Preparatory Attention: Experiment and Theory

Consciousness and Cognition 9, 396–434 (2000) doi:10.1006/ccog.1999.0429, available online at http://www.idealibrary.com on

Preparatory Attention: Experiment and Theory David LaBerge 1 Simon’s Rock College of Bard, Great Barrington, Massachusetts 01230

Laurent Auclair Universite´ de Savoie, Chambery, France

and Eric Sieroff Universite´ de Paris, Paris, France This study investigated attention to a spatial location using a new spatial preparation task. Participants responded to a target dot presented in the center of a display and ignored a distractor dot presented to the right or left of the center. In an attempt to vary the level of preparatory attention directed to the target, the distractor dot was presented prior to the onset time of the target and the relative frequency of distractor dots to target dots within a block of trials was varied. The results from the first three experiments showed that when instructions induce weak preparatory attention to the target location, response times to a target on target-only trials increase substantially as the percentage of trials containing a distractor increases from 0 to 75%. In Experiments 2 and 3, instructions and display saliency were used to induce strong preparatory attention to the target location, resulting in almost constant response times across distractor percentages. Experiment 4 varied percentage of target trials in the absence of distractors, with the result that response times decreased as target trial percentage increased. Accounts of these data by early ‘‘activity-based’’ and late ‘‘criterion-based’’ attention theories are compared, and the early theory is given a more detailed description within the context of a cognitive neuroscience theory of attention.  2000 Academic Press

Many of the attention tasks used in experiments published over the past several decades were designed to measure the selective aspect of attention during the presentation of a target display (for reviews, see LaBerge, 1995; Pashler, 1998). In a typical selective-attention task, the display contains a target item along with one or more distractor items. For example, a target may be a letter positioned somewhere in a clock-like circle of several letters, or a target may be a green T located in a field of randomly placed red T’s and red and green X’s, or a target may be the center letter in a three-letter display. The purpose of these experiments usually was to determine the effects on attention of distractors, specifically their number, their positions with respect to the target, and their shared attributes with the target. The effects of these variables on attentional operations are presumed to occur during the presentation of the display, whose duration is typically less than 1 s. In a typical conjunction search 1 Address correspondence and reprint requests to David LaBerge, Simon’s Rock College, 84 Alford Road, Great Barrington, MA 01230. Fax: (413) 528-7365. 396 1053-8100/00 $35.00

Copyright  2000 by Academic Press All rights of reproduction in any form reserved.

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task, for example, the duration of attention given to each item is estimated to be in the range of 10–50 ms (Treisman & Sato, 1990). Other attention-related tasks were designed to measure operations of selective attention prior to the presentation of the target display. In these tasks, a cue typically is presented at a specific time interval before the target display with the purpose of directing the observer’s attention to a particular item or location of the upcoming target display. When the cue-target delay itself is of interest, the cue–target delays are varied within a trial block or across trial blocks; typically, response time decreases to a minimum at a 500-ms delay and then slowly increases or remains relatively constant thereafter (Posner, 1978). To measure the effects of endogenous or top-down control of attention in cueing tasks, a symbolic cue is typically presented, e.g., a centrally located arrow pointing to the right or left; this cue is assumed to induce the observer to direct attention to the right or left location where a target object is likely to appear. If the target appears in the uncued location, the response time is longer than when the target appears in the cued location, indicating that attention must be shifted from the cued location to the uncued location in order to process the target. Thus, in these tasks, attention is presumed to be directed to the cued location before the target appears. In order to distinguish attention generated prior to the target display from attention generated at the time of the target display, we use the terms preparatory attention and brief attention respectively. Both aspects are selective, as is a third aspect, maintenance attention (LaBerge, 1995). Maintenance attention refers to attending to an experience for its own sake, so it occurs at the time of the display, as does brief attention. But the typical duration of both preparatory and maintenance is prolonged in contrast to the typically brief duration of attention evoked at the time of a display. Also, it could be said that both preparatory attention and maintenance attention involve expectations: preparatory attention is typically based on the expectation that a particular object will occur in a particular location, and maintenance attention may be accompanied by expectations that a particular experience will continue. All three aspects of attention, brief attention, preparatory attention, and maintenance attention, are assumed to involve the same brain pathways, according to the triangular circuit theory of attention (LaBerge, 1995, 1997). If attention is actively directed to a particular location before the onset of the target display, it is presumably subject to distraction by items occurring prior to the target display, just as attention to a target is subject to distraction by other items occurring during the target display. When distractors occur before target onset, and when distractors are simply expected to occur, they may compete with preparatory attention to an upcoming target, with the result that less attention is allocated to the target. Therefore, distractors can be used as a means of varying the amount of attention directed to a particular target attribute or location, whether that attention is being directed at a location or attribute at the time of the target display or attention is being directed at a location or attribute in the time interval prior to the target display. The purpose of this study was to vary preparatory attention during the time interval prior to the onset of a target display by occasionally presenting distractors during this preparatory period. Three boxes were displayed throughout each trial, and the target was a black square dot which appeared inside the center box. The target ap-

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peared at random times in a 300-ms interval (or, in some conditions, in a 1800-ms interval) which began approximately 1300 ms after the onset of the three-box warning signal. Prior to the onset of the target a distractor dot sometimes appeared in the box located to the left or right of the center box. It was assumed that, during the initial trials of a trial-block, the observer would begin to anticipate (prepare for attentionally) the occurrence of a distractor as well as the occurrence of a target and that the strengths of these anticipations would vary with the percentages of distractor and target trials within a trial block. The main independent variable of the present experiments was the percentage of trials in which a distractor dot appeared in a trial block. The corresponding hypothesis was as follows: If the appearance of distractor dots in a series of trials induces the observer to attend to the location of a distractor box (or distractor boxes), then the greater the percentage of distractor trials the less the attention directed toward the central target box; the less the attention that is directed to the central box during the preparatory interval the longer the response time given to the target dot when it appears. Thus, the response time to the target dot was used as a measure of the amount of preparatory attention generated to the target during the interval prior to the onset of the target display. The response time to the target dot may also be regarded as an indirect measure of the preparatory attention directed to the distractor. Since response time to the target dot was intended to be the indicator of preparatory attention, it was desirable to eliminate other factors which could influence attention to the target and therefore affect the response-time indicator. The main source of other attention-demanding factors were the characteristics of the target display itself. To minimize selective attention effects, no distracting items appeared at the same time as the target dot, and an attempt was made to make the selective discrimination of the target location as easy as possible by separating the three boxes sufficiently to reduce errors and misses to a level below 1%. Plan of the Present Study Four experiments are reported. The first experiment was designed to demonstrate that the change in percentage of distractor trials produces a substantial change in response times to a target, which would support the hypothesis that distractor-trial percentage influences preparatory attention. The first experiment also compares the effects of distractor trials on target response times when distractor trials contain two distractors instead of only one distractor. The second experiment examines the effect of percentage of distractor trials on target response times under weak and strong instructions in an attempt to test conflicting predictions by late and early attention theories and to separate the cueing function of the distractors from their attentioncompeting function. The third experiment attempts to provide independent evidence that the strong instructions of Experiment 2 affect attention operations, and Experiment 4 attempts to show that the amount of preparatory attention can be changed by target probability alone, without any distractors being present. Finally, the conclusions drawn from the results of these experiments are interpreted in the context of the criterion-based and the triangular-circuit activity-based theories of attention.

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EXPERIMENT 1: EFFECT OF DISTRACTOR TRIALS ON THE RESPONSE TIME TO A TARGET

The procedure of this experiment required subjects to detect the presence of a dot in the center box of three boxes displayed in a horizontal line. The displays, which made up a trial, are shown in Fig. 1. The three boxes were displayed continuously throughout a trial, and the onset of the three boxes served as a warning signal. On some percentage of trials a dot appeared in one of the two outside boxes, but the subject was instructed to respond only to the appearance of the dot in the center box. Sometimes no dot appeared on a trial, sometimes a distractor dot was followed by a central target dot, sometimes a distractor dot was followed by no dot, and sometimes the target dot was the only event on a trial. The timed response to the target-only trials was regarded as the measure of main interest in this experiment, and these response times were expected to increase as the percentage of distractor trials increased. The design of the experiment varied the percentage of distractor trials across four levels; 0, 25, 50, and 75%, and measured the effects of these distractor-trial percentages on preparatory attention by observing the time taken to respond to the target. In these four blocks of trials, a target dot appeared in the center box (without a distractor) 50, 37.5, 25, or 12.5% of the time, respectively, while the percentages of

FIG. 1. The stimulus displays presented on a trial of Experiment 1 in which one distractor occurred before the target. Other types of trials included two distractors prior to the target, target-only trials, and trials containing neither target nor distractors.

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no-dot trials were 50, 37.5, 25, or 12.5%, respectively. When a distractor dot occurred on a trial, it was followed by a target dot 50% of the time and followed by no dot 50% of the time. For example, in a 25% distractor-trial block, the distractor appeared alone 12.5% of the time, the distractor was followed by a target 12.5% of the time, the target appeared alone 37.5% of the time, and the no-dot trial occurred 37.5% of the time. Thus, the percentage of trials on which a target dot occurred was 50% across all conditions, so that the overall percentage of trials in which a response occurred was maintained at 50% across all conditions to avoid changes in level of response bias (e.g., LaBerge, Legrand, & Hobbie, 1969). However, this constraint forced the percentage of target-only trials to vary inversely with the percentage of distractor trials, given that some of the distractor trials contained targets. It was decided to include trials on which a target followed a distractor in an attempt to increase the attention-attracting strength of a distractor. When a target follows a distractor with a short delay, the target appears to be a reinforcement for the act of attending to the distractor. Thus, the appearance of a distractor can function as a cue to an upcoming target, and the expectation of a distractor can function as a competitor with the target for preparatory attention. This tentative hypothesis was confirmed by preliminary data which showed stronger distractor trial effects when the distractor sometimes was followed by the target than when the distractor never was followed by the target. This issue is discussed further in the discussion section of Experiment 3 and in the ‘‘General Discussion.’’ The design of this experiment also varied the number of distractors which appeared on distractor trials; in one condition a distractor trial contained one distractor dot, which appeared in one of the two outside boxes; in the other condition a distractor trial contained two distractor dots half of the time (which appeared successively in both outside boxes), and one distractor dot the other half of the time. The target ended a distractor trials half of the time, and the other half of the time the distractor trial ended without a target appearing. Thus, the effects of distractor trials containing one dot could be compared when the one-dot distractor trial occurred along with double-dot distractor trials and when the one-dot distractor trial was the only kind of distractor trial. In order to induce participants to maintain preparatory attention over an extended period of time, the targets and distractors were presented at randomly chosen times within a trial following the onset of the warning signal display. On trials containing one distractor, there were three different delays between the onset of the warning signal and the distractor; when a target followed a distractor there were also three delays between the distractor offset and the target onset. On target-only trials, there were three delays between the onset of the warning signal and the target onset, and these delays were the same as the delays between the warning signal and the target on the distractor trials in which a distractor intervened between the warning signal onset and the target onset. In the condition in which two distractors appeared on a trial, there were three delays between the warning signal and the first distractor, three delays between the first and second distractor, and three delays between the second distractor and the target (on trials in which the target followed a distractor). Thus, in the condition in which distractor trials contained either one or two distractors the target-only trials

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contained six delays, three delays which were relatively short in duration (matching the warning-signal-to-target durations when there was one intervening distractor) and three delays which were relatively long in duration (matching the warning-signalto-target durations when there were two intervening distractors). The two delay classes were called Short and Long, and there were three delay durations within each delay class. Method Participants. The participants were eight undergraduate students enrolled at Simon’s Rock College, and their ages ranged from 17 to 20. They participated on a voluntary basis, and after the experiment they were fully informed of the group results and the implications of these results for our understanding of the attention process. For each participant, informed consent was obtained according to the regulations of the college committee on research. Stimuli. The trial began with the display of three boxes, positioned horizontally, and the three boxes remained until the trial was terminated (see Fig. 1). The size of each box was 4 ⫻ 4 mm, and the size of the black square dot which appeared within a box was 2.5 ⫻ 2.5 mm. The distance between the boxes was 3.5 mm. The approximate viewing distance (eye-to-screen) was 45 cm. The presentation of stimulus displays and the recording of the responses were controlled by an IBM computer; the stimuli were displayed as white figures on the 16-inch black screen of the monitor. The software that controlled stimulus presentations and response recordings was developed in the first author’s laboratories at the University of Minnesota and the University of California, Irvine. Design and procedure. The design contained four main conditions: distractor level (one distractor on a trial vs one or two distractors on a trial), distractor percentage (0, 25, 50, 75%), delay class (Short vs Long), and delay duration (three durations within each delay class). The one-distractor condition contained only the short delay class, while the one-or-two-distractor condition contained a mix of the short and long delay classes. The one-or-two-distractor condition contained both one and two distractor trials in equal proportions. All conditions were given within each of two sessions, and each session took place on separate days within a week of each other. The orders in which the distractor levels were given across the 2 days (1–2, 2–1 and 2–1, 1–2) were balanced across the eight participants. Within each distractor level condition there were four blocks of trials, and each block corresponded to a distractor percentage. The orders in which these percentage-blocks occurred were balanced by a Latin square across the participants. Thus, there were four blocks of trials within each of the two conditions given in each day’s session. Participants were instructed at the beginning of the experiment ‘‘to press the right shift key promptly when a dot appeared in the center box, and do not respond when a dot appears in one of the other boxes.’’ No further instructions were given as conditions of the experiment were changed from trial-block to trial-block. Because participants presumably had to become acquainted with the new block conditions in the first several trials of each block, the first 12 trials of each block were removed in the data analysis. One-distractor condition. Each block of the one-distractor condition contained 48 trials. A (distractor) dot appeared in one of the outside boxes on 0, 12, 24, or 36

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TABLE 1 Frequencies of Trial Types within a Block of Trials Percentage of distractor trials

Target-only Nothing Distractor-only Distractor-then-target

0

25

50

75

24 24 0 0

18 18 6 6

12 12 12 12

6 6 18 18

trials (0, 25, 50, or 75% of the time), and when it appeared it was followed by a center (target) dot 50% of the time and by no dot 50% of the time. The side of the distractor dot was balanced within each block of trials. In these blocks of trials, a distractor dot appeared alone on 0, 6, 12, or 18 trials (0, 12.5, 25, 37.5% of the time), respectively, and it was followed by a target on 0, 6, 12, or 18 trials (0, 12.5, 25, 37.5% of the time), respectively; a target appeared alone on 24, 18, 12, or 6 trials (50, 37.5, 25, or 12.5% of the time), respectively, and the no-dot trials occurred on 24, 18, 12, or 6 trials (50, 37.5, 25, or 12.5% of the time), respectively (see Table 1). Thus, the percentage of trials in which a center dot occurred was 50% across all conditions, so that the overall percentage of trials in which a response occurred was also maintained at 50% across all conditions. However, the percentage of target-only trials varied inversely with the percentage of distractor trials (for reasons previously described). When a distractor appeared on a trial, the time delay between the onset of the warning signal (the appearance of the three-box display) and the onset of the distractor varied randomly at 444, 740, or 1036 ms, and when a target followed the distractor it followed at 740, 592, or 444 ms, respectively. The duration of the distractor dot was 148 ms, so that the total duration from the onset of the warning signal to the onset of the target was either 1332, 1480, or 1628 ms, respectively. When no distractor appeared on a trial (a target-only trial), the time delay between the onset of the warning signal and the onset of the target varied randomly at 1332, 1480, or 1628 ms. Thus, the three time intervals between onsets of the warning signal and the onset of the target (when it occurred) were the same for distractor trials and target-only trials. The intertrial interval was 296 ms, and the response wait time was 592 ms. One-or-two-distractor condition. A block of this condition contained 96 trials (with a rest period after 48 trials) for each of the 25, 50, and 75% distractor blocks and 48 trials for the 0% distractor block. The partitioning of these trials among the trial types (distractor or distractors followed by target, distractor, or distractors followed by no target, target-only, and neither target nor distractor) followed the same percentages as in the one-distractor condition. Half of the trials within a block of this condition contained two distractors, and one distractor dot appeared in one outside box and the other distractor dot appeared in the other outside box. The side of the first

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FIG. 2. Mean response times to the target as a function of distractor-trial percentage on target-only trials in Experiment 1. Data from eight participants.

dot was balanced within a block of trials. The other half of the trials within a block of this condition contained one distractor, which appeared equally often in the two outside boxes. When two distractors appeared on a trial there were three delays, (a) a delay between the warning signal and the first distractor, (b) a delay between the first distractor and the second distractor, and (c) a delay between the second distractor and the target (when it appeared). These duration triplets for the long delay class had the following time values: (a) 1036, 740, and 444 ms; (b) 444, 592, and 740 ms; and (c) 444, 740, and 1036 ms. Since the duration of each of the two distractor dots was 148 ms, the total durations between warning signal onset and target onset were 2220, 2368, and 2516 ms, respectively. When no distractor appeared on a trial, the long durations between the onset of the warning signal and the onset of the target were 2220, 2368, and 2516 ms. For the one-distractor trials (which occurred equally often with the two-distractor trials in this condition) the short durations were 1332, 1480, or 1628 ms, as was the case in the one-distractor condition already described. The time intervals for the two-distractor trials are labeled long delays and the time intervals for the one-distractor trials are labeled short delays for the purpose of analysis. Results The mean response times to targets on target-only trials are shown in Fig. 2, and the mean response times to targets on distractor trials are shown in Fig. 3. The data were based on responses on the trials that followed the first 12 trials of response times from each block for each participant. It was assumed that a participant was becoming acquainted with the percentage characteristics of the block condition within

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FIG. 3. Mean response times to the target as a function of distractor trial percentage on trials in which the target followed one or two distractors in Experiment 1. Legend: 1DS, target following one distractor in the one-distractor condition (short delay); 1&2DS, target following one distractor in the one-or-two-distractor condition (short-delay); 1&2DL, target following the second distractor in the oneor-two-distractor condition (long delay). Data from the same task and from the same eight participants as the data shown in Fig. 2.

the initial 12 trials, so that the remaining trials of a block would then approximate more closely the asymptotic level of response times to the conditions of that block than did the entire set of trials from that block. Two within-subjects ANOVAs of the data in Fig. 2 were carried out, one for the two short-delay curves (one curve from the one-distractor condition and one curve from the two-distractor condition) and the other for the short- and long-delay curves of the two-distractor condition. Target-only trials. The ANOVA of the two short-delay curves in Fig. 2 was a 4 ⫻ 2 ⫻ 3 ⫻ 2 factorial design involving percentages of distractor trials, distractor condition (one vs one and two distractors on a trial), delay duration, and session. The only significant main effect was the percentage of distractor trials, F(3, 21) ⫽ 12.65, p ⬍ .001, and the only significant interaction effect was delay duration by session, F(2, 14) ⫽ 5.74, p ⫽ .015. The delay duration by session interaction was produced by an effect of delay during the first session (309, 292, 261 ms for delay durations of 1332, 1480, and 1628 ms, respectively), and no effect of delay duration during the second session (297, 296, 283 ms for the same delay durations, respectively). The ANOVA of the short- and long-delay curves of responses on target-only trials of the one-or-two-distractor condition in Fig. 2 was a 4 ⫻ 2 ⫻ 3 ⫻ 2 factorial design involving percentages of distractor trials, delay class (short vs long), delay duration, and session. The only significant main effect was percentage of distractor trials, F(3, 21) ⫽ 16.78, p ⬍ .001, and the only interaction effect was delay duration by session, F(2, 14) ⫽ 3.99, p ⫽ .042. The delay duration by session interaction was produced by an effect of delay during the first session (306, 296, and 295 ms for delay durations of 1332, 1480, and 1628 ms, respectively), and no effect of delay duration during the second session (286, 290, and 280 ms for the same delay durations, respectively).

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Target-following-distractor trials. The ANOVA of the two short-delay curves in Fig. 3 (one short-delay curve for the distractor trials in the one-distractor condition and the other short-delay curve for the one-distractor trials in the one-or-two distractor condition) was a 3 ⫻ 2 ⫻ 3 ⫻ 2 within-subjects factorial design involving percentages of distractor trials, distractor conditions (one vs one and two distractors), delay durations, and sessions. The only significant main effect was distractor condition, F(1, 7) ⫽ 10.31, p ⫽ .015, and there were no significant interactions. The ANOVA of the short- and long-delay curves of the two-distractor condition in Fig. 3 involved a 3 ⫻ 2 ⫻ 3 ⫻ 2 factorial design involving percentage of distractor trials, delay class (short vs long), delay duration, and session. The only significant main effect was delay class, F(1, 7) ⫽ 39.51, p ⬍ .001, and the only significant interaction was delay class by delay duration, F(2, 14) ⫽ 9.50, p ⫽ .002. The delay class by delay duration interaction was produced by an effect of delay duration for the long delay class (237, 242, and 258 ms for delay durations of 2220, 2368, and 2516 ms, respectively), and no effect of delay duration for the short delay class (281, 280, and 279 ms for delay durations of 1332, 1480, and 1628 ms, respectively). For all the curves shown in Figs. 2 and 3, errors and misses were less than 1% (for the one-distractor condition, the percentages of errors and misses were 0.7 and 0.5%, respectively, and for the two-distractor condition the percentages of errors and misses were 0.3 and 0.3%, respectively). Discussion The main finding of Experiment 1 is that percentage of distractor trials had a significant effect on response time to the target on target-only trials (shown in Fig. 2). The strength of the total effect appears to be quite substantial, since the amount of RT change (approximately 45 ms) is well over 10% of the lowest RT value (269 ms). The frequencies of errors and misses were negligible in this experiment, which suggests that the process of selecting the target location is independent of distractor trial percentage. Apparently adding trials containing two distractor to trials containing one distractor does not produce a detectable increase in the slope of the function relating percentage of distractor trials to response time. A comparison of the two short-delay curves of Fig. 2 shows a small difference in overall level of response time, but this difference is not supported by statistical analysis. The addition of more than two distractors on a distractor trial may produce an increase in the level of the curve relating response time to distractor trial percentage, but there is no indication in these data that presenting more than one distractor on a distractor trial will produce an appreciable increase in the slope of the one-distractor curve. In contrast to the data of Fig. 2, the data in Fig. 3 show no significant effect of distractor trial percentage on response time for target-following-distractor trials. The occurrence of a distractor just prior to a target within a trial appears to cancel the between-trial effect of distractor trial percentage shown in Fig. 2. Because the target follows a distractor 50% of the time across all distractor trial percentages (and no dot stimulus follows a distractor the other 50% of the time), the occurrence of a distractor predicts the immanent appearance of the target equally often across the

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three distractor trial percentages. Furthermore, the delays between the distractor and the target within a trial were shorter than the delays between the warning signal and the target on target-only trials, so that preparatory activity for the target may be higher for these data, resulting in faster response times. When the percentage of distractor trials is varied in the design of Experiment 1, the percentage of target-only trials does not remain constant, but varies in an inverse manner. Specifically, when the distractor trial percentage is 0%, the target trial percentage is 50%, and when the distractor trial percentage is 75%, the target trial percentage is 12.5%. Therefore, the obtained change in response times, shown in Fig. 2, is possibly produced by an unknown combination of the two manipulations: the frequency of distractor trials and the frequency of target trials. A direct way to assess the contribution of the change in target trial percentage to the data in Fig. 2 is to carry out an experiment in which target trial percentage is varied without the presence of distractor events. This estimation of effects of target trial percentage alone on target response times is postponed to Experiment 4, while Experiments 2 and 3 attempt to provide additional data that will be helpful in giving an adequate theoretical account of the results of Experiment 1. EXPERIMENT 2: EFFECT OF INSTRUCTIONS AND DISTRACTOR TRIALS ON THE RESPONSE TIME TO A TARGET

The main finding of Experiment 1, shown in Fig. 2, is that the percentage of distractor trials affects the response time to a target on trials in which the target appears alone. This finding appears to support the hypothesis that when distractors have appeared on recent trials, they affect attentional preparations for the target in the interval of time just prior to its next onset. Experiment 2 addresses the question of where the attentional preparations take place in the processing system. Late attention theories typically assume that attentional preparations take place in the decision stage of processing, where signals and noise are accumulated and produce a response when the accumulation of signals reaches a specific criterion level (e.g., Mulligan & Shaw, 1981; Rouder & Ratcliff, 1998; Sperling & Dosher, 1986; Pashler, 1998). Early attention theories typically assume that the signal can be selectively amplified more than noise at the sensory stage of processing, before information reaches the response decision stage (e.g., Brunia, 1999; Hawkins et al. 1990; Heinze et al., 1994; LaBerge, 1997; Mangun & Hillyard, 1991; Woldorff et al., 1993). The term preparatory attention specifies that the operations which selectively amplify the stimulus signal are in existence prior to the onset of the target stimulus. Both theories provide straightforward accounts of the increase in response time to the target on target-only trials, shown in Fig. 2. According to a late criterion theory, increasing distractor trials increases the noise that accompanies a target dot and therefore more information needs to be accumulated at the time of the target display to assure that the target signal had indeed occurred. An early theory of attention assumes that the signals arising from the target stimulus are modified before they reach a criterion mechanism that produces a decision. The modification of the target signals is produced by the level of preparatory attention that is directed to the target and

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distractor locations prior to and extending into the time that the target display occurs. The relative amounts of preparatory attention directed to the target and distractor are determined by the memory of the relative frequency of recent target and distractor trials. An increase in the relative frequency of distractor trials reduces the amount of preparatory attention given to the center location on a given trial and, consequently, there is less enhancement of the incoming target signal when it arrives. Therefore, preparatory attention increases the signal-to-noise ratio of the stimulus input (Brunia, 1999; LaBerge, 1997). When attention is directed to a particular location before the stimulus appears, the preparatory attentional activity existing at the site of attentional expression potentiates the activity arriving there from the sensory receptors when the stimulus appears. For simplicity, we may interpret this potentiation as the combining or adding of sensory activity to the activity already produced by preparatory attention. Thus, it is the existence of prior attentional activity at the target and distractor sites which in effect modulates the signal-to-noise ratio corresponding to target or distractor stimuli. The particular proportion of recent distractor and target trials generates corresponding levels of expectancy for the target and distractor, which in turn produce corresponding levels of preparatory attention. For example, in the 75%-distractor-trial condition, the subject is likely to expect a distractor to occur before a target on most trials, and therefore the subject is likely to attend in a preparatory manner to the distractor locations following the onset of the warning signal. Then when a target appears (without a distractor appearing first) there is less attentional activity at the target site to augment the incoming activity from the target stimulus. As a consequence, the response time to the target (on target-only trials) under the 75%-distractor condition is long relative to the 50%-, 25%-, and 0%-distractor-trial conditions. The amount of attentional activity in location sites of the target and distractor prior to the onset of the target display is assumed not to be an all-or-none affair, but rather a continuously variable modulation process. When the target is selected to receive preparatory attention on a particular trial, the level of activity of attention may be varied from low to high. For example, while carrying a full bowl of soup across the room, one continuously anticipates (prepares to observe) any movement of the soup toward the edge of the bowl, and the intensity of this preparatory attention increases with the perceived value of the carpet upon which one is walking. This early attention account of preparatory attention can be described in terms of specific brain structures by adding a few new assumptions to the triangular circuit theory of attention. Fig. 9 shows the major modules of control, amplification, and expression of attention, joined by a triangular set of connections. A more detailed description of the operations of the components of the modified triangular circuit theory is given in the ‘‘General Discussion.’’ The present early attentional account of the RT curves shown in Fig. 2 involves the description of attentional operations both before and after the onset of the target display. The operations before the target display onset involve preparatory attention, and the operations after the target display involve both preparatory and brief attention. The initiation of preparatory attention occurs when the three-box warning

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signal is presented. Preparatory attention is distributed across the three boxes according to operations in the selective and modulatory control modules, which are located in frontal areas of the cortex. The target and distractor locations are assumed to be mapped in these control sites, and recent target and distractor trial frequencies are stored in the target and distractor columns within the selective control module. These records in the selective control module form the basis of expectations, and subjects can access this information directly if they were simply asked to predict whether a target or distractor would appear first on a given trial, regardless of whether they attend to the target or distractor location in a preparatory or anticipatory manner. The selective control module registers not only the recent target and distractor events, but also registers the effects of instructions concerning what is to be selectively attended. In the procedure of Experiment 1, it is assumed that the instructions to respond to the dot only when it appears in the center box added some amount of activation to the target sites in the selection module. In order for the expectancies in the selection module to produce preparatory attention, the selection control must activate corresponding target and distractor sites in the modulatory control module. The modulatory control, in turn, directly activates the target and distractor sites in the posterior cortex where the target signals arrive and are potentiated by these already-active sites. Thus, when the warning signal appears, the sites of attentional expression to location in the posterior cortex begin to receive activation from the frontal cortical modulation site. This activation occurs in both target and distractor sites, according to the relative frequencies with which targets and distractors have recently been observed. When the target stimulus appears, activation from the sensory receptors enters the target and distractor sites, but, owing to the large sensory difference between the target and distractor in the present task, the level of activity entering the target site always substantially exceeds the level of activity entering the distractor site, so that errors and misses remain near zero. Hence, at target onset, the target site activity will almost always exceed the distractor site activity, even if the level of preparatory attention directed to a distractor site exceeds the preparatory attention directed to a target site (as is likely in the 75%-distractor-trial condition). As a result, the rates of errors and misses remain virtually at zero, while the effects of recent target and distractor trials modulate the activity level of the target site before the target stimulus occurs. When activity from the target stimulus arrives at the target site, the existing attentional activity combines with the sensory activity and the increased activity is sent on to a criterion mechanism. Thus, the potentiation of target sensory activity produced by preparatory attention at the (early) posterior cortical site is decreased as the percentage of recent distractor trials is increased. In an attempt to generate opposing predictions by the late and early theories, Experiment 2 introduces a new instruction for the preparatory attention task used in Experiment 1. The new instruction asks the participant to attend to the central box. In the old instruction, the participant was instructed to respond only to the central dot and not to respond to a dot that appeared to the right or left of center. The new instruction was assumed to produce strong attention to the central target location, and the old instruction is assumed to produce weak attention to the central location.

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What changes are predicted by the two theories for the curve that relates response time to the percentage of distractor trials when attentional instructions are changed from weak to strong? If a late theory mechanism increases attention by lowering the criterion, then the overall response time of the curve should decrease; that is, the curve shown in Fig. 2 should be translated downward. The slope of the curve could be reduced slightly, owing to a possible floor effect, but since the effects of distractor trials are still present, they should continue to increase the criterion in the manner in which they increased the criterion to produce the slope of the RT curve in shown in Fig. 2. Also, the late theory predicts that errors should increase if the overall response-time curve decreases sufficiently because a greatly lowered criterion will allow low proportions of target elements present in the distractor stimulus to trigger a response. The early attention prediction, based on the triangular-circuit theory, assumes that instructions to attend to the center location produces a ‘‘selective’’ effect in the modulatory control, as well as adds substantial activity to the target site within the selective module. Instead of distributing its effects across all three boxes, the modulatory control is narrowed to only the center box. Thus, the same target and distractor expectancies, registered in the selective control, give rise to modulatory control over only the center location when the strong attention instructions are given and give rise to modulatory control over all three locations when the weak attention instructions are given. The theoretical structure which determines which box location sites in the selective control will influence box-location sites in the modulatory control is the motivationbased basal ganglia (see Fig. 10). Briefly stated, the assumption is that the instruction to attend only to the center box creates a basal ganglia-related state in which only the center box is ‘‘of interest’’; in contrast, the instruction to respond only when the dot appears in the center box creates a basal ganglia-related state in which all three boxes are ‘‘of interest.’’ The operation of the basal ganglia output upon the circuit connecting the selective and modulatory controls is described in more detail in the ‘‘General Discussion’’ section. Given these additional assumptions to the triangular circuit theory, it is predicted that instructions to attend to the center box will not only add substantial activity to the target site in the selective module, but will also induce the modulatory control to activate only the location site of the target. Therefore, the level of target activation in the modulatory control will be high and virtually constant across all distractor trial percentages. In view of these considerations, the early, activity-based, theory predicts a flat RT curve for target-only trials of the strong instruction condition, while the late, criterionbased, theory predicts a rising RT curve. Both theories predict that the overall curve for the strong attention instruction will lie below the curve of the weak attention instruction. A second purpose of using a strong attention condition was to attempt to separate a possible time-cueing function of the distractor from a possible attention-competition function. If the effects of the distractor trial percentage can be virtually eliminated on target-only trials while the response time of the target on target-afterdistractor remains below the response time of the target on target only trials, then

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it would appear that the two functions of the distractor have been experimentally separated. Method Participants. The participants were eight undergraduate students at the Universite´ de Savoie, at Chambery, France. There were five females and three males whose ages ranged from 22 to 27 years with a mean of 24.4 years. Participation was voluntary, and they were treated according to the guidelines of the Universite´ de Savoie. Stimuli. The trial began with the display of three boxes, positioned horizontally within a 24 ⫻ 24 mm frame, and this display remained until the trial was terminated (see Fig. 1). The size of each box was 5 ⫻ 5 mm, and the size of the black square dot which appeared within a box was 3.5 ⫻ 3.5 mm. The distance between the boxes was 4.5 mm. The approximate viewing distance (eye-to-screen) was 50 cm. The presentation of displays and recording of responses were controlled by a Macintosh Quadra 800 (AppleT) computer. The stimuli were displayed on a 16-inch Apple monitor with a 832 ⫻ 624 pixel resolution. The software which controlled the presentation of stimulus displays was PsychLabT. Design and procedure. The design contained three main conditions: instruction (weak vs strong), distractor trial percentage (0, 25, 50, and 75%), and duration of the delay between the warning signal onset and the target onset (1800, 2000, and 2200 ms). When a distractor occurred on a trial, there was only one distractor. Therefore the way a block of trials in each distractor percentage was constructed was the same as the way blocks of trials were constructed in the one-distractor condition of Experiment 1. The instructions were carefully worded. For the weak-instruction condition, participants were told at the beginning of the experiment ‘‘to press the right shift key of the computer keyboard when a black square appears in the center square, and respond to the dot only when it appears in the center square.’’ For the strong-instruction condition, participants were told at the beginning of the experiment ‘‘to fixate your attention on the center square and to press the response key only when a black square appeared in the center square’’; and these instructions were repeated before each distractor percentage condition. Each subject ran the strong condition 1 month after they ran the weak condition. Each block of distractor conditions contained 60 trials. The orders in which the distractor percentage conditions occurred were balanced by a Digram-balanced latin square (Keppel, 1991, pp. 338–369). The order of distractor conditions for each subject was reversed between the two instruction conditions. The delay durations between the warning signal onset and the distractor onset were varied randomly among the values of 600, 1000, and 1400 ms. On the trials in which a target followed a distractor, the intervals between the distractor and target were 1000, 800, and 600 ms, respectively. Since the duration of the distractor was 200 ms, the time delays between the warning signal and the target onset were 1800, 2000, and 2200 ms, not only on trials in which the target followed a distractor, but also on trials in which a target appeared without a distractor intervening between the warning signal and the target. The intertrial interval was 600 ms.

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Results Target-only trials. The mean response time to targets on target-only trials are shown in Fig. 4 for the two instruction conditions. The first 12 response-time trials were removed from the data, as in Experiment 1. The ANOVA of response times on target-only trials was a 2 ⫻ 4 ⫻ 3 factorial design involving instructions (weak and strong), distractor trial percentages (0, 25, 50, and 75%), and delay between the warning signal and target (1800, 2000, and 2200 ms). There were two significant main effects: instructions, F(1, 7) ⫽ 11.16, p ⫽ .001, and distractor percentage, F(3, 21) ⫽ 8.51, p ⫽ .001. The overall level of mean response time for the strong instructions was approximately 60 ms lower than that of the weak instructions. However, at the 0% distractor trials, the difference in mean response times was not significant, F(1, 7) ⫽ 0.71, p ⫽ .42, suggesting that there was no appreciable practice effect from the weak instruction session to the strong instruction session. The only significant interaction was between instructions and distractor trial percentage, F(3, 21) ⫽ 12.40, p ⫽ .001. A planned comparison showed that this interac-

FIG. 4. Mean response times to the target as a function of distractor-trial percentage and instructions on target-only trials in Experiment 2. In the weak-attention condition, participants were instructed to respond only to the dot when it appeared in the center location; in the strong-attention condition, participants were instructed to attend strongly to the center location at all times and respond to the dot when it appeared there. Data from eight participants.

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tion was produced by a significant effect of distractor trial percentage under the weak instructions, F(3, 21) ⫽ 12.88, p ⫽ .00005, and no effect of distractor trial percentage under the strong instruction, F(3, 21) ⫽ 1.78, p ⫽ .18. Moreover, the analysis of the weak instruction data indicated that mean response time increased linearly with distractor trial percentage, F(1, 7) ⫽ 22.05, p ⫽ .002, with a residual of F(1, 21) ⫽ 0.755, p ⫽ .39. In order to evaluate the near-zero slope of the strong attention curve of Fig. 4, each participant’s four response time values, corresponding to the 0-, 25-, 50-, and 75%-distractor-trial percentages, were converted to a slope value for each instruction condition, by fitting a straight line to the four values by the least-squares method (e.g., LaBerge & Brown, 1986, Appendix). The mean slope for the strong condition was 0.21 ms and for the weak condition was 1.17 ms (based on the unit of 1%). For purposes of evaluating by eye the mean slopes of the data shown in Fig. 4, the strong and weak slopes could be converted, based on a unit of 25 percentage points, to 5.25 for the strong condition and 29.25 for the weak condition. The ANOVA of these slope values revealed a significant effect only for instructions, F(1, 7) ⫽ 11.69, p ⫽ .001. Using the error-variance estimates of the ANOVA, the slope of the strong instruction curve of Fig. 4 was tested against zero, t (7) ⫽ 1.25, p ⫽ .25, and the slope of the weak instruction curve was tested against zero, t(7) ⫽ 4.70, p ⫽ .002. The standard error of slope for the strong instruction was 0.17 and for the strong condition was 0.25 (based on a unit of 1%). Thus confidence intervals could be set for the estimated mean slope of the strong instruction condition. The range of two sigmas below and above the obtained mean slope of 0.21 is ⫺0.12 to 0.54 ms per percentage point or from ⫺3 to 13.5 ms per 25 percentage points. Therefore, the slope data, based on eight subjects, supports the mean responsetime data in showing that the slope of the strong attention curve is much lower than the slope of the weak attention curve. The slope data goes further and shows that the mean slope of the strong attention curve is ‘‘close’’ to zero. The only evidence of a departure from zero slope occurred when the distractor trial condition changed from 50 to 75%. An ad hoc test of this response-time change yielded a t(1, 7) ⫽ 2.41, p ⫽ .045. Errors and misses. For the target-only trials of the strong-instructions condition, the mean percentage of errors was 0.03% and the mean percentage of misses was 0.28%. For the weak-instructions condition, the mean percentage of errors was 0.05% and the mean percentage of misses was 0.16%. Target-following-distractor trials. The mean response times on trials in which the target followed a distractor on a trial are shown in Fig. 5. The ANOVA of these data was a 2 ⫻ 3 ⫻ 3 factorial design, involving instructions (weak and strong), distractor trial percentage (25, 50, and 75%), and delay (1800, 2000, and 2200 ms). The only significant effect was delay, F(2, 14) ⫽ 11.24, p ⫽ .001. The effect of instructions approached significance, F(1, 7) ⫽ 3.72, p ⫽ .095; a sign test yielded a p ⫽ .077, based on the finding that seven of eight subjects showed faster responses under the strong condition. The mean response times of the strong condition of the target-after-distractor trials and for the target-alone trials (i.e., the lower curves in Figs. 4 and 5) were averaged

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FIG. 5. Mean response times to the target as a function of distractor-trial percentage and instructions on trials in which the target followed a distractor in Experiment 2. Data from the same task and from the same eight participants as the data shown in Fig. 4.

across the 25-, 50-, and 75%-distractor-trial conditions for each participant. A sign test of the difference yielded a p ⬍ .01 because all eight participants showed a lower mean response time on target-after-distractor trials compared to target-only trials. Errors and misses. For the target-after-distractor trials of the strong-instructions condition, the mean percentage of errors was 0.01% and the mean percentage of misses was 0.04%. For the weak-instructions condition, the mean percentage of errors was 0.07% and the mean percentage of misses was 0.75%. Discussion The strong-attention RT curve, shown in Fig. 4, shows a near-zero slope, as predicted by the present version of the early attention theory. However, the connection between the participants’ subjective interpretation of the verbal instructions and their attention to the center box may not seem sufficiently reliable to some readers for supporting the conclusion that the strong-instruction condition actually produced a state in which the center box was the sole location ‘‘of interest.’’ Therefore, another experiment was carried out in an attempt to provide independent evidence for the obtained difference in response-time slopes (shown in Fig. 4), using a manipulation of stimulus displays that is well-known to influence selective attention. EXPERIMENT 3: EFFECT OF DISPLAY SALIENCE AND DISTRACTOR TRIALS ON THE RESPONSE TIME TO A TARGET

The purpose of this experiment was to attempt a replication of the contrasting slopes of the two main response-time curves of Experiment 2 (shown in Fig. 4) by changing the characteristics of the display of three boxes, while keeping constant the weak instructions used in Experiments 1 and 2. A box in the stimulus displays was

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modified by making the top and bottom lines thicker by adding two lines above the top line and two lines below the bottom line. For the strong-attention condition, only the center box was given the extra lines, and for the weak-attention condition, all three boxes were given the extra lines. In order to emphasize the thicker top and bottom lines, the first 800 ms of a trial showed the unmodified boxes, and then the modified boxes appeared. Thus, the highlighting of the center box alone produced a feature singleton, which attracts attention to its location when it ‘‘pops-out’’ 800 ms after the onset of the warning signal (Treisman & Gelade, 1980; Yantis, 1993). Method Participants. The participants were eight undergraduate students at Simon’s Rock College, none of whom had been in previous experiments of this kind. There were five males and three females who volunteered, and informed consent was obtained according to the regulations of the college committee on research. Their ages ranged from 17 to 20. Stimuli. The stimuli were the same as used in Experiment 2, with the exception that two lines were added to the top and bottom of specific boxes. For the strongattention condition, only the center box had an additional pair of lines added above and below the standard box, and for the weak-attention condition, all three boxes had an addition pair of lines added above and below the standard box. For each condition the modified outlines of the boxes appeared after the three thin boxes had been displayed for 800 ms. The presentation of displays and recording of responses were controlled by the same devices described in Experiment 1. Design and procedure. The design and procedure was the same as in Experiment 2, except for three features: (1) the instructions were the same for both conditions and were the same instructions as were used in Experiment 1 and in the weak-instruction condition of Experiment 2: ‘‘Press the right shift key of the computer keyboard when a black square appears in the center square, and respond to the dot only when it appears in the center square’’; (2) the order of running the two conditions was balanced across participants and the participants ran the two conditions on different days; and (3) each distractor trial condition contained 48 trials. Results Target-only trials. The mean response times to targets on target-only trials are shown in Fig. 6 for the two display conditions. The first 12 response-time trials were removed from the data, as in Experiments 1 and 2. The ANOVA was a 2 ⫻ 4 ⫻ 3 ⫻ 2 design involving conditions (strong and weak), distractor trial percentages (0, 25, 50, and 75%), delay between the warning signal and target (1800, 2000, and 2200 ms), and days (1 and 2). The only significant effects were the main effect of distractor trial percentage, F(3, 18) ⫽ 5.04, p ⫽ .01, and the distractor trial percentage by condition interaction, F(3, 18) ⫽ 6.83, p ⫽ .003. Errors and misses. For the weak-attention condition, the mean percentage of errors was 1.0% and the mean percentage of misses was 0.1%. For the strong-attention

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FIG. 6. Mean response times to the target as a function of distractor-trial percentage and display condition on target-only trials in Experiment 3. In the strong-attention condition the center box had thicker lines on the top and bottom; in the weak-attention condition all three boxes had thicker lines on the top and bottom. Data from eight participants.

condition the mean percentage of errors was 0.3% and the mean percentage of misses was 1.0%. Target-following-distractor trials. The mean response times on trials in which the target followed a distractor on a trial are shown in Fig. 7 for the two display conditions. The ANOVA of these data was a 2 ⫻ 3 ⫻ 3 ⫻ 2 factorial design, involving

FIG. 7. Mean response times to the target as a function of distractor-trial percentage and display condition on trials in which the target followed a distractor in Experiment 3. Data from the same task and from the same eight participants as the data shown in Fig. 6.

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conditions (strong and weak), distractor trial percentage (25, 50, and 75 ms), delay (1800, 2000, and 2200 ms), and days (1 and 2). The only significant effect was condition ⫻ delay, F(2, 14) ⫽ 10.54, p ⫽.002. The mean response times of the strong condition of the target-after-distractor trials and for the target-alone trials (i.e., the lower curve in Figs. 6 and 7) were averaged across the 25-, 50-, and 75%-distractor-trial conditions for each participant. A sign test of the difference yielded a p ⬍ .01, because all eight participants showed a lower mean response time on target-after-distractor trials compared to target-only trials. Errors and misses. For the target-after-distractor trials of the strong attention condition, the mean percentage errors was 0.3%, and the mean percentage of misses was 1.0%. The slopes of the curves shown in Fig. 6, estimated by the least-squares method (LaBerge & Brown, 1986, Appendix), were 0.16 ms for the strong condition and 0.62 ms for the weak condition. The slope estimate for the strong condition of this experiment is slightly less than the slope estimate for the strong condition of Experiment 2, which was 0.21 ms. The slope estimate for the weak condition of this experiment is close to the 0.59-ms slope of the one-distractor curve of Experiment 1, owing to the fact that the participants in this experiment and Experiment 1 were from the same college-student population. Discussion The pattern of results of Experiment 3 is similar to that of Experiment 2 and therefore supports the assumption that the strong instructions of Experiment 2 produced stronger preparatory attention to the center target location than the weak instructions (particularly over the distractor-trial percentages of 25, 50, and 75%). Experiment 2 was designed (1) to determine whether the pattern of results of Experiment 1 could be explained by a decision criterion operating at the time that the target was presented or by changes in the level of activity existing at the location sites of the target and distractor existing at the time the target was presented and (2) to determine that the distractor functions not only as a cue that the target is about to appear (on targetafter-distractor trials), but also that the distractor functions as a competitor for attention during the preparatory interval prior to the target onset on target-only trials. Early-attention ‘‘activity-based’’ account. The pairs of RT curves from the targetonly trials shown in Figs. 4 and 6 appear to confirm the predictions derived from the early theory described at the beginning of the report of Experiment 2. Both the instruction to attend to the center box in Experiment 2 and the saliency or ‘‘popout’’ of the center box in Experiment 3 presumably make the center box an ‘‘object of interest,’’ while the instruction to respond to the dot when it appears in the center box in Experiment 2 and the equal saliency of all three boxes in Experiment 3 presumably make all three boxes ‘‘objects of interest.’’ Moreover, the pair of strong attention conditions in these two experiments are assumed to add considerable activation to the selective control module compared to the activation added under weak-attention conditions. As a consequence the activity levels of the target and distractor sites in the modulatory control are very different in the strong- and weak-attention conditions. In the strong-attention condition the output from the basal ganglia inhibits the projec-

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tion of activity from the distractor site in the selection control to the distractor site in the modulation control and releases inhibition on the projection of the now higher activity from the target site in the selection control to the target site in the modulation control. The activity from the modulatory control is sent to the posterior sites of attentional expression, where it preactivates target and distractor sites, which in turn interact with the incoming target activity to elevate the signal-to-noise ratio in the activity subsequently projected to a criterion mechanism. The response times generated by the criterion mechanism are thus strongly influenced by the level of preactivation in the target and distractor sites which intervene between the sensory receptors and the criterion mechanism in this early attention account of the data in Figs. 4 and 6. Late-attention ‘‘criterion-based’’ account. The traditional assumption of late theories of attention is that changes in attention in tasks like the one in the present experiment are produced by changing the criterion for how much sensory input from a display must be accumulated at the decision stage before triggering a response. The criterion assumption easily predicts the target-only data from Experiment 1 (Fig. 2): the reasoning is that an increase in the percentage of distractor trials produces more noise (more distractor signals whenever a target dot appears) and, therefore, to avoid committing misses when a target appears (produced by not receiving enough target signals in a given amount of time), more information must be accumulated to trigger a response. But if more information is accumulated each time a dot appears, then when a dot appears in an outside box, the targetlike signals produced by the distractor dot now have a greater likelihood of accumulating to the criterion and triggering an error response. It could be assumed that errors and misses in Experiment 1 were near zero because the target stimulus itself has a very high signal-to-noise ratio, owing to the large spatial separation between the target and distractor, and this ratio is only slightly decreased by the noise produced by the increases in distractor trial percentage. It can be shown mathematically that criterion models predict that large changes in mean response times can take place in response to increases in noise, while the probability of errors remains near zero. Two large classes of criterion models are counter models and random-walk models (for a review see Luce, 1986). In counter models, the onset of a stimulus produces a series of signal and noise elements, and these elements enter two kinds of counters, one for signals and the other for noise. The first counter to accumulate the criterion count generates a decision corresponding to its type of counter. In random-walk models, the series of elements results in the movement of a point toward a signal boundary or a noise boundary (the distance of the boundaries from the start point represent the criteria). Formally, the random walk model can be conceived as an interactive counter model, in which the addition of one element to one counter produces the subtraction of one element from the other counter. Both the counter models and random-walk models, in their most general and simple forms, have been compared with respect to two predictions (LaBerge, 1994) which are relevant to the present description of a criterion account of the data of Experiments 2 and 3. When the signal is large relative to noise, the probability of a correct response remains near 1.00 for appropriately large criterion values (see Figs. 7 and 8 of LaBerge, 1994). When the criterion value changes, the resulting mean reaction time

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can increase substantially if the time for each element to enter a counter or move the random walk one step is appropriately large (see Fig. 10 of LaBerge, 1994). Thus, both counter and random-walk versions of criterion models can predict the obtained slopes of the RT curves under weak instructions, in which increase in distractor noise produces an increase in mean RT while the probability of correct responding remains near 1.00. In Experiments 2 and 3, when attention to the center location is increased by the strong-attention conditions, the increase in attention to the center location should be produced by a change in the response criterion. The large decreases in slope of the strong-attention curve compared to the weak-attention curve shown in Figs. 4 and 6 would seem to indicate that the strong instructions must have lowered considerably the criterion settings associated with each distractor trial percentage. According to a criterion theory, the presence of distractor noise should still induce the participant to adjust the criterion upward as distractor noise increases with the increase in distractor trial percentage. As the criterion level decreases, a given change in noise level will have a greater effect on response time. Therefore, if one assumed that the amount of criterion change was constant as distractor trial percentage increased across the distractor trial percentages (i.e., from 0, 25, 50, to 75%), then one would predict that the slope of the target-only curve would actually increase from the weak- to strongattention conditions. The influence of a ‘‘floor effect’’ on the almost-horizontal slopes of the strong-attention curves in Figs. 4 and 6 can be ruled out because the response times in the strong-attention curves of Figs. 5 and 7 are consistently and significantly lower than the strong-attention curves of Figs. 4 and 6 by approximately 20 ms. A ‘‘noise-suppression’’ account. The distractor inhibition mechanism in the present version of the early theory has a parallel in a version of attention theories in which it is assumed that the criterion is combined with a ‘‘noise-reduction’’ mechanism that can exclude channels that produce noise (Pashler, 1998). On this assumption, it could be assumed that increases in preparatory attention to the central target location in the present tasks takes place by filtering or attenuating activity arising from dots at the outside locations. In this way distractor signals can be suppressed before they reach the decision stage, which is another way of saying that the signal-to-noise ratio of the stimulus is increased prior to the criterion. Under strong attention conditions, the noise-suppressor is set at or near maximum; under weak conditions, the noisesuppressor allows some distractor signals to reach the decision stage, so that when the distractor trial percentage increases there is an increase in noise, which induces an increase in the criterion level, producing longer response times. Although both the ‘‘noise-suppression’’ mechanism and the distractor-inhibition mechanism of the present early theory operate on the distractor activity, the distractor inhibition occurs in the control modules of the frontal cortex, but the output from these control modules to the posterior cortical sites of attentional expression produces target enhancement, not distractor inhibition (all long-range cortico-cortical neurons are excitatory). Therefore, the immediate effect on activity from an incoming target stimulus is to increase the signal part of the input, not to decrease or suppress the noise part of the input. It may be noted that some versions of the early attention theory assume that early selection operates not by enhancement of the target but by suppression or attenuation of the distractor (e.g., Moran & Desimone, 1985; Treis-

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man, 1988). A third version of the early theory could assume that selection occurs both by target enhancement and by distractor suppression. Clearly, combining a noise-suppression mechanism with a criterion mechanism will account for the RT data from target-only trials shown in Figs. 4 and 6. Strictly speaking, such a theory would be classified as an early-late theory because the noisesuppression mechanism operates before the criterion. However, it is not clear how the noise-suppression mechanism works, nor where it may be located in brain structures. Also, it is not clear what mechanism produces the changes in criterion necessary to generate the increases in RT in the weak attention curves of Figs. 4 and 6. In the early attention theory described here, the circuitry and brain location of the distractor inhibition mechanism is specified, and a description is given of how it operates in both the weak- and strong-attention conditions. And since the positive slope of the weak-attention curves of Experiments 1, 2, and 3 can be derived without changing the criterion values as distractor trial percentage changes, the criterion mechanism is not crucial for accounting for the general pattern of results of these experiments. However, a criterion mechanism is deemed important for generating theoretical accounts of the details of response time distributions. Cueing and competitive functions of the distractor. Turning to the response-time data from trials in which the target followed a distractor (Figs. 5 and 7), it appears that both weak- and strong-attention conditions produce curves with slopes close to zero. These near-zero slopes appear to be consistent with the near-zero slopes obtained for the target-following-distractor data in Experiment 1. Since a near-zero slope was also obtained for target-only trials under strong attention instructions, it would seem that the occurrence of a distractor in the target-following-distractor trials acts as a cue, inducing the subject to temporarily attend strongly to the target location, regardless of the distractor trial percentage. The distractor-target intervals in these experiments are relatively short: 400–700 ms in Experiment 1 and 600–1000 ms in Experiments 2 and 3. As in the case of the target-only trials, strong attention overshadows the effects of recent distractor-trial percentages. The level of this momentary stronger preparatory attention induced by a distractor is expected to vary across the weak- and strong-attention conditions because it adds to the already high strength of attention generated in all of the trials of the strong-attention condition. Therefore, this assumption could account for the difference in overall response-time levels of the target-only curves of Figs. 4 and 6 and the target-after-distractor curves in Figs. 5 and 7. It could also account for the differences in the overall response-time levels of the curves in Fig. 3 if it is assumed that the second distractor (long delay) produces stronger attention than the first distractor (short delay) in the one-or-two distractor conditions and that the first distractor in the one-or-two distractor condition produces less attention than the only distractor in the one-distractor condition. Thus, the relatively flat and lower response times of the target-after-distractor data appear to support the hypothesis that, in these tasks, a distractor acts as a cue for an upcoming target. It is conjectured that the strength of the cueing function of the distractor should be reduced by increasing the delay between the distractor and target on distractor trials. This particular hypothesis requires further research to be adequately tested.

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If a distractor functions as a strong cue, as it seems to be the case in the present experiments, then it should possess strong attention-attraction properties; that is, it should also function as a distractor and compete for attention with the target during the preparatory interval. This hypothesis is supported by the large effects of distractor-trial percentage in the weak-attention conditions of the present experiments. But in Experiments 2 and 3, the strong attention conditions seem to virtually confine attention to the central target location and thereby block the attention-competition function of the outside dots. However, under the strong attention conditions, the cueing function of the outside dots appears to remain, since the target-after-distractor response times of Figs. 5 and 7 are significantly below the corresponding target-only response times of Figs. 4 and 6. Thus, the present data appear to support the hypothesis that the distractor dots function both as cues and competitors for preparatory attention in these experiments. Future research is intended to provide a more systematic inquiry into the hypothesized dual function of the distractor cue in this task. EXPERIMENT 4: EFFECT OF TARGET-TRIAL PERCENTAGE ON RESPONSE TIME TO A TARGET

Experiment 4 attempts to assess the effect of target frequency alone on the time to detect a visual target. In Experiments 1, 2, and 3, target-trial percentage varied inversely with distractor-trial percentage, and therefore this factor could contribute to the increase in response times with distractor-trial percentage in the curves shown in Fig. 2 and in the weak-attention conditions of Figs. 4 and 6. As in the first three experiments, the experimental procedure required subjects to detect the presence of a dot in the center box of three horizontally positioned boxes. However, during trials of this experiment no distractors were presented. The three boxes were displayed continuously throughout a trial. The onset of the three boxes again served as the warning signal, and participants were instructed to press the right shift key when the dot appeared in the center box. The trials in which a dot appeared in the center box varied in values of 100, 75, 50, and 12.5%, and three randomly selected delay intervals separated the onset of the warning signal from the onset of the target. In the design of Experiment 4, the probability of a response was not constant across conditions, but increased directly with the target percentage. Therefore, obtained differences in response times across the four percentages of target trials may reflect response bias as well as the perceptual bias for the target location. Method Participants. The participants were the eight undergraduate students at Simon’s Rock College who had participated in Experiment 1. Participation was voluntary and they were fully informed of the group results and the implications of these results for our understanding of the attention process. Informed consent was obtained for each participant according to the regulations of the college committee on research. Stimuli. The stimuli and viewing conditions were the same as in Experiment 1. Design and procedure. The design contained two conditions: target percentage (100, 75, 50, and 12.5%), and the same delay durations as in the one-distractor condition of Experiment 1 (1332, 1480, and 1628 ms). Each participant served in one

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session, which contained four blocks of trials, one for each target percentage. Each block contained 48 trials, and the order of blocks was balanced across the 8 participants by two different 4 ⫻ 4 Latin squares. In all other respects the procedure was the same as the procedure of Experiment 1. Results and Discussion Shown in Fig. 6 are the mean response times to targets as a function of the percentage of target trials (vs no-dot trials) within a trial-block. The data were adjusted by the removal of the first 12 trials from each block, as was done in the other experiments. The ANOVA of the data shown in Fig. 6 was a 4 ⫻ 3 factorial design involving percentage of target trials and delay duration. The only significant main effect was percentage of target trials, F(3, 42) ⫽ 21.48, p ⬍ .001. The mean response times across delay durations were quite similar: 245, 239, and 243 ms for the three delay durations of 1332, 1480, and 1628 ms, respectively. The interaction between percentage of target trials and delay duration was not significant. Errors and misses were less than 1% (the relative frequencies of error and misses were .001 and .002, respectively). The main finding of Experiment 4 is that percentage of target trials by itself has a clear effect on response time. The amount of the response time change between target trial percentages of 50 and 12.5%, shown in Fig. 8, is approximately 20 ms, and the slope of this segment of the curve is 0.27 ms. In comparison, the slope of the one-distractor curve of Experiment 1 across the same range of target-trial percentages (i.e., the entire curve in Fig. 2) is 0.59. An ANOVA of these slopes, involving

FIG. 8. Mean response time to the target as a function of target-trial percentage in Experiment 4. Data from eight participants.

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the two variables of Experiment (1 vs 4) and delay (three durations) yielded an F(1, 14) ⫽ 4.81, p ⬍ .05, and no other significant effects. Thus, there is a significant distractor component of the slope of the one-distractor curve of Experiment 1. Therefore, the slope of the one-distractor curve of Fig. 2, and by implication the slopes of the other response-time curves of this study produced by weak attention conditions, is not produced solely by changes in relative frequencies of distractor events as the distractor-trial percentage changes. The response time increases in these curves is apparently being produced also by changes in the relative frequency of target events. GENERAL DISCUSSION

Experiments 1, 2, and 3 show that, under relatively weak instructions to attend to a target location, response times to a target on trials containing only a target increase substantially as a function of the percentage of trials in which a distractor recently appeared. Experiment 4 shows that response time to a target decreases, but at a smaller rate, as a function of the percentage of trials in which the target recently appeared. The combined results suggest that, in the weak-attention conditions of Experiments 1, 2, and 3, the response times to targets in target-only trials are influenced by both the percentage of recent distractor trials and the percentage of recent target trials. Therefore, these findings appear to support the hypothesis that when distractors and targets have appeared on recent trials, they affect attentional preparations for a target in the trial that is currently in progress. Experiments 2 and 3 increased the strength of attention to the central target location to see if the changes in response time would follow predictions from a criterion-based decision (late) theory of attention or the activity-based (early) theory of attention. The criterion-based theory assumed that the level of the decision criterion would be lower when attention was increased to the center target location, but distractor trial effects would still remain. Therefore, the predicted RT curve for target-only trials under the strong attention condition should be translated downward from the RT curve under the weak-attention condition. The activity-based theory of attention predicted that the strong attention condition would increase target activity and suppress distractor activity in control sites of attention with the result that the target sites in the expression sites of attention would be highly activated regardless of the distractor trial percentage. Therefore the predicted RT curve for target-only trials under the strong attention should be flat and lower than the RT curve under the weak-attention condition. The results favored the activity-based early theory of attention and were unfavorable to the criterion-based late theory of attention. A second mechanism of attention, the ‘‘noise-reduction’’ mechanism (Pashler, 1998) was considered. This mechanism operates by selectively suppressing the information from the distractor ‘‘channels.’’ When the noise-suppression mechanism is combined with the criterion mechanism, an adequate account can be given of the target-only data of both the weak and strong attention conditions obtained in Experiments 2 and 3 (Figs. 4 and 6). However, it is not clear how the noise-suppression mechanism is evoked, nor where in the cognitive system it resides. In contrast, the present triangular circuit theory places the distractor inhibition

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mechanism in the circuitry connecting the basal ganglia to the modulatory control, and a plausible description is given of the circuitry based on known principles of connectivity between the basal ganglia, the thalamus, and frontal cortical areas. Modifications in the Triangular-Circuit Theory Suggested by the Present Data While the triangular circuit theory of attention (LaBerge, 1995, 1997, 1998, 1999) emphasizes the role of early attentional processing, it does not rule out the existence of a late criterion mechanism whose mode of operation influences the form of response-time distributions. Rather, the early theory assumes that attention changes the signal-to-noise ratio of the stimulus input before the effects of the stimulus input reach the criterion stage. The present early theory assumes that a criterion mechanism follows the events described by the diagram in Fig. 9 (i.e., the events following the top-down operation of the triangular circuit that produces the expression of spatial attention in the parietal area). Mathematical models of the criterion process can connect theory with response-time data in a manner which provides quantitative predictions (for reviews of models, see Luce, 1986 and Townsend & Ashby, 1983). Criterion models based on the accumulations of target and distractor signals are described by LaBerge (1962, 1994) and Smith and Vickers (1988). A criterion model of the

FIG. 9. Triangular-circuit theory of visual attention to a spatial location. Stimulus input through area V1 and the superior colliculus produce an expression of orientation in the parietal area, which activates frontal cortical areas of attentional control (shaded rectangles indicate columns which code for target and distractors). Frontal areas of control return activation to the parietal area via two routes within a triangular circuit: one direct and the other indirect through a thalamic nucleus, which produces an expression of attention in that parietal area. The selective control selects the location in the parietal area to which attention will be directed, and the modulatory control varies the intensity of attentional activity directed to that selected location. Connections between the selective control and modulatory control areas are also produced through two routes within a triangular circuit: one direct and the other indirect through a thalamic nucleus.

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accumulation of activity differences between a target and a distractor (based on the thalamocortical circuit) that generates responses directly from the expression of attention to location (or to stimulus attributes) is described by LaBerge, Carlson, and Williams (1997). Details of the relationships between these models and the present data are beyond the scope of the present paper. The main change in the triangular circuit theory suggested by the present experiments is the division of attentional control into two submodules: a selection module and a modulatory module. The schematic diagram in Fig. 9 shows theoretical representations, in terms of brain structures, of the expression, enhancement, and control of spatial attention to the central box (target) and to the outside boxes (distractors) during a trial of the distractor task in the weak-attention conditions of Experiments 1, 2, and 3. Brain areas of top-down control are assumed to be part of systems of working memory (e.g., Baddeley, 1995; Goldman-Rakic, 1987), in which two kinds of processing are prominent: storage of information in highly accessible form over short periods of time and executive control, which governs encoding, retrieval, and commands for the expression of attention in other areas of the brain. The direct connections between frontal (including premotor and prefrontal), pulvinar, and parietal areas have been confirmed in several anatomical tracing studies (for a review see Selemon & Goldman-Rakic, 1988). The connections within the frontal cortex appear plausible, given the known interconnectivity with the prefrontal and premotor areas and between these cortical areas and underlying thalamic nuclei (e.g., Selemon & Goldman-Rakic, 1988; Jones, 1985; Fuster, 1989). In Fig. 9, the attentional command component of working memory is represented by two related subareas of control, labeled selective control and modulatory control. Both components of control are assumed to be activated when the three boxes appear as a warning signal and when a dot appears in one of the boxes during a trial. Within each area of control is a cluster of cortical columns which represent the target and a cluster of cortical columns which represent a distractor. It should be noted that in distributed cortical coding of similar locations and similar objects there is considerable overlap of cortical columns which are activated by both types of stimuli. Therefore, when the descriptive phrase ‘‘cluster of columns’’ is used here, there is no necessary implication that the column clusters are disjoint. The columns within the modulatory and selective control areas are assumed to store the cumulative record of recent stimulus events. Previous studies have shown that locations attended to on recent trials of an experiment affect subsequent response times to those locations. LaBerge and Brown (1986) varied the range of locations (along a horizontal line) in which stimuli were presented and found that as range of locations became more narrow, the response times to a given stimulus within that range decreased. Presumably, when stimulus locations are clustered in close proximity, the effects of recent trials mutually strengthen the residual activity at neighboring locations more than at remote locations, which in turn contributes to greater preparatory attention for those locations. In a recent study by Carlson (1998), stimuli were presented to the left and right of a center fixation point with different frequencies, and when these locations were tested with probe stimuli, the response times of the probe stimuli showed lower response times to the more frequent location. Thus, these studies showed that a particular stimulus location produced different response times

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depending on the frequency with which that location or closely proximate locations had been presented on recent trials. Similarly, in the present experiments, the occurrences of target and distractor events are assumed to be stored in working memory, and these memories induce preparatory attention directed to their locations when the warning signal begins a trial. When the stimulus display (in the form of a cue or an appropriate warning signal) activates spatial locations, all columns of the selective control module are activated, but the columns storing the more frequent recent events are activated more strongly (as indicated by the darker shading within the target control columns in Fig. 9). In the selective control area, the activity in the target column is produced mainly by the memory of the instructions to observe and respond to the central target and less strongly by the memory of recent target and distractor events. The low percentages of errors and misses obtained in the present experiments are consistent with this assumption. In the modulatory control area, the initial activity levels of the target and distractor columns are produced mainly by projections from the selective control, where the frequencies of recent target and distractor trials are stored. After the onset of a cue or warning signal produces the initial levels of activity in the selective and modulatory control areas, the selective control area activates the area of modulatory control via the triangular circuit involving a nucleus of the thalamus, which serves the frontal area. The ventrolateral nucleus serves the premotor area, which is a likely site of modulatory control, and the mediodorsal nucleus serves the prefrontal area, which is a likely site of selective control (for PET evidence of the involvement of these thalamic nuclei in a preparatory attention task, see Liotti, Fox, & LaBerge, 1994). As the target columns in the modulatory control increase their activity, they undergo interference from activity in the distractor columns. This interference may occur both in the cortico-cortical connection and in the corticothalamocortical connection of the triangular circuit. The connection between the selective control columns and the modulatory control columns involving the thalamus is shown in Fig. 10. The structure of this circuit is the standard thalamocortical circuit, which includes the inhibitory neurons of the reticular nucleus of the thalamus. The operation of this circuit has been simulated (LaBerge, Carter, & Brown, 1992), and the stimulation results show that a small initial difference in the input firing rates of the target and distractor pathways can be transformed into a large difference in firing rates at the cortical columns, favoring the target over the distractor (a sample of the simulation is shown in Fig. 5 of LaBerge, 1999). Thus, when the selective control columns activate the modulatory control columns, a small difference between the activity levels in the selective control columns will be amplified as it is passed through the thalamocortical circuit, which provides input to the columns of the modulatory control. The process of amplifying a small difference between target and distractor sites involves both an increase in activity of the initially higher activity site and a decrease in activity of the initially lower activity site. To account for the increase in response time to the target-only trials produced by the increase in percentage of distractor trials, it is assumed that the modulatory control activates preparatory attentional activity in parietal sites where incoming target activity arrives. Preparatory attentional activity at the target sites is combined with the incoming target activity to increase the signal-to-noise ratio of the target stimulus.

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As the level of preparatory activity at the distractor site is decreased and the level of preparatory activity at the target site is increased (by decreasing distractor trial percentage), the signal-to-noise ratio of the information entering the decision criterion mechanism is increased, with the result that mean response time decreases. Basal Ganglia and Motivational Influences The modulatory control area is influenced not only by activity sent from the selective control area, but also by activity arising from the basal ganglia, which is a brain structure believed to be crucial for the communication of motivational states to the frontal cortex (via the thalamus). The basal ganglia maintain tonic inhibition of the thalamocortical circuits serving the frontal cortical areas, and this enduring inhibition prevents an augmentation of activity in frontal cortical columns, thereby preventing unwarranted actions from being initiated. The increase in activation of a particular cluster of frontal columns is made possible when the inhibitory fibers from the basal ganglia themselves are inhibited (for a description of the circuits by which the basal ganglia are assumed to control the control areas in the frontal cortex see LaBerge, 1998). This disinhibition is presumed to occur when the perceived object is of interest to the individual; in other words, when active areas in the posterior cortex (representing the attribute or location of the object) activate appropriate circuits within the basal ganglia, perceptions of the object are associated with motivational states. Under the weak-attention conditions of the present experiments, basal ganglia tonic inhibition of the thalamocortical input to the target and distractor columns of modulatory control (and from other brain areas to the selective control) is assumed to be reduced, which represents a cognitive state in which all three boxes are ‘‘of interest’’ (see Fig. 10). By blocking basal ganglia inhibition of the thalamocortical loops serving the modulatory control, the inputs from both target and distractor columns of the selective control are free to interact. The interaction has already been described as one which takes in small differences in input activity levels and delivers large differences in output activity levels. However, under the strong attention condition, the object ‘‘of interest’’ is the target box, and the perception of the target box in posterior cortex directly activates a particular patch of neurons in the basal ganglia. As a result, the basal ganglia releases tonic inhibition of the target pathway between the selective and modulatory controls, but maintains inhibition of the distractor pathways. Therefore, only the target site within the modulatory control is activated, and the level of this activation is higher than the level under weak-attention conditions, owing to the additional target activation added to the selective control and to the absence of competition from distractor activity while the thalamocortical circuit performs its enhancement operation. Because the stored effects of recent occurrences of distractors in the selective control are prevented from being communicated to the modulatory control, the targetonly curve in the strong attention condition (Figs. 4 and 6) is predicted to show a zero slope. A generalization that is suggested by these considerations of narrowing attention to an object’s location is that it can cancel other influences on attention, for example, the influences of recent trial events (as in the present study) or the presence of nearby distractors in the target display (LaBerge et al. 1991).

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Pathways of Visual Orienting The relationship of preparatory attention to orienting is shown in Fig. 9. There are two main pathways leading from the primary visual cortex (V1) to the parietal cortex that serve orienting; one pathway contains synapses in intermediate cortical areas, and the other pathway contains synapses in the superior colliculus (which projects its fibers to the parietal area via synapses in the pulvinar nucleus of the thalamus). Another pathway of orienting (not shown here) connects the retina directly with the superior colliculus. These pathways are assumed to produce bottom-up activation of the parietal area; for example, when the three boxes of the present experiments are presented as the warning signal, three locations are activated in the parietal spatial area. The activations are typically produced by abrupt onsets of stimuli, and the activity levels decay rapidly. These patterns of activations in the parietal area produced from the ‘‘bottom-up’’ direction are regarded here as expressions of orientation, not expressions of attention (LaBerge, 1999). When activity in the three location sites of the parietal area are projected to the frontal cortical areas, they activate corresponding locations in the modulatory and selective control areas. Subsequently, the selective control site induces the modulatory control site to return activation to only one location (e.g., the center box) of the parietal area, which receives additional and more prolonged activation, while activity at the other locations decays. This activation in the single selected location is considered here to be an expression of attention in the parietal area because it involves the triangular circuit, which augments the activity in the particular parietal site to a sufficiently high level and sustains the activity for a moderate (i.e., nonbrief) duration of time. Thus, although many noncontiguous locations can express orientation at the same time, only one noncontiguous location appears to be able to express attention at a given time, particularly when the attentional intensity is high. Integration of the Triangular Circuit with the Theory of the Spread of Preparatory Attention When preparatory attention is directed to only one particular location by the selective control and augmented to a high level by the modulatory control, activation is assumed to spread to neighboring locations, with the activity level decreasing in intensity as distance increases from the attended location (LaBerge & Brown, 1989; LaBerge, 1995; LaBerge et al., 1997). The momentary distribution of preparatory attention at its highest level of intensity (just prior to the onset of an expected target at the attended location) is assumed to resemble back-to-back exponential distributions, with a small plateau at the peak whose width is the size of the attended area. The spread of this intensity distribution has been measured by the response times of probe stimuli and found to resemble a V-curve (LaBerge & Brown, 1986, 1989; LaBerge et al., 1997). Although the intensity at the central peak of the activity distribution decreases rapidly following a shift of attention to other locations, during the time it is at a high intensity, preparatory attention is moderately intense in locations adjacent to the attended location. Thus, it could be said that, for a brief duration of time, attention is expressed at more than one location at the same time.

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When distractors and targets appear in many different and overlapping locations, then traces of this activity produce high levels of activity in modulatory columns that represent all of these locations, which may exist in all four quadrants of the visual field. If a target is presented along with a distractor, regardless of the distance between them, the activity in both target and distractor columns quickly increases to a higher level. The pattern of activities in these columns is sent to the selective and modulatory controls, where the pattern of activity across these columns changes, as the selective control target and distractor columns induce the modulatory control to increase its target columns activity and to decrease its distractor column activity (a control map of location in one frontal hemisphere contains all quadrants of the visual field, e.g., Funahashi, Bruce, & Goldman-Rakic, 1989). The resulting changes of activity in the modulatory control columns are then sent back to the target columns of the parietal areas. Here, the target columns continue to maintain the high level of activity which was produced at the onset of the stimuli, while the activity in the distractor column decays to a new lower level controlled by the lower level of activity in the modulatory distractor columns. If recordings were made of a cell in each of these parietal columns, the time course of cell activations would show an initial increase in activity of both target and distractor cells, followed by a decrease in activity of distractor cells, while the target column cells remained at the same level. This time pattern of target and distractor activity in a selective attention task is the signature of a selection-by-suppression mechanism (LaBerge, 1999). Theoretical Accounts of Selection by Suppression in the Attention Literature The division of attentional control into modulatory and selective components provides a new way of accounting for data in attention experiments which show selection by suppression of distractors (e.g., Cepeda, Cave, Bichot, & Kim, 1998; Chelazzi, Miller, Duncan, & Desimone, 1993; Moran & Desimone, 1985). The general pattern of results from these experiments indicates that the expression of attention to a particular target object is produced mainly by a reduction in activity at locations corresponding to the distractor object or objects and not mainly by the increase in activity at locations corresponding to the target object. One hypothesis accounts for this pattern of results by assuming that local circuits within the cortical areas of attentional expression enable the active target site to inhibit activity at distractor sites. According to the present account, the main inhibitory processing in these selective attention tasks which show selection by suppression of distractor sites occurs in the frontal control areas, not in the local circuits of posterior cortical areas where attention is expressed. In a frontal map, widely separated location sites in the visual field are close enough (Funahashi, Bruce, & Goldman-Rakic, 1989) to be interconnected through the lateral inhibitory fibers of the reticular nucleus of the thalamus. If the activity is initially at a high level in the distractor and target columns of the frontal modulatory control area, then the modulatory activity for the target column is maintained, while activity in the distractor columns is suppressed. Then, activity initially sent from distractor sites in the frontal area to the distractor sites in the posterior cortical areas simply decays when the target display occurs, while the activity initially

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FIG. 10 Diagram of the major elements of the standard thalamo-cortical circuit connecting the thalamic neurons with columns of the frontal cortex. Relative activity levels within clusters of columns corresponding to the target location (T) and the distractor location (D) are represented by the shaded rectangles. The inputs to these columns of modulatory control arise from (1) the current activity levels within corresponding columns in the selective control area (see Fig. 9) and (2) the reduction of tonic inhibitory activity in fibers arising from the basal ganglia.

sent from target sites in the frontal area to the target sites in the posterior cortical areas remains constant. In this way the pattern of activity in the posterior cortical sites (parietal in the case of location-based attention and occipitotemporal sites in the case of object-based attention) of target and distractors would show a pure selection-by-suppression pattern. This account can be described in more detail with the help of the theoretical diagrams shown in Figs. 9 and 10. When a series of trials contains stimuli at target and at distractor locations, the effects of attending to these stimuli are stored in the corresponding columns in the selective and modulatory control area. Then, when a stimulus display [a warning signal, or cue, or a target plus distractor(s)] activates the spatial pathways of the brain, the target and distractor columns in the modulatory and selective control areas increase their activation to a level which depends upon their recent frequency of occurrence. When the target stimulus occurs, the activity in the target columns in the selective control area increases and both target and distractor

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columns activate the columns in the modulatory control area, which sends high activation to both distractors and target sites in the posterior cortex. When the target appears, the existing high activity in both target and distractor columns of the modulatory control changes. The appearance of the target adds considerable activity to the target site in the selective control, and then the thalamocortical circuit connecting the selective control to the modulatory control suppresses the activity of the modulatory distractor columns without producing a further increase in the activity of the target columns. As this process develops over time following the target onset, the target and distractor columns in the modulatory control send their activities to target and distractor sites in the posterior cortex. The level of activity in target sites of modulatory and posterior cortical areas remains approximately constant, while the level of activity in the distractor site of the posterior cortex begins to decay because there is less activity arriving from the distractor site in the modulatory control. Thus, at the onset of a target display, the predicted pattern of activation over time in the posterior cortical sites of attention expression will first show an increase in both distractor and target columns (from a base level) produced by the warning signal (or cue, or targetdistractor display), and then, when the frontal control areas are activated and return activation to the posterior sites, the activation in the posterior sites will continue to increase for both distractor and target columns until the activity in the distractor columns of the modulatory control area begins to decrease. At that time, the distractor activity in the posterior columns will begin to decay, while the target activity remains at its initial high level. This is the general pattern of target and distractor activity over time shown by several cellular recording studies of attentional selection (e.g., Chelazzi et al., 1993). Thus, the inhibitory suppression of distractor activity during selective attention, according to the present account, can take place mainly in the frontal areas of the brain instead of mainly in the posterior areas. The decrease in neural activity at posterior cortical distractor sites is assumed here to represent decay of the activity projected to it from frontal areas, not inhibition by local corticol sources. One structure, proposed here, which contains the kind of circuitry which would produce inhibition of distractor site activity in the frontal control areas is the thalamocortical circuit, illustrated schematically in Fig. 10. Other circuit structures which may perform the same function may lie in the frontal cortical columns themselves and may be activated both by the cortico-cortical inputs and the thalamocortical inputs. Not all selective attention tasks in the literature show the expression of attention by suppression of target activity. Some attention studies show attentional selection in which enhancement of the target dominates suppression of the distractor (e.g., Maunsell, 1995; Spitzer, Desimone, & Moran, 1988). According to the present theory, selection by increase in target site activity within the modulatory and selective control areas will occur when the initial activity levels in the target and distractor sites in these areas is not high. This can come about when the discrimination of the target is difficult, when the distractor is not presented frequently (or is absent) in a block of trials, or when the display of the target does not contain features which strongly activate distractor sites. In the Spitzer, Desimone, and Moran (1988) study, only one stimulus was given at a time (e.g., a green bar), so that on target trials, the distractor representation in the selective control area was not highly activated. When

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the target was made harder to discriminate, activity at the target site increased. In the Maunsell study, the target and distractors were well separated, so that there was little selective interference between target and distractor representations in the selective control area. In contrast to these procedures, the procedures which typically produce selection by suppression often appear to depend upon selective interference between the target and distractors presented together in a display. Negative priming. The assumption, made by the triangular circuit theory, that recent target and distractor trials leave their traces in frontal cortical columns would appear to provide the basis of an account of negative priming. The negative priming effect (e.g., Tipper, MacQueen, & Brehaut, 1988) is commonly described as the increase in response time to a target item on a given trial when that item was a distractor on the previous trial. The account follows the same lines of reasoning as the account of the distractor trial effect already described in this section, except that the property of the target and distractor that is attended to in the present task is location, while the property of the targets and distractors responded to in typical negative priming experiments is an attribute of the stimuli, such as color or shape. When a dot appears in a distractor location over a recent series of trials, the response time to that dot in a target location (on a target-only trial) increases. The top-down sources of attentional control accumulate a record of recent appearances of distractor occurrences (and target occurrences as well), and when a new trial begins, these sources produce attentional activation of both targets and distractors as a function of their accumulated records. Thus, each trial begins with an attentional bias toward potential distractors and targets, and attention generated during the target display is added to this bias to determine how fast the target item will be processed. Selective and modulatory attention. The variations of the experimental task described and tested here appear to measure the intensity of preparatory attention to a specific location in visual space while attention is sustained over time durations of approximately 1 to 3 s. Under weak attention conditions, the intensity of preparatory attention apparently was varied by changing the relative frequency of distractors and targets (in Experiments 1, 2, and 3) and by changing the relative frequency of targets to no-targets (in the target-only task of Experiment 4). Selective attention was apparently so easy in both tasks that errors and misses were virtually absent, suggesting that selective control of attention did not systematically change when modulatory control is changed. Therefore, the present tasks appear to provide a measure of preparatory attention that separates the effects of modulatory attention from selective attention. Selective attention is assumed to influence the duration of attention by determining where attention is directed or to what attention is directed. While attention is directed to a location or object, the intensity of attention can change, if time is provided for activity in modulatory control sites to be changed. Low attentional intensities, represented by low levels of activity in cortical columns of attentional expression (e.g., in cortical areas representing locations, objects, or thoughts) can be produced quickly after attentional shifts to a new location or new object of thought (as in visual search or associative thinking), so that the attentional ‘‘dwell time’’ on a location or thought need be only brief. In contrast, high attentional intensities, represented by high activity levels in cortical columns of attentional expression, are not achieved

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in fractions of a second, but require seconds to develop. Hence, high intensities of cortical activation are not expected during typical search tasks or typical rapid thinking, in which the dwell time of attention on any one item is a fraction of a second. Longer durations necessary to the production of high attentional intensity are more typically found in preparation tasks but even here the intensity level may not be high unless the nature of the task requires it, for example, by displaying the target very briefly following a long preparatory interval (e.g., LaBerge & Brown, 1989; LaBerge & Buchsbaum, 1990; LaBerge, Carlson, Williams, & Bunney, 1997; Liotti et al., 1994) or by motivating the participant appropriately (e.g., the strong instruction condition of Experiment 2). Thus, selective control is assumed to operate quickly (in milliseconds) because columns are presumed to function at low intensities and therefore take less time to reach effective levels; this allows more shifts of attention per unit of time; in contrast, modulatory control is assumed to operate relatively slowly (in seconds) because columns must take time to develop moderate to high intensities; this allows fewer shifts of attention per unit of time. The brain pathways involved in sustaining attention at moderate and high levels during preparatory attention are assumed to be the same pathways involved in sustaining attention at these levels in maintenance attention, in which cortical activity is continued for its own sake and not for the explicit purpose of responding to an expected immanent event. In particular, during maintenance attention, selective control is assumed to be crucial in determining what and how long particular cortical columns will be activated, and modulatory control is assumed to be crucial in determining how intense the activity will be. Application of the Present Tasks to Early Diagnosis of Frontal Deficits If the control of attention is located in frontal areas, then neural damage in this area should affect the ability of the patient to resist the effects of distractors. If recent distractor events have a greater effect on a patient’s ability to attend to the center location of the present task, then a larger slope is expected for the target-only response times as a function of distractor trial percentage. Because the weak attention task appears to be sensitive to distractor effects, this task may show greater-than-normal slopes for individuals who are in early stages as well as in late stages of a frontal disorder. ACKNOWLEDGMENTS The author is grateful to the students at Simon’s Rock College and at the Universite´ de Savoie for volunteering to participate in the experiments of this study and to Dr. Anne O’Dwyer for assistance with accessing the computer-based statistical analyses of data of Experiments 1, 3, and 4. Dr. Janice Lawry provided helpful discussions of several issues treated in this article.

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