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Observing behavior topography in delayed matching to multiple samples.

One topic of continuing interest in analyses of stimulus control concerns the range, breadth, or number of stimuli that can exert control simultaneously. This question has been addressed in such diverse areas as, for example, breadth of attention in animal cognition (e.g., Maki & Leuin, 1972); the effects of task complexity (number of stimuli) on reaction times in aging populations (e.g., Baron & Menich, 1985); and stimulus overselectivity, an atypically restricted breadth of stimulus control related to learning problems of some individuals with developmental disabilities (e.g., Dube & McIlvane, 1997; Lovaas, Koegel, & Schreibman, 1979; Stromer, McIlvane, Dube, & Mackay, 1993).

Experimental analyses of this topic have sometimes employed a delayed matching-to-sample (DMTS) procedure with multiple sample stimuli. This procedure presents a series of matching-to-sample trials in which two or more sample stimuli are displayed on each trial. After a sample observation period, the samples disappear from the display and an array of single comparison stimuli that includes one of the samples is presented. Selecting the former sample stimulus is the correct response. From trial to trial, the subject can not predict which of the sample stimuli will appear as a comparison, and thus high accuracy indicates that the subject has satisfied the behavioral requirements for stimulus control by all samples on every trial.

One question that arises in multiple-sample DMTS concerns the relation between DMTS accuracy and the subject's observing behavior, a necessary prerequisite for stimulus control (Dinsmoor, 1985). Eye-tracking technology provides a straightforward means to address this question. The typical eye-tracking apparatus uses a video camera to monitor eye movements and the subject's observing behavior is determined by comparing eye orientation with the known locations of experimental stimuli. Eye tracking has been used to examine a wide range of topics in psychology; examples include research on cognitive theories of attention (e.g., Hyona, Radach, & Deubel, 2003), eye movements in reading (e.g., Rayner, 1993), language acquisition in children (Trueswell, Sekerina, Hill, & Logrip, 1999), and response to social situations in autism (Klin, Jones, Schultz, Volkmar, & Cohen, 2002). In behavior-analytic studies, eye tracking has been used to examine operant control of observing behavior (Schroeder & Holland, 1968a, 1968b, 1969), eye movements in relation to stimulus control in simple discrimination (e.g., Schroeder, 1969a), transfer of stimulus control (e.g., Schroeder, 1969b, 1997), observing topographies in programmed instruction (Doran & Holland, 1971), and observing failures in stimulus overselectivity (Dube et al., 2003).

The present study examined observing behavior topographies in relation to task complexity in multiple-sample DMTS. Two levels of complexity were arranged by presenting two or four sample stimuli per trial. Observing behavior topography was evaluated by eye tracking for all subjects before and after task complexity increased. For subjects whose initial accuracy scores were intermediate with four samples per trial, observing behavior was evaluated a third time, after additional practice to high accuracy levels. Data analyses asked if there were characteristics of observing sample or comparison stimuli that were related to task complexity or task accuracy. The dependent variables included number and duration of observations, and whether all potentially relevant stimuli were consistently observed.

Method

Subjects, Setting, and Apparatus

Subjects were 4 adults with no known clinical condition, 21 to 39 years old, recruited through personal contacts. Experimental sessions were conducted in a 4- x 2.5-m room. On one side of the room was a chair for the subject and a small table with a computer and color monitor with a touch-sensitive screen. This computer was used to display stimuli to the subject. On the other side of the room were chairs for two experimenters and a table with the eye-tracking apparatus. During sessions, a curtain was drawn across the room to separate the subject from the experimenters and eye-tracking apparatus.

The eye-tracking apparatus consisted of a RK-426PC Pupil/Corneal Reflection Tracking System, a RK520PC Autocalibration System, and ISCAN Miniature Head-Mounted Eye Imaging and Line-of-sight Scene Imaging Systems (ISCAN Inc., Burlington, MA). These systems were integrated with a Pentium computer running ISCAN's Point of Regard Data Acquisition and Fixation Analysis software. Miniature video cameras mounted on a headband produced images of the subject's eye and central portion of the subject's field of view. The apparatus performed on-line image analysis and produced a real-time video image of the environment from the subject's perspective with a superimposed cursor indicating the location of the subject's visual gaze (see Dube et al., 2003 for additional apparatus details). Vertical interval time code (VITC) was added to the video signal, and the composite video image was recorded on a videotape cassette.

Matching-to-Sample Tasks

Stimuli were black abstract forms, approximately 1.25 cm square, displayed on a white background (for examples, see Dube & McIlvane, 1997). The stimuli for each trial were drawn at random, without replacement, from a pool of 180 different forms. If the pool of stimuli was exhausted before the session ended, stimuli for subsequent trials were randomly re-drawn from the pool with the restriction that correct comparison stimuli from previous trials were not used.

Trials began when one, two, or four sample stimuli appeared in the center of the screen. Two samples were presented side-by-side, 4 cm center to center (4.2[degrees] visual angle at a viewing distance of 55 cm). Four samples were presented in a 2 x 2 array, 4 cm center to center horizontally and vertically. When the subject touched any point within the sample display area, all sample stimuli disappeared from the screen. After a delay of 1 s, during which the screen was blank, three comparison stimuli appeared in three corners of the screen. One comparison was identical to one of the samples, and touching it was the correct response. Touching either of the nonidentical comparisons was an error. During 3-s intertrial intervals, the display screen was blank.

Correct responses were followed by a computer-generated beep, the word "CORRECT" displayed for 1 s in the top center of the monitor screen, and the addition of 1 point to a 1- x 2-cm counter displayed in the top center of the screen. Trials that ended with errors were followed only by the intertrial interval.

Procedure

Subjects read and signed a consent form that described the apparatus as "used to measure certain characteristics of your eyes (e.g., pupil size) as you look at the computer screen" (after Schroeder & Holland, 1968a). They were then seated in front of the stimulus-presentation computer monitor at a viewing distance of approximately 55 cm, and the imaging headgear was adjusted. Each session began with a brief calibration routine in which subjects were instructed to hold the head still and fixate targets that appeared in various locations on the stimulus display monitor. After calibration, subjects were told that they need no longer hold the head still. Any questions about the apparatus were deferred to a debriefing that followed participation.

At the beginning of the first session, a window appeared on the monitor screen with the following instructions: "In this experiment, shapes will appear on the computer screen. You can earn points by touching the shapes. The window at the top of the screen will show your score. Try to get the highest score you can. Touch 'Continue' to begin." Subjects were asked to read the instructions aloud, and then they touched an on-screen button labeled "Continue" to begin the session.

Two-sample sessions consisted of 3 delayed one-sample trials followed by 36 delayed two-sample trials. Subjects EMU, LDC, and JNO, all experimentally naive, each received 1 two-sample session. Subject LCN had just finished participation in a pilot study examining the stability of observing behavior. Her entire experimental history consisted of 6 two-sample sessions with exactly the same procedure described above. The first of these sessions was used for data analysis in the present study.

The initial four-sample session consisted of 3 simultaneous four-sample trials (the sample stimuli remained displayed throughout the trial) followed by 36 delayed four-sample trials. Subjects LCN and EMU received 1 four-sample session. Subjects LDC and JNO had relatively low accuracy scores in the first four-sample session, and they next received a four-sample practice session without eye tracking. This session consisted of blocks of 18 trials of delayed four-sample matching and it continued until accuracy improved to at least 17/18 correct for two blocks of 18 trials. LDC and JNO completed 36 and 108 practice trials, respectively, and both met the accuracy criterion. LDC and JNO then received one final eye-tracking session consisting of 36 delayed four-sample matching trials.

Results

Computer-assisted coding of eye tracking videotapes was accomplished with OCS Tools software (Research Triangle Collaborative, Raleigh, NC) and Video Frame Coder software (Abilities Software, Sudbury, MA). To allow some time for performance to stabilize, the first 10 two-sample or 12 four-sample delayed-matching trials in each session were not included in the analyses.

An observation of a sample stimulus was defined as occurring when (a) the sample stimuli were displayed and (b) the center of the point-of-regard cursor was within a square target area surrounding each sample stimulus. Sample target-area boundaries were estimated from the point midway between sample stimuli, such that the stimulus was in the center of each target area, and the border between adjacent target areas was halfway between adjacent stimuli. An observation of a comparison stimulus was defined as occurring when (a) the comparison stimuli were displayed and (b) the center of the point-of-regard cursor was within a target area surrounding each comparison stimulus. Square comparison target-area boundaries were estimated with sides equal to one third of the vertical height of the computer screen.

The data analyses include 26 trials for each two-sample session and 24 trials for each four-sample session. To evaluate coding accuracy, a second experimenter independently coded one session for each subject; these sessions were randomly selected with the restriction that they included 2 two-sample and 2 four-sample sessions. Interobserver agreement was calculated by dividing the number of frames in which both records were coded for observation of the same stimulus by the number of frames in which either record was coded for observation of any stimulus (agreements / agreements + disagreements). Interobserver agreement scores for sample stimulus observations ranged from 90% to 97% (890/992, LCN, two samples; 1290/1351, EMU, two samples; 1374/1472, JNO, four samples; 1878/1937, LDC, four samples). Interobserver agreement scores for comparison stimulus observations ranged from 91% to 96% (831/910, LCN; 756/796, EMU; 748/780, JNO; 1010/1065, LDC). Eye-tracking data presented below came from the primary coding records.

The upper portion of Table 1 shows the accuracy and sample observing results for the two-sample task. Matching accuracy scores ranged from 96% to 100% correct. The second data row in Table 1 shows the mean number of sample observations per trial, calculated by dividing the session totals by the number of trials. For example, a left-right-left observing sequence was scored as three observations. With the two-sample task, all 4 subjects averaged more than three sample observations per trial. The row labeled "Comprehensive observing" shows percentages of trials on which subjects observed both of the sample stimuli. On the two-sample task all 4 subjects observed both sample stimuli on all trials.

Table 1 also shows sample observing duration per trial, calculated by dividing the total time during which the point-of-regard cursor remained within the target areas for sample stimuli by the number of trials. Mean sample observing durations ranged from 1.24 to 2.53 s per trial. The row labeled "Sample not observed" shows the per-trial duration during which the samples were displayed and the point-of-regard cursor was not within either of the stimulus target areas. These durations were very low or zero, and they indicate that subjects rarely or never looked away from the sample stimuli while those stimuli were displayed.

The lower portion of Table 1 shows the results for the four-sample task. The first four columns show the data for each subject's initial session. When four-sample problems were introduced, Subjects LCN and EMU's accuracy scores remained high, both 92%. Accuracy scores for Subjects LDC and JNO fell to lower levels, 67% and 63%, respectively.

In the four-sample task there were modest differences in frequency and observing diligence between subjects with high and low accuracy scores. Observing frequencies ranged from 6.13 to 8.13 observations per trial, with lower accuracy subjects at the lower end of this range. The row labeled "Comprehensive observing" shows that both subjects with lower accuracy scores observed all four samples on only 83% of the trials (20/24). Each subject made one error on one of the trials in which all samples were not observed.

The most pronounced difference among subjects in initial four-sample sessions was in sample observing duration. Relative differences in duration between subjects with high (3.65 and 4.19 s) and low (2.02 and 2.66 s) accuracy scores were greater than relative differences in other measures.

The lower right portion of Table 1 shows the results for Subjects LDC and JNO in their final four-sample sessions, in each case following a four-sample practice session. Accuracy scores were 100% for both subjects. Mean sample observing frequency for LDC increased from 6.67 to 8.71 observations per trial, and frequency remained approximately the same for JNO. The major change was in sample observing duration, which more than doubled for both subjects.

Figure 1 shows an analysis of sample stimulus observing patterns on four-sample trials. The first four to six sample observations on each trial were included in the pattern analysis. The figure shows a frequency distribution of observing patterns that occurred on at least 10% of trials; patterns that occurred on less than 10% of trials are grouped together as "Others" in the rightmost column of each plot.

[FIGURE 1 OMITTED]

The top row in Figure 1 shows data for LCN and EMU, with high accuracy scores in the initial session. Two similar clockwise patterns occurred on a majority of the trials for these subjects. The middle row shows data from LDC and JNO's initial sessions with low accuracy. No individual pattern occurred on more than one third of the trials. The leftmost column in each plot shows the proportion of trials on which fewer than four stimuli were observed (comprehensive observing < 100% in Table 1). On these trials, LDC's observing frequencies were one, three, or four, and the neglected stimulus locations varied from trial to trial (frequencies greater than three indicate that at least one location was observed more than once). On all of JNO's trials with fewer than four stimuli observed, observing frequencies were four or five, and the lower right sample location was neglected in every case.

The bottom row in Figure 1 shows data from LDC and JNO's final sessions with high accuracy. The change in LDC's sample observing topography was primarily the increase in comprehensive observing and an approximately equal increase in the clockwise pattern. In contrast, there was a striking change in JNO's observing; the clockwise pattern occurred on all but one trial.

Table 2 shows the results of data analyses for observing the comparison stimuli. The upper portion of Table 2 shows the results for the two-sample task. The first data row in Table 2 shows the mean number of comparison observations per trial, calculated by dividing the session totals by the number of trials. For example, an upper-left, upper-right, upper-left comparison observing sequence was scored as three observations. Number of observations ranged from 2.69 to 3.77. The row labeled "Comprehensive observing" shows percentages of trials on which subjects observed all three of the comparison stimuli. On the two-sample task this measure ranged from 42% to 65%. It should be noted that an observation of each comparison stimulus was not necessary for accurate responding. After the subject had observed the correct comparison, there was no need to continue to observe the other comparisons.

Table 2 also shows comparison observing duration per trial, calculated by dividing the total time during which the point-of-regard cursor remained within the target areas for comparison stimuli by the number of trials. For the two-sample task, comparison observing durations ranged from 0.94 to 0.99 s per trial.

The lower portion of Table 2 shows the comparison-stimulus observing results for the four-sample task. The first four columns show the data for each subject's initial session. When four-sample problems were introduced, observing frequencies (range 3.46 to 4.63 observations per trial), comprehensive observing of comparison stimuli (range 68% to 79% of trials), and comparison observing durations (range 1.17 to 1.59 s per trial) all increased relative to the two-sample task. There were no consistent differences in any measure for subjects with high or low accuracy scores.

The lower right portion of Table 1 shows the results for Subjects LDC and JNO in their final four-sample sessions. Accuracy for each subject was 100%. Mean frequency of observing comparisons decreased from the initial four-sample session for both LDC and JNO. Comprehensive observing of comparison stimuli increased by 9% for LDC and decreased by 10% for JNO. Changes in comparison observing durations were also inconsistent between these 2 subjects, with a small decrease for LDC and an increase for JNO.

Discussion

When the number of sample stimuli increased from two to four, all subjects had similar increases in the number of sample observations per trial. In contrast, subjects with high accuracy had greater increases in observing duration than subjects with low accuracy. For the subjects with low accuracy, practice and improvement to high accuracy was accompanied by a modest increase in frequency of observing sample stimuli for 1 subject, and a substantial increase in duration of observing sample stimuli for both subjects.

These results suggest that the stimulus control of different aspects of observing behavior topography may be independent. For subjects with high accuracy on the initial four-sample test, increases in both sample observing frequency and duration were approximately proportional to the increase in the number of sample stimuli. The data support an inference that the individual sample stimuli controlled both the pattern of eye movements and the observing duration, and these types of controlling relations were accompanied by reliable conditional stimulus control of comparison selections by sample stimuli on almost every trial.

For those subjects with low accuracy on the initial four-sample test, the data support an inference that the individual sample stimuli often controlled the trajectory of observing behavior and the pattern of eye movements, but some other aspect of the experimental situation (e.g., the entire sample array as a unit) controlled observing duration, with resulting durations that were similar to those for the two-sample arrays in the previous session. These types of controlling relations did not produce reliable conditional stimulus control by all of the sample stimuli. The apparent inflexibility in observing duration is consistent with basic laboratory research showing that observing behavior may be resistant to change when the stimuli that are observed are correlated with high rates of reinforcement (Shahan, Magee, & Dobberstein, 2003). The present results are also consistent with previous findings reported in Hodgson and Golding (2003), in which reinforced gaze strategies influenced current response execution in adults performing tasks that required flexible control of eye movements (e.g., a matching-to-sample version of the Wisconsin card sort task).

In the final session following practice and improvement to high accuracy, changes in sample observing topography included not only increases in observing durations, but also decreases in the variability of observing patterns, as shown in Figure 1. The regularities in observing behavior accompanying high accuracy suggest that one result of reinforced practice may be to increase the degree to which observing sequences function as operant units in topographically coherent response classes. Decreased variability in behavior has long been described as one of the effects of operant reinforcement (e.g., Iversen, 2002; Skinner, 1938). In the present case the decrease might best be described as an indirect effect of reinforcement because the reinforcement contingencies for accurate matching were independent of any specific pattern of comprehensive observing.

Comparison stimulus observing frequency, comprehensiveness, and duration increased from the two- to the four-sample task for all subjects, even though the number of comparison stimuli per trial was the same for both tasks. No measure of comparison stimulus observing, however, was correlated with higher accuracy in the initial four-sample session or with increases in four-sample accuracy following practice for 2 subjects. This result suggests that observing behavior topography with respect to the comparison stimuli was related to overall task difficulty, but not to differences in the effectiveness of stimulus control by sample stimuli.

As noted previously, the delayed matching to multiple samples task has been used in laboratory models of stimulus overselectivity in individuals with intellectual disabilities (Dube & McIlvane, 1997; Stromer et al., 1993). An initial analysis of eye movements in this population indicates that failures to engage in comprehensive observing may accompany the intermediate accuracy scores characteristic of atypically restricted stimulus control (Dube et al., 2003). A related finding has been that the imposition of differential observing response procedures may improve accuracy scores, at least temporarily (Dube et al., 2003; Dube & McIlvane, 1999). Such procedures impose additional response requirements that verify discrimination of all potentially relevant stimuli, and thus they require at least one observation of each sample stimulus and presumably increase comprehensive observing (as defined above) to 100%. Results of the present study suggest that the effectiveness of remedial procedures may also depend on the extent to which such procedures encourage increases in per-stimulus sample observing durations and trial-to-trial regularities in sample observing patterns. In cases where remedial procedures for stimulus overselectivity are ineffective, the present results suggest dependent variables for analysis: observing frequency, duration, and consistency.

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WILLIAM V. DUBE, LYN M. BALSAMO, THOMAS R. FOWLER, CHATA A. DICKSON, and KRISTIN M. LOMBARD

University of Massachusetts Medical School--Shriver Center

GERSON Y. TOMANARI

University of Sao Paulo, Brazil

Data collection and manuscript preparation were supported by NICHD Grants HD25995 and HD37055, and CNPq Grant 200552/96-1. The contents of this paper are solely the responsibility of the authors and do not necessarily represent the official views of NICHD. Some of the data were presented at the annual conference of the Southeastern Association for Behavior Analysis, Chapel Hill, NC, October, 1997.

We thank Kevin Farren for assistance in data analysis, Bill McIlvane for advice on the project, and Bill McIlvane and Richard Serna for comments on the manuscript. For their generosity with technical support and assistance, we thank Rikki Razdan and Alan Kielar of ISCAN Inc., and Karen DeGregory and David Pasterchik of Abilities Software.

Address correspondence to William V. Dube, Psychological Sciences Division, UMMS Shriver Center, 200 Trapelo Road, Waltham, MA 02452. (E-mail: william.dube@umassmed.edu).
Table 1 Delayed Matching Accuracy Scores and Eye-Tracking Data Analyses
for Sample Stimuli

Two-Sample Task LCN EMU LDC JNO

Accuracy 96% 100% 100% 100%
Sample observing frequency 3.92 3.08 3.19 3.42
Comprehensive observing 100% 100% 100% 100%
Sample observing duration 1.24 1.70 2.53 1.32
Sample not observed 0.02 0 0.02 0

 Initial Session Final Session
Four-Sample Task LCN EMU LDC JNO LDC JNO

Accuracy 92% 92% 67% 63% 100% 100%
Sample observing frequency 8.13 6.83 6.67 6.13 8.71 6.04
Comprehensive observing 100% 100% 83% 83% 100% 100%
Sample observing duration 3.65 4.19 2.66 2.02 6.59 4.12
Sample not observed 0 0 0.05 0 0.03 0.02

Note. Observing frequency, observing duraton, and duration during which
displayed sample stimuli were not observed (Sample not observed) are
per-trial means. Comprehensive observing shows percentages of trials in
which all sample stimuli were observed at least one

Table 2 Eye-Tracking Data Analyses for Comparison Stimuli

Two-Sample Task LCN EMU LDC JNO

Comparison observing frequency 3.77 3.23 2.96 2.69
Comprehensive observing 65% 65% 65% 42%
Comparison observing duration 0.94 0.99 0.96 0.98

 Final
 Initial Session Session
Four-Sample Task LCN EMU LDC JNO LDC JNO

Comparison observing frequency 4.09 4.04 4.63 3.46 3.71 2.92
Comprehensive observing 70% 79% 79% 68% 88% 58%
Comparison observing duration 1.17 1.51 1.59 1.19 1.43 1.39

Note. Observing frequency and duration are per-trial means.
Comprehensive observing shows percentages of trials in which all
comparison stimuli were observed at least one time.
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Author:Dube, William V.; Balsamo, Lyn M.; Fowler, Thomas R.; Dickson, Chata A.; Lombard, Kristin M.; Tomana
Publication:The Psychological Record
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Date:Mar 22, 2006
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