location of T2. Both the moving-spotlight and the activity-distribution models predict symmetrical slopes when T2 is at the central location. This was, in fact, the case as the mean slopes were approximately 63 ms/degree for the left arm and 75 ms/degree for the right arm. A t test of these two slopes indicated that they are not different, t(14) < 1. The two models, however, do make different predictions concerning the slopes found at the peripheral T2 locations. The moving-spotlight model predicts symmetrical slopes at these locations, whereas the activitydistribution model predicts asymmetrical slopes (with the steeper slope occurring on the more peripheral side of T2). When T2 was at +2, the mean slope values were approximately 27 ms/ degree for the left (medial) arm, and 96 ms/degree for the right (peripheral) arm. The t test of these two slopes yielded a significant effect, t(14) = 2.99, p < .01. When T2 was at –2, the mean slope values were approximately 89 ms/degree for the left (peripheral) arm, and 27 ms/degree

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PRATT AND QUILTY TABLE 1 Percentage of errors for Experiments 1, 2, and 3

Experiment

T2 Location

T3 Location ———————————————— –4 –2 0 2 4

1

–2 0 2

2.6 3.7 2.1

1.8 2.7 1.3

2.1 1.1 2.1

3.4 2.1 1.3

4.0 4.2 2.7

2

–2 0 2

3.4 2.9 3.4

4.0 5.1 1.6

1.6 1.7 1.9

3.4 3.7 2.9

3.2 4.2 4.3

3

–2 0 2

0.8 1.3 2.1

2.6 0.5 2.9

2.9 1.6 2.1

3.2 2.1 3.2

2.4 2.1 2.9

for the right (medial) arm. The t test of these two arms yielded a significant effect, t(14) = 2.21, p < .05. A 3 (T2 location) × 5 (T3 location) ANOVA of participant errors reveals a significant main effect of T3 location, F(4, 56), 3.476, p = .01, with more errors at the more peripheral locations than at the centre location. No other main effects or interactions were found (ps > .09). The error data appear in the top portion of Table 1. The results of Experiment 1 are consistent with the predictions of the activity-distribution model and replicate the pattern of results found by LaBerge et al. (1997). Specifically, the data suggest that the activity distribution was skewed when T2 was at a peripheral location, with its peak at the T2 location and significant resources remaining at the central location, due to the build-up of resources caused by the warning signal and T1. This resulted in a shallower slope of the arm of the V curve toward the central location and a steeper slope of the arm of the V curve toward the peripheral location. When T2 was at the centre location, the activity distribution was symmetrical, with its peak at the central location, resulting in arms of equal slopes. Having replicated the basic pattern of results found by LaBerge et al., in the next experiment we slightly altered the trial sequence to examine the activity-distribution model with exogenous cues.

EXPERIMENT 2 In an attempt to find some common ground between the disparate experimental methods used in testing the activity-distribution and moving-spotlight models, Experiment 2 incorporated a simple exogenous cue into the middle of the series of stimulus displays (T2). In this experiment, Tl and T3 were exactly the same as before. T2, however, was the abrupt appearance of a short duration exogenous cue (an asterisk), which had no value in determining whether a response should or should not be made. The sudden appearance of an object (the exogenous cue) is thought to orientate attention reflexively in cue–target experiments (e.g., Posner & Cohen, 1984; Yantis & Hillstrom, 1994; Yantis & Jonides, 1984). If such a cue tends to move a spotlight of attention, on the one hand,

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then responses to T3 should be fastest at the T2 locations. Moreover, the symmetrical V shaped pattern of RTs should be found with T3 locations adjacent to the T2 location. On the other hand, the activity-distribution model would predict that the exogenous cue is likely to cause only a small shift in the distribution of attention because relatively few resources are needed to detect the abrupt appearance of the asterisk. At least, this should result in faster RTs for medial T3s than for peripheral T3s when T2 occurs at +2 or –2. At most, the shift in attentional resources may be so small that the fastest RTs occur at the 9 position (where the initial build-up of attentional resources is) regardless of the location of T2. As noted earlier, the bulk of studies that support the moving-spotlight notion of visual attention have used exogenous or endogenous cues followed by targets. Exogenous cues were chosen for T2 in the present study because, unlike endogenous cues, their effect occurs: (1) very rapidly, and (2) without predicting the upcoming target location. Moreover, simple exogenous cues (such as the abrupt appearance of a dot, box, or asterisk) are typically thought to capture attention reflexively (presumably the spotlight of attention) in a wide range of experimental situations (e.g., Egly, Driver, & Rafal, 1994; Henderson & Macquistan, 1993; Posner & Cohen, 1984; Yantis & Jonides, 1984).

Method Participants Participants were 15 undergraduates from the University of Toronto. All participants had normal or corrected-to-normal vision, and they received course credit for their participation.

Apparatus and display The apparatus and display were the same as those described in Experiment 1.

Stimuli and procedure The stimuli and procedure were largely the same as those described in Experiment 1. The only change made was that T2 was now simply an asterisk (*), which could appear in the same three possible locations. Participants were instructed to respond only if the centres of T1 and T3 were Os, and they were to withhold this response until all four displays had been presented. As before, participants completed a practice block of 15 trials, and then five test blocks of 75 trials each. For both T1 and T3, there was a 75% chance that the central character would be a target (O).

Results and discussion The mean RTs appear in Figure 3 and were analysed using a 3 (T2 location: –2, 0, +2) × 5 (T3 location: –4, –2, 0, +2, +4) ANOVA. This revealed a significant main effect of T3 location, F(4, 56) = 25.069, p < .01, with slower responses to the more peripheral locations. A significant interaction between T2 and T3 locations was also found, F(8, 112) = 4.903, p = .01. To examine this interaction, the average slopes for each participant were calculated, and then these values were used to calculate the mean slope for each possible location of T2. When T2 was at 0 (centre location), the mean slope values were approximately 104 ms/degree for the left

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Figure 3. Experiment 2 mean reaction times for the five T3 locations (–4, –2, 0, 2, 4) when T2 location was –2 (filled dots), 0 (open dots), and +2 (filled triangles). Error bars represent standard error. The distance between each T3 location was approximately 0.88 degrees (see the text for details).

arm and 92 ms/degree for the right arm. The t test of these two arms was not significant, t(14) < 1.1, p > .29. When T2 was at – 2, the mean slope values were approximately 78 ms/degree for the left (peripheral) arm, and – 13 ms/degree for the right (medial) arm. The negative slope indicates that fastest responses were to T3s at the zero T2 location, not to those at the –2 T2 location. The t test of these two arms yielded a significant effect, t(14) = 3.25, p < .01 When T2 was at +2, the mean slope values were approximately –40 ms/degree for the left (medial) arm and 54 ms/degree for the right (peripheral) arm. Once again, the fastest RT was at the zero T2 location, not at the +2 T2 location. The t test of these two arms yielded a significant effect, t(14) = 3.64, p < .01. A 3 (T2 location) × 5 (T3 location) ANOVA of participant errors reveals no significant main effect for T2 location, F(2, 28) < 1, nor a T2 by T3 interaction, F(4, 112) < 1.2, p > .3. However, there was a trend for fewer errors when T3 was in the 0 position, F(4, 56) > 2.3, p < .07. Thus, the patterns of RTs were not due to a speed–accuracy trade-off. The error data appear in the middle portion of Table 1. Once again, the results are consistent with the activity-distribution model and not with the moving-spotlight model. Not only were asymmetrical V-shaped patterns of RTs found for the peripheral T2 locations, but the fastest RTs occurred for T3 locations at the central location and not for peripheral T2 locations. Thus, exogenous cues do produce only small shifts in the distribution of attention.

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EXPERIMENT 3 Different predictions can also be made from the activity-distribution and moving-spotlight models with regards to when T3 is a simple exogenous target (an asterisk) preceded by two letter discrimination displays (T1 & T2). Once again, the moving-spotlight model predicts the fastest detection responses at the T2 location with corresponding symmetrical V shaped patterns of RTs. In light of the results of Experiment 2, the activity-distribution model makes a considerably different prediction. Given that the exogenous T2 in Experiment 2 produced a relatively small shift in the distribution of attentional resources, it is likely that relatively few resources are needed to detect the appearance of the asterisk as the imperative stimulus. Assuming that the distribution of attention across the visual field never drops below some minimum level (i.e., the tailing ends of the distribution never reach zero), the activitydistribution model would predict little or no effect of T2 locations on T3 responses.

Method Participants Participants were 15 undergraduates from the University of Toronto. All participants had normal or corrected-to-normal vision, and they received course credit for their participation.

Apparatus and display The apparatus and display were the same as those described in Experiment 1.

Stimuli and procedure The stimuli and procedure were largely the same as those described in Experiment 1. The only change made was that T3 was now simply an asterisk (*), which could appear in the same five possible locations. In order to minimize anticipatory responses, catch trials in which T3 would not appear were used on 20% of the trials. Participants were instructed to respond only if the centre of T1 was an O, the centre of T2 was an R, and T3 appeared, and they were to withhold this response until all four displays had been presented. As in the previous experiments, participants completed a practice block of 15 trials, and then five test blocks of 75 trials each. For both T1 and T2, there was a 75% chance that the central character would be a target (O or R, respectively).

Results and discussion The mean RTs appear in Figure 4 and were analysed using a 3 (T2 location: –2, 0, +2) × 5 (T3 location: –4, –2, 0, +2, +4) ANOVA. This revealed a significant main effect of T2 location, F(2, 28) = 4.607, p = .01, as RTs were faster when T2 was at the central location than when it was at the two peripheral locations. However, no main effect for T3 F(4, 56) < 1.3, p > .29, nor any interaction, F(8, 112) < 1.5, p > .17, were found. The lack of statistical interaction can be clearly seen by examining Figure 4. A 3 (T2 location) × 5 (T3 location) ANOVA of participant errors reveals no significant main effect for T3, F(4, 28) < 1.3, p > .25, nor a T2 by T3 interaction, F(8, 112) < 1. There were marginally fewer errors when T2 was at the 0 position, F(2, 28) < 3.1, p > .06. As before,

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Figure 4. Experiment 3 mean reaction times for the five T3 locations (–4, –2, 0, 2, 4) when T2 location was –2 (filled dots), 0 (open dots), and +2 (filled triangles). Error bars represent standard error. The distance between each T3 location was approximately 0.88 degrees (see the text for details).

there was no evidence of any speed–accuracy trade-off. The error data appear in the bottom portion of Table 1. The V shaped RT plots found in the previous experiments, and again predicted by the moving-spotlight model, did not occur in Experiment 3. Rather, it appears that attentional resources that are needed to detect the abrupt appearance of an object are less than the minimum amount of attention distributed across the potential target area. Once again, these results are consistent with the activity-distribution model of attention.

GENERAL DISCUSSION The present study was designed to examine the activity-distribution model of LaBerge and his colleagues (LaBerge & Brown, 1986, 1989; LaBerge et al., 1997) using exogenous cues and targets more typically found in studies supporting the moving-spotlight model of attention. To review, Experiment 1 replicated the pattern of results predicted by the activity-distribution model using a version of the basic paradigm of LaBerge and co-workers (e.g., LaBerge et al., 1997, Experiment 1). Experiments 2 and 3 used variations of the basic trial sequence from Experiment 1. In Experiment 2, the difficult letter discrimination task at display T2 was replaced by a single exogenous cue, and in Experiment 3 the letter discrimination at T3 was

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replaced by a single exogenous target. In both experiments, the findings were consistent with the activity-distribution model rather than the moving-spotlight model of attention. In addition to the work of LaBerge and colleagues (LaBerge et al., 1997) and present findings, several other findings point toward converging evidence against a unitary moving beam of attention. For example, Kramer and Hahn (1995) compared participants’ responses to targets and distractors that appeared suddenly or that were created by removing sections of premasks. Participants were presented with two targets separated by two distractors, with the task of indicating whether the two targets were the same or different. Kramer and Hahn found that when the stimuli appeared abruptly, the distractors affected participant response. This did not occur when the abrupt onsets were not used, however, suggesting that attention was allocated to two separate target locations simultaneously. Kramer and Hahn concluded that, at least under some conditions, attention can be allocated to more than one location in the visual field. Whereas such a conclusion violates the basic tenet of the moving-spotlight model (i.e., a unitary beam), it is easily accounted for in the activity-distribution model (i.e., a bimodal distribution of activity). In examining the spatial distribution of attention with exogenous cues, Henderson and Macquistan (1993) presented cues and targets at either four or eight locations in the visual field. Their study resulted in three major findings. First, they found that targets at the cued location were responded to faster, even when compared to uncued targets in the cue visual quadrant. Second, they found visual meridians (the imaginary lines that separate the vertical and horizontal visual fields) do not play a role in the allocation of attention following an exogenous cue. Their third finding, and most relevant to the issue at hand, is that they found that responses to targets were fastest at the cued location and became gradually slower with increasing distance from the cue. Henderson and Macquistan argue that this pattern of results is best accounted for by an attentional gradient across the visual field rather than by the movement of a spotlight of attention. The results of several other studies that show the allocation of attention to non-contiguous regions of space are also easily accounted for with the activity-distribution model. These studies include Baylis and Driver (1989), Castiello and Umiltà (1992), Shaw and Shaw (1977), and Müller and Findlay (1987). However, as Castiello and Umiltà note, some of these studies have been difficult to replicate (e.g., see Berry & Klein, 1993, for a failure to replicate Baylis & Driver) and the findings are open to a variety of interpretations. Despite these problems, there is growing evidence that attention can be allocated to more than one location at a time. It is also worth noting that evidence for the activity-distribution model has been found across a variety of different paradigms. Originally, LaBerge and co-workers (e.g., LaBerge & Brown, 1986, 1989; LaBerge et al., 1997) used a series of difficult letter discriminations to shift the underlying distribution of attention activity. This basic method was adapted in the present study to include either exogenous cues or targets. For example, Henderson and Macquistan (1993) used a variation of the basic exogenous cue target method, whereas Kramer and Hahn (1995), Baylis and Driver (1989), and Castiello and Umiltà (1992) used methods that did not involve the use of cues. Moreover, as noted by Eriksen and Murphy (1987), the studies that initially attempted to determine how the spotlight of attention moved (Remington & Pierce, 1984; Shulman et al., 1979; Tsal, 1983) failed to produce converging results. Thus, although the moving-spotlight model of attention has great intuitive appeal and is widely accepted, the

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activity-distribution model may ultimately prove to be the best explanation for the underlying nature of visual attention.

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