Behavioural Processes 45 (1999) 141 – 157

Attention and timing: dual-task performance in pigeons Helga Lejeune a,*, Franc¸oise Macar b, Dan Zakay c a

Psychobiology Temp/Processes Unit (PTPU), Faculty of Psychology, Uni6ersity of Lie`ge, 5 Boule6ard du Rectorat B32, B-4000 Sart-Tilman, Liege, Belgium b CNRS-CRNC, 31 Chemin Joseph Aiguier, 13402 Marseille Cedex 20 , France c Department of Psychology, Tel A6i6 Uni6ersity, Israel Received 1 July 1998; received in revised form 18 November 1998; accepted 18 November 1998

Abstract Pigeons were exposed to an analog of a ‘dual-task’ procedure used to test attentional models of timing in humans. After separate training on an auditory duration discrimination and on a variable ratio (VR) schedule, VR episodes lasting for 5 s were superimposed on the stimuli to be timed, either early (E) or late (L) during the trial. Trials with VR yielded underestimation of the target durations (increased % of ‘short’ choices), relative to trials without VR, and this effect was stronger under the L than under the E condition. Data were similar to those collected with humans and support attentional models of timing according to which the simultaneous non-timing task uses processing resources which are diverted from the timing mechanisms. © 1999 Elsevier Science B.V. All rights reserved. Keywords: Timing; Dual task; Attention; Pigeons

1. Introduction The temporal information processing (TIP) model designed by Church (1984) and Gibbon et al. (1984) is at the core of many studies concerned with temporal processing in the range of brief durations. Briefly described, this model is composed of three interacting levels: a clock, a mem-

* Corresponding author. Tel.: +32-4-3662017; fax: + 32-43662859. E-mail address: [email protected] (H. Lejeune)

ory, and a decision level (Church, 1984). At the clock level, pulses generated by a pacemaker are gated to an accumulator through a switch, which can be closed (so that pulses pass) or opened (pulses are stopped). The closure of the switch is triggered by incoming significant temporal information, its opening by the end of the temporal episode to be estimated (Roberts, 1983; Church, 1984; Gibbon et al., 1984). The memory level includes a short-term store which is functionally equivalent to the accumulator (it briefly retains information loaded from the accumulator when a

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delay exists between the end of the duration to be measured and the opportunity to express a duration judgment) and a long-term store (reference memory) where reinforced durations are transferred at the end of a trial. Finally, a decision level involves a comparator which compares the number of pulses currently in the short-term store, n, and a sample from reference memory, n*. A decision as to whether or not to respond depends on the comparison of the absolute difference between n and n*, expressed as a fraction of n*, and a threshold b. If this normalised value is less than the threshold, responding is initiated. This information processing model implements, in terms of psychological processes, the scalar expectancy theory, SET (Gibbon, 1977) according to which behavior exhibits the scalar property, i.e. the standard deviation of the temporal estimates is a constant fraction of the mean estimate whatever the temporal criterion t. This ‘timer’ mechanism, derived from the seminal work of Treisman (1963) on human subjects, has been supported by several animal data. It has also inspired theoretical views within the framework of human temporal processing. It has been found, for example, that under prospective conditions (that is, when the subject’s attention is clearly oriented toward the duration to be estimated), the magnitude of subjective time estimates is inversely correlated with the number of nontemporal items that are processed during the target duration. Consistent data have been obtained with various methods that manipulated the amount of attention allocated to temporal and nontemporal information (see Casini and Macar, this issue, and Lejeune, this issue). Whereas the data collected in humans with dual-task paradigms seem to reflect an attentional tradeoff between the timer and processors of nontemporal information, the status of attention is less clear in animal timing performance. However, this does not mean that the effects of attention on animal timing have been totally neglected. Indeed, during the sixties and seventies, Staddon suggested that poor timing performance may depend on the inability to focus attention on the temporal parameters of the task (Staddon, 1965, 1967, 1974). Within the framework of the temporal

information processing model, attentional variables are thought to act, firstly, at the level of the switch, and, secondly, when the comparator retrieves a sample duration or a response rule from reference memory. In the first case, diverting attention from time delays the closure of the switch or induces switch opening during the course of the duration stimulus (a ‘flickering’ switch): thus, ‘pulses’ are lost, which induces a bias towards underestimating duration. In the second case, a ‘wrong’ sample duration or response rule might be chosen, which distorts the decision process (Church, 1984; Meck, 1984). Data illustrative of both cases are described in Lejeune (1998). So far, the protocols used with animals to explore the effects of attention on timing have little in common with those designed for humans. This emphasizes the need for developing ‘analog’ experiments allowing animal–human comparisons on common methodological ground. The dualtask procedure extensively used with humans seems suited to this goal, because it is well known that animals can perform on complex operant schedules where two or more simple tasks are sequentially or simultaneously combined during a session. Previous studies have also shown that animals are capable of timing simultaneously two (e.g. DeLorge, 1967; Catania and Reynolds, 1968; Gibbon and Church, 1981; Church, 1984; Meck and Church, 1984) or even three durations (Fetterman and Killeen, 1995; Leak and Gibbon, 1995), as human subjects can do (Brown and West, 1990; Brown et al., 1992). However, as far as we know, no dual-task procedure has as yet been designed to evaluate the effects of attentional sharing between temporal and nontemporal information processing in animals. An analog of the dual-task procedure used with human subjects was designed in the present experiment, to test the applicability of the attentional model of timing to performance in pigeons. The temporal task consisted of discriminating the duration of auditory stimuli. Pigeons were trained in a three-key experimental cubicle. Reinforcement was obtained for a peck on the left key following a short duration stimulus, and on the right key following a long one. The nontemporal task during the target durations was a variable ratio (VR)

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schedule, where reinforcement rate depended on response rate on the center key of the cubicle. The attentional model of time estimation predicts that durations will be underestimated in the dual task compared to the simple-task condition, because attention allocated to the timer is reduced by the occurrence of the attention-demanding VR. A second experiment addressed the question of whether this effect would be changed by the time of VR presentation in the trial. In that experiment, the VR task was presented toward the end of the auditory stimulus, whereas it was presented early after its start in Experiment 1. This design was intended to enlighten expectancy processes.

2. Experiment 1

2.1. Methods 2.1.1. Subjects Three naive homing pigeons approximately 2years-old (P1, P2 and P3) were maintained at 85% of free feeding weight and kept on a 12:12 L/D schedule (lights on at 07:00 h). The birds were individually housed in a heated and ventilated room and had free access to water and grit. 2.1.2. Apparatus The experimental cubicle was a standard transparent three-key chamber (40 cm high × 50 cm wide ×40 cm deep) with a mat black intelligence panel on the left wall. Three keys (2 cm diameter) were placed horizontally in a row, 22 cm above the floor, with the centers of the keys 15 cm apart. A force of 0.20 N was required to operate each key. The center key could be lit red or blue, the side keys green. Reinforcers were accessible through a 5 cm2 opening located 11 cm below the center key. The cubicle was located in a larger (160 cm high×125 cm wide× 100 cm deep) heated (20°C), ventilated and partially sound-isolated experimental enclosure. White noise signals (70 DB) were produced by a Bru¨el and Kjaer generator (type 1405) and diffused by a loudspeaker located at the center of the left wall of the cubicle, 80 cm above the floor. Experimental events were recorded on a PC compatible com-

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puter located in an adjacent room. Two reinforcement dispensers were used successively: a Gerbrands grain dispenser (model G5610) and a Gerbrands pellet dispenser (model G5100). In the latter case, 45 mg Noyes pigeon pellets were dropped via a plastic tubing in a small circular cup adjusted to the funnel of the grain dispenser.

2.1.3. Procedure The dual task involved a duration discrimination schedule and a VR task which reinforces variable numbers of responses around a mean selected by the experimenter (nontemporal task). The discrimination task used durations of white noise, as previous data showed that such stimuli are well perceived by pigeons (Heinemann and Avin, 1973). Both tasks were learned in parallel, but not as components of a multiple schedule. Duration discrimination sessions usually took place in the morning, whereas VR sessions occurred in the afternoon. During step 5, discrimination and VR sessions alternated on successive days. VR training was completed at the end of this step (see ‘VR training’, below, for individual VR ratios). A ‘refresher’ VR session of 60 trials was scheduled after the last session of step 6, on the eve of the first dual-task test (step 7). For the sake of clarity, duration discrimination and dualtask training will be described first, before VR training. 2.1.4. Duration discrimination and dual-task training 2.1.4.1. Shaping the response to the center key. After magazine training, the pigeons were shaped to peck on a blue center key. The side keys were shrouded behind black adhesive covers. This procedure was in force until 20 reinforcers were obtained. Thereafter, the blue color was preceded by the red illumination of the center key. A peck at red immediately changed the key color to blue, and a reinforcer could be obtained as before. Two more sessions, limited to 20 reinforcers, occurred the same day. 2.1.4.2. Shaping the responses on the two side keys. Only one side key was accessible, the two other

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keys were shrouded under a black adhesive cover. Each peck to green was followed by a reinforcer. ITIs lasted for 5 s. Another identical 20-reinforcer session followed on the same day, with the other side key lit green. This training was repeated the next day, with the order of access to the side keys inverted.

2.1.4.3. Learning the red (center key) green (side keys) peck sequence. Two sessions ending after 20 reinforcers each followed, with the red center key preceding the green illumination of a side key. A red – green peck sequence was reinforced. ITIs were 5 s, as before. On the next session scheduled the same day, the other green key was lit. 2.1.4.4. Learning the red– white noise-green sequence. A peck on the red center key turned the duration stimulus on (white noise). Thus, the birds controlled the occurrence of the durations to be discriminated. The duration signal lasted for 4 (short standard) or 16 s (long standard) and was immediately followed by the illumination of the correct lateral green key (6 sessions). Pigeons had to learn a spatio-temporal relationship, as in Roberts and Church (1978) or Stubbs (1968). Pecking left was reinforced after the short, and pecking right after the long duration. Similar sessions followed, with 8 – 32 (4 sessions) and, finally, 10–40 s signals (6 sessions). Short and long durations were scheduled at random for each bird, provided that over the complete session series, each duration stimulus occurred eight times. The correct side key remained lit for 10 (first sessions) and then for 6 s, or until the reinforced keypeck. Each session was stopped after 40 reinforcers had been earned. 2.1.4.5. Two-duration training with simultaneous access to both side keys. Twenty sessions followed, each limited to 60 trials, where the simultaneous illumination of the two side keys followed the duration signal. Incorrect responses and reinforcer delivery were followed by the 5-s ITI. Signal durations were scheduled in semi-random order. No correction procedure was used. A series of 16 sessions, limited to 80 trials each, came next. From now on, the 3-s grain reinforcer was re-

placed by one 45 mg pigeon pellet, to minimize interferences due to grasping and swallowing. The short-long discrimination was acquired to a criterion of at least 90% correct choices over the last 10 sessions of this series (800 trials: 400 short and 400 long durations). No systematic side bias could be detected, as the total number of right /left errors (peck right instead of the ‘correct’ left key after a short stimulus/peck left instead of the ‘correct’ right key after a long stimulus) were 8/9, 15/8 and 9/17 for pigeons 1, 2 and 3, respectively.

2.1.4.6. Four-duration training without the dual task. Two probe durations were added, one located at the geometric (20 s) and the other at the arithmetic mean (25 s) of the short and long duration stimuli. These probe durations were tested in extinction, as subsequent left or right choices were not reinforced. Each session lasted for 100 trials (30× 10 s, 30 ×40 s, 20 ×20 s and 20×25 s, presented in semi-random order). Other details were as before. This 4-duration training lasted for 20 sessions. 2.1.4.7. Four-duration test with the dual task. Ten 100-trial sessions then followed, with a 5 s VR probe occurring on half the trials. The VR probe started 3 s after white noise onset, as the center key became blue. Thus, after the end of the VR, the remaining durations of white noise were 2, 12, 17 and 32 s, respectively, for 10, 20, 25 and 40 s stimuli. On average, reinforcers could be earned on about 50% of the VR trials. After the pellet was picked up, responding on the center key resumed until the blue light went off. VR probes were scheduled to occur semi-randomly on 50% of each duration trial. The side-keys remained on for 10 s, or until the choice response was made. 2.1.5. VR training After the pecks on the blue key were reinforced as described above (step 1), the VR schedule was introduced during step 3 (in separate sessions), with ratios of 3 (range 1–5), 8 (3–13), 13 (2–24), 18 (4–32) and 23 (10–36) responses per reinforcer. The three first ratios remained in force for two sessions each, the next for six and the last for 30 sessions limited to 20 reinforcers each (total

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number of sessions: 42). Twelve sessions limited to 60 reinforcers each followed, with the VR task cut into 5 s segments (range 4 – 6 s), with a 6 s ITI (4 – 8 s). These sessions were designed to fine-tune the VR ratios to reinforce the birds on about 50% of the VR trials. The final ratios used on the dual-task were 15 (5 – 25) for bird 1, 30 (10 – 50) for bird 2 and 18 (6 – 30) for bird 3. Small adjustments could occur, if inspection of the daily data showed that reinforcement ratio tended to depart from 50%. The left part of Fig. 1 depicts the experimental conditions in the dual-task trials of Experiment 1. The right part of the Figure concerns Experiment 2, to be described later.

2.1.6. Data analysis The Wilcoxon test for related samples was used to compare, for each bird separately, baseline and dual-task dependent variables, with the successive sessions taken as matched pairs. The one-tailed version of the Wilcoxon test was chosen, as the hypotheses concerning the direction of effects were clearly stated. 2.2. Results Watching the birds during the 10 dual-task sessions showed that they pecked the blue VR key each time it was lit, with very few exceptions, and picked the reinforcers up. Response rates on VR did not fluctuate much and depended on the bird (average responses/min were 47, 126 and 66 for pigeons 1, 2 and 3, respectively). Responding on the duration discrimination task was not prevented by the VR probes, as the number of choices was equal or very close to the scheduled number of trials. Further, the VR probes increased the absolute number of errors but did not induce a ‘short’ side bias on 10 and 40 s baseline trials, as the total number of right (peck the ‘long’ instead of the ‘short’ key)/left (peck the ‘short’ instead of the ‘long’ key) errors were 18/15, 11/3 and 42/19 for pigeons 1, 2 and 3, respectively. Dual-task trials with and without reinforcement during the VR period were compared first, for each bird and each duration stimulus, to check for any differences in the probability of identifying

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the signal as ‘long’. Differences were not significant, except for P3 at 20 s (T= 0, P B 0.02). Here, the probability of responding ‘long’ was lower after a trial where VR performance was reinforced. As differences were absent in 11 cases out of 12, data from both types of dual-task trials (with and without VR reinforcement) were merged and compared to data from VR-free trials (hereafter called ‘baseline trials’). Fig. 2 shows for each bird separately and on average the probability of identifying the signal as ‘long’ (ordinate) on baseline (black dots) and dual-task trials (circles) and their related standard error of the mean (SEM.: standard deviation devided by the number of matched pairs, i.e. 10), with signal duration indicated on the abscissa. As preliminary analysis showed that curvilinear fits could not be used in every case, straight lines were fitted by the method of least squares to each set of four data points and their slopes were computed. The points of subjective equality (PSE), i.e. the durations of white noise inducing 50% of ‘long’ choices were also obtained. The PSE can be considered as the psychological midpoint between the two anchor durations, in this case 10 and 40 s. Psychophysical data indicate that animals such as rats or pigeons tend to bisect at the geometric mean (here 20 s), whereas humans yield mixed results (see for example Stubbs, 1979; Allan and Gibbon, 1991 and Wearden and Ferrara, 1996). The present experiment did not aim at obtaining refined psychophysical data, therefore, the PSEs should only be taken as dependent variables whose value might be modulated by the VR probes. As can be seen in Fig. 2, the percentage of ‘long’ choices dropped on the dual-task trials and the differences between baseline and dual-task scores were most conspicuous at the intermediate durations. Differences were significant at 10, 20 and 25 s (T= 5.5, PB 0.025; T = 2.5, PB 0.005 and T= 0, PB 0.01, respectively) but not at 40 s for P1. They were significant at each duration for P2 (from 10 to 40 s, T = 0, P B 0.025; T= 2, PB 0.005; T= 7, PB 0.025 and T= 1, P B 0.025, respectively) whereas they differed only at the 20 and 25 s intermediate durations for P3 (T = 0, PB 0.005 in both cases). As between-subject

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Fig. 1. Schematic representation of the experimental setting (top: loudspeaker and three-key panel) and dual-task trial types (short, geometric mean GM, arithmetic mean AM, long) used in Experiment 1 (left: E, early presentation of the VR) and Experiment 2 (right: L, late presentation of the VR). The middle part of the figure indicates the outcome of keypecks (reinforcement, RF, or nonreinforcement, noRF) on the left (L) and right keys (R) at the end of each trial. Each experiment included 50% of trials with VR, and 50% without VR. For other details, see text.

trends were highly similar, the Wilcoxon test was also applied to the average performance. Differences between baseline and dual-task choices were significant at each stimulus duration (T = 0, P B

0.005 in every case). Regression lines fitted to the baseline and dual-task data were almost parallel or tended to converge. Slope values increased on dual-task trials (P1: 2.95 vs. 2.52; P2: 3.00 vs.

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Fig. 2. Psychometric functions relating the percentage of ‘long’ choices (ordinate) to signal duration (abscissa) on baseline trials (black dots) and dual-task trials with the VR probe presented Early (circles). SEM are given for each data point. Linear regression lines (dashes) are fitted to each function separately, and multiple regression lines are fitted to data from both functions (dots). Graphs present individual (P1, P2 and P3) and average data (bottom right).

2.98; P3: 2.33 vs. 1.92), but this increase was significant only for P1 (T = 6, P B0.025). Thus, sensitivity to time did not change after the introduction of the dual task. Such a change would have required a decrease in the number of correct choices both after the short and the long anchor durations. As slope values were not significantly different for birds P2 and P3, multiple regressions were computed for these subjects, that yielded the best fitting straight lines to both psychophysical functions. They are also shown on Fig. 2, between the linear regressions separately computed from baseline and dual-task data. PSEs obtained from baseline data were closer to the geometric (20 s) than to the arithmetic mean of the 10 and 40 s anchor durations (25 s), as usually found in animal experiments (pigeons 1 to 3: 21.98, 21.58 and 15.93, respectively). PSEs increased significantly on dual-task trials, as compared to baseline values (pigeons 1 – 3: 26.62, 27.20 and 28.67 s;

T= 1, PB 0.005; T = 0, PB 0.005 and T = 0, P B 0.005, respectively). This indicated a rightward shift of the psychophysical functions. Fig. 3 presents the daily averages of ‘long’ choices in the dual-task trials at each stimulus duration. No clearcut session effect was found at 10 and 40 s, as percentages of ‘long’ choices remained within narrow ranges (0–10 s or 80–90 s). Intermediate values followed opposite trends, with ‘long’ choices decreasing at 20 and increasing at 25 s, before stabilizing over the last sessions. From the beginning to the end of the session series, values remained hierarchically organized (% of ‘long’ choices at 10 B 20B 25B 40 s), in the same order as the stimulus durations.

2.3. Discussion First, it should be noted that dispensing reinforcers during the VR period did not disrupt

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performance, contrarily to what might happen under conditions where response-independent reinforcers are dispensed as animals perform on operant schedules (for instance, Rachlin and Baum, 1972). Trials with reinforced and non-reinforced VR similarly affected duration estimates. This experiment showed the following trends. First, the dual task decreased the proportion of ‘long’ choices, and this decrease was most conspicuous at the non-reinforced intermediate probe durations. Secondly, between-session variability of performance was small (see SEMs). Thirdly, regression lines and PSEs indicated that the psychophysical functions were shifted to the right. These data show, for the first time, that a dual-task procedure used in a non-human species yielded effects that are highly similar to those described in humans (review in Brown, 1997). The difference between the extreme versus intermediate

Fig. 3. Session by session evolution (abscissa) of the average percentage of ‘long’ choices (ordinate) made after each signal duration (10, 20, 25 and 40 s) on dual-task trials from condition ‘early’.

target durations might be explained by the fact that the former were reinforced and were clearly discriminated as shown by baseline trials (about 90% correct choices). In addition, despite a floor effect in the case of the 10 s-duration that initially induced a very small proportion of ‘long’ choices, this small proportion further decreased significantly in the dual-task trials of pigeons 1 and 2. Concerning the intermediate durations, as no ‘correct’ judgement was defined for these probes tested in extinction, the constraint to choose one or the other response was not strong, therefore allowing for the full expression of the dual-task effect. One interpretation of these effects in the context of human research is that a smaller number of pulses accumulates during the target duration when attention is diverted from it, because of concurrent information processing. As a result, the target duration is judged to be shorter, as estimated duration is assumed to be in monotonic relation with the accumulated pulse number (Thomas and Weaver, 1975). The present experiment suggests that, when performing on dual tasks, animals share common mechanisms with humans as concerns both timing and attention. The question of how the nontemporal task interferes with time estimation deserves further investigation. Three hypotheses may be considered, thereafter called ‘switch’, ‘erasure’ and ‘expectancy’. First, performing the dual task during the duration stimulus might open the switch mechanism included in the information processing model (Church, 1984) and, hence, prevent pulses from reaching the accumulator. The underestimation would then depend on the length of the VR period, whatever its location within the duration stimulus. In other words, the dual task is supposed to ‘stop the clock’ during its occurrence. Secondly, the dual task might erase all the pulses accumulated previously to and during its occurrence. Varying the moment of this occurrence in the course of a trial would thus produce various amounts of duration underestimation: the later the VR episode, the more underestimation should be observed. The switch and erasure hypotheses

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have been discussed on the basis of data obtained with animals (Meck, 1984; Olton et al., 1988; Roberts et al., 1989) and humans (Macar et al., 1994; Casini and Macar, 1997). Although duration discrimination tasks such as the one used here do not offer the possibility of measuring accurately the amount of underestimation, as production or reproduction tasks can do, the switch and erasure views yield contrasted predictions that are easy to check by changing the moment of VR presentation. No difference in the underestimation trend should be observed in the case of a switch opening limited to the VR episode, whereas, if the erasure hypothesis holds, underestimation should be proportional to the location of the VR episode: the later the VR, the more underestimation should occur. Both hypotheses suggest that the VR operates at the first level of the temporal information processing model, the first hypothesis targeting only the switch, the second targeting the switch and pulse counts already encoded in the accumulator. These contrasted predictions would imply that the two mechanisms considered are clear-cut and not modulated by expectancy. It has been suggested, however, that the underestimation effect that is obtained when an additional task is given during the target duration is influenced by expectancy (Casini and Macar, 1997). In human subjects who had to discriminate both the duration of a visual stimulus and the amplitude of a brief change in intensity that could occur at any time during that stimulus, underestimation increased as the change occurred later. The authors proposed that the subjects expected the change from the beginning of the trial, and that the effects of expectancy increased with the estimated probability of its occurrence. Expectancy might produce additional attention shifts that transiently block pulse accumulation. It should thus enhance the effects postulated in line with the switch hypothesis. Admittedly, an additional memory effect may take place, if some of the pulses previously accumulated are erased at each attention shift. This possibility differs from the simple version of the erasure hypothesis in that only partial loss is assumed to occur, rather than complete erasure of all the pulses accumu-

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lated until the occurrence of an interference. Thus, the expectancy hypothesis, wherever its impact, may be contrasted to simple (expectancy-independent) views of the switch and erasure mechanisms. Experiment 2 documented this question.

3. Experiment 2 Experiment 2 was designed to test whether the underestimation effect is sensitive to the position of the VR period during the duration stimulus, in order to decide between the ‘switch’, the ‘erasure’ and the ‘expectancy’ hypotheses. Rather than being placed early in the course of the duration stimulus (3 s after its onset) as in Experiment 1, the VR period was delayed so as to end 3 s before its offset. This modification will be designated as condition ‘late’ (L) by contrast with condition ‘early’ (E) of Experiment 1. If the ‘switch’ hypothesis holds, the underestimation effect should not be affected by this modification. Therefore, psychophysical functions from the dual-task E and L conditions should superimpose, and simply shift to the right with regard to baseline data. If the ‘erasure’ hypothesis is prevalent in the L condition, the psychophysical function should give way to a flat line located at about 0% ‘long’ responses, as the short residual portion of the target duration after the end of the VR period (that is, the preserved period of pulse accumulation) would be identical at the four duration stimuli. If the ‘expectancy’ hypothesis fits the data, underestimation should be more marked in the L condition, because the pigeons, first trained on E trials, would expect VR occurrence from the beginning of the target duration. Further, the magnitude of the effect expected on L trials should be intermediate between those predicted by the ‘switch’ and the ‘erasure’ views. The expectancy effect should also be sensitive to the actual learning conditions. It can be maximized if the E condition precedes the L condition under an AB design, or on a design where E and L trials are scheduled at random during the same session. The first design was chosen to maximize the expectancy effect in the

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first L sessions and to test the prediction that this effect should weaken as the new training progresses. The L condition was preceded by a 3-session E retraining to ensure that behavior typical of those from the first experiments were recovered before E/L comparisons were done.

3.1. Methods A 2-week recess without training followed the last step of Experiment 1. Then the pigeons were returned for 2 sessions on a 4-duration discrimination without VR, and then to the E condition for 3 more sessions. VR response rates obtained on the latter trials were similar to those recorded in Experiment 1 (pigeons 1 – 3: 57, 100 and 61, respectively), and casual observation confirmed that blue-key responses were given on almost every VR probe. Choice patterns similar to those from condition E were recovered. Next, the L condition of the dual task was scheduled for 10 sessions. The procedure was identical to the 7th step of the E condition, except that the 5 s VR sequence ended 3 s before the end of the duration stimuli. Thus, the VR probes started 2, 12, 17 and 32 s after the onset of the 10, 20, 25 and 40 s white noise stimuli, respectively. The conditions prevailing in Experiment 2 are depicted in the right part of Fig. 1.

3.2. Results As previously, pigeons pecked at the blue key on VR probes (response rates from pigeons 1 to 3: 55, 101 and 56, respectively) and the numbers of duration judgements were equal or close to the number of trials of the session. A systematic side bias on 10 and 40 s baseline trials was not found: right/left errors were equal to 8/9, 2/2 and 11/13 for birds 1, 2 and 3, respectively. As in experiment 1, dual-task trials with and without reinforcement during the VR period were compared first, for each bird and each duration stimulus, to check for any differences in the probability of identifying the signal as ‘long’. Differences were not significant, except for P1 at 40 s (T = 0, PB 0.01). For that bird, the probability of responding ‘long’ was lower after a trial where

VR performance was reinforced. As differences were absent in 11 cases out of 12, data from both types of dual-task trials (with and without VR reinforcement) were merged and compared to data from VR-free trials (hereafter called ‘baseline trials’). The individual and average psychophysical functions from Experiment 2 (condition L), as well as their fitted regression lines, can be seen in Fig. 4. A striking difference emerges with regard to the E condition: the psychophysical gradients derived from dual-task trials were much flatter, whereas the baseline gradients remained closer to the previous ones. Between-session variability remained small (see SEMs), except for P3. Differences between the percentages of ‘long’ choices on baseline and L trials were significant at all durations for P1 (10 s: T= 0, P B 0.025; 20, 25 and 40 s: T= 0, PB 0.005). For P2, differences were significant at 20 (T= 2, PB 0.005), 25 and 40 s (T= 0, PB 0.005 in both cases), whereas they were significant only at 40 s for P3 (T = 2, PB 0.005). Indeed, inspection of the response gradients in bird 3 showed that, over the last sessions, percentages of ‘long’ responses increased at the shortest duration, which might be interpreted as a general loss of sensitivity to time. However, Wilcoxon tests computed over the data from the first eight sessions (long dashes on the graph of P3) yielded significant differences at 20 (T = 1.5, PB 0.01), 25 and 40 s (T= 0, PB 0.005 in both cases). The average function of the three birds, taking all 10 sessions into account, is presented at the bottom right of Fig. 4. Differences between baseline and dual-task L trials were significant at 20 (T= 1.5, PB 0.005), 25 and 40 s (T= 0, P B 0.005 in both cases). Overall, performance recorded on L trials can be described as an asymmetrical change in the ogival function as, in contrast to what happened in Experiment 1, percentages of ‘long’ responses dropped heavily at the 40 s stimulus duration. In contrast to data from Experiment 1, regression lines fitted to baseline and L data clearly diverged. Trends would even have been sharpened had regression lines been fitted to the intermediate durations only or to the data from the first ses-

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Fig. 4. Psychometric functions relating the percentage of ‘long’ choices (ordinate) to signal duration (abscissa) on baseline trials (black dots) and dual-task trials with the VR probe presented late (circles). Other details are as in Fig. 2.

sions of the L series (see Figs. 4 and 6). Slope values were much lower from L than from baseline trials (P1: 1.31 vs. 2.94; P2: 2.44 vs. 3.36; P3: 1.18 vs. 2.78; T= 0, P B0.005 for each case). Baseline PSEs were located close to the arithmetic mean (pigeons 1 and 2: 23.49 and 25.54 s, respectively), or just between the geometric and arithmetic means (P3: 22.60 s). PSEs from L trials were much larger in each bird (P1: 80.53 s; P2: 37.06 s; P3: 35.00 s). Relative to baseline values, these increases were significant for pigeons 1 and 2 (T = 0, PB0.005 for each bird) and just short of significance for P3 when taking the complete 10 session series into account (T =9, NS). However, over the first eight sessions, baseline-L differences reached significance (22.41 vs. 43.10 s: T = 1, P B 0.01). Session by session evolution of average proportions of ‘long’ responses is depicted in Fig. 5. Differences with the E condition (Fig. 3) are clearcut, as percentages of ‘long’ choices were

much lower at 20, 25 and 40 s. Indeed, over the first 4 sessions, percentages of ‘long’ choices after 20 or 25 s matched the 10 s ones and were close to or equal to zero, before increasing slowly. Percentages of ‘long’ choices after the 40 s stimulus were about half the value found on E trials. They increased progressively, and reached E values only at the end of the session series. Fig. 6 highlights this evolution by showing the percentage of ‘long’ choices (expressed as proportions of their respective baseline values) computed separately from the first and last three sessions on conditions E and L. As could be guessed from comparing Figs. 3 and 5, choices at the end of condition L grew close to those prevailing on condition E. Between-experiment comparisons were made to further characterize differences between E and L conditions. To this purpose, L data were expressed as proportions of the respective baseline values at each duration. Comparison of these normalized values yielded significant differences

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at 20, 25 and 40 s for P1 (T =1, P B 0.005; T =1, PB0.005 and T = 0, P B0.005, respectively) and P2 (20 s: T =6, P B 0.025; 25 s: T = 0, PB0.005; 40 s: T = 3.5, P B0.01). In every case, ‘long’ choices were less numerous on dualtask L trials. Such a trend was significant only at 40 s for P3 (T= 5.5, P B0.025), due to the progressive drift of choices described above. Furthermore, comparison of normalized E and L slopes indicated that values were significantly smaller on the L than the E condition (birds 1 to 3: T =0, PB0.005; T = 2, P B0.005; T= 1, P B0.005, respectively). Finally, Comparison of normalized PSEs yielded significant differences for birds 1 and 2 (T = 0, P B 0.005 and T = 7, P B 0.025). Over the 10 session series, this difference did not reach significance for P3. As previously, a significant difference showed up when the first eight sessions were taken into account (T = 1, PB0.01).

Fig. 6. Percent of ‘long’ choices, expressed as proportions of their respective baseline values (ordinate), on the first three (black symbols) and the last three (open symbols) sessions of conditions E (squares) and L (triangles), as a function of signal duration (abscissa). For the sake of clarity, the values have been arbitrarily set at zero for the 10 s stimulus, because the small percentages of ‘long’ responses to that duration yielded proportions which were in some cases superior to 1: for example, if ‘long’ choices amount to 3% on baseline, and 5% on condition E, the ratio would be 1.66.

4. Discussion

Fig. 5. Session by session evolution (abscissa) of the average percentage of ‘long’ choices (ordinate) made after each signal duration (10, 20, 25 and 40 s) on dual-task trials from condition ‘late’.

Experiment 2 confirmed that the VR task reduces the proportion of ‘long’ choices. Further, it allowed to decide between the ‘switch’, the ‘erasure’ and the ‘expectancy’ hypotheses. The first predicted similar psychometric functions on E and L trials, as transfer of pulses to the accumulator is hampered only during the dual-task. The second suggested the complete flattening of the function derived from L trials, because the VR period erases the durations stored previously to or during its occurrence. The third posited that proportions of ‘long’ choice should be lower on L than on E, at least in the first sessions, because, due to their previous experience (E condition), the pigeons ‘wait’ for the occurrence of the VR period from the beginning of the trial, which reduces attention allocated to the timer and lowers pulse count. Thereafter, a clear effect of training under the new (L) condition was expected.

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As compared to Experiment 1, the dual task trials in the L condition from Experiment 2 significantly reduced the proportion of ‘long’ choices, decreased the slopes of the psychometric functions and increased the PSEs. These data entail rejection of the mere switch hypothesis, as E and L functions did not superimpose. The erasure hypothesis is also inadequate, as L functions were not completely flat. The asymmetrical change in the psychometric function on L trials rather fits with a bias towards the ‘short’ choice alternative (which was predicted by the expectancy hypothesis) and cannot be accounted for in terms of a mere loss in the sensitivity to time, which requires that the percentage of errors increases both for the short and the long anchor durations. The evolution of performance from session to session clearly sustains this conclusion, as, contrarily to the stable pattern observed in Experiment 1, the percentages of ‘long’ choices were extremely low in the first L sessions and increased thereafter. The absence of a session effect on E was due to the fact that the early occurrence of the VR episode did not interfere with attention allocated to the residual stimulus durations (after the end of VR). Birds had just to generalize responding developed on baseline trials to a set of durations as easy to discriminate as baseline durations (2, 12, 17 and 32 s instead of 10, 20, 25 and 40 s). Quite to the contrary, residual durations were the same on condition L. Mastering the task thus required to allocate sufficient attention to durations preceding the VR probe. This was not achieved over the first five sessions or so: due to the just previous experimental history, attention was focused on waiting for an early occurrence of the nontemporal event (VR) and not on the timer. It is only after learning the late occurrence of the VR that more attention could be allocated to the durations preceding the occurrence of the VR probe. As, in dual tasks using human subjects, motor load bound to the performance of the dual task is a variable which can modulate the estimation of time (Brown, 1997), it may be objected that our baseline and dual-task conditions differed by the level of motor load involved. Indeed, with regard to baseline conditions, the VR episode required

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additional keypecking (motor load) which may be thought to induce underestimation. However, according to this line of reasoning, the larger underestimation found in L compared to the E condition should also correspond to increased motor load. To evaluate motor charge, VR response rates from E and L were compared for each bird. No significant difference was found for bird 1, whereas lower response rates (i.e. decreased motor load) were observed during L for birds 2 and 3 (T= 0, P B 0.005 for each bird). Thus, the role of motor load is not conclusive here. Still another hypothesis can be disproved, which posits that the opportunity to collect supplementary reinforcers during VR induced an arousal increase which sped the pacemaker up. Indeed, arousal is thought to increase the rate of the pacemaker (Wearden and Penton-Voak, 1995), as do drugs such as dopaminergic agonists (Meck, 1983). Thus, more pulses would be recorded per unit time, leading to an overestimation of the duration of a stimulus. Furthermore, as pulse rate decrease does not follow a step function, but rather a smooth decline, after-effects of pulse rate increase cannot stop immediately on the end of the arousing episode. Transposing this reasoning to the present case, it is compelling that, if the VR episode sped the pacemaker up, durations should be overestimated in the dualtask conditions with regard to baseline, and also on the E condition with regard to L because, in the former case, a much longer residual stimulus duration follows the end of the VR episode. Thus, trends opposite to those described here should be obtained. The present data can be compared with the expectancy effect described by Casini and Macar (1997) in humans. In this case, however, the moment when the nontemporal task was presented in the course of a trial was varied within rather than between blocks. Hence, the subjects had no possibility to discover any recurrence and to modify their performance with training. Rather, they were expecting the nontemporal task until it took place, and the later it took place, the greater was their underestimation. Similarly, the pigeons may be thought to allocate attention to the possible occurrence of the VR task from the beginning of

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the trial in the first sessions of Experiment 2. Each attention shift, whether due to expectancy or to the actual processing of the nontemporal task, might block pulse accumulation. This may impair the initial steps of duration coding, by acting at the switch level (Penney et al., 1996). The dramatic effects observed in the first L sessions further suggest that attention shifts also provoked a memory loss leading to an additional pulse reduction. Memory defects also seem to account for the bias towards underestimation of duration that is found in delayed choice experiments. Researchers in this field generally used the delayed matchingto-sample procedure (DMTS), with the exception of Church (1980) and Fetterman (1995) who trained pigeons on a temporal psychophysical choice task as here. In Fetterman’s first experiment, four pigeons were tested with 2 and 10 s reinforced durations, and four intermediate duration probes presented in extinction. Data obtained with response delays ranging from 0 to 15 s were similar to those described here: the slope of the psychometric functions decreased as response delay increased, and the PSEs increased. The decrease in slope values was akin to a bias to respond ‘short’ and could not, as was the case here, be completely accounted for in terms of a mere loss of sensitivity to time. Results were interpreted as supporting subjective shortening and retrospective measure of stimulus duration, prior to choice. According to the subjective shortening model (Spetch and Wilkie, 1982, 1983; Spetch and Ruzak, 1992), remembered duration shortens during the retention interval, and this shortening grows as the delay interval lengthens. This effect is congruent with the coding of duration in analogical terms (for instance, numbers of pulses stored in short-term memory) and incompatible with a categorical coding of duration, for instance in terms of response strategy (short = ‘peck blue’; long = ‘peck red’). It is important to notice, firstly, that we obtained a ‘choose short’like effect using a dual-task instead of choice delays, and, secondly, that this effect, as those predicted by the subjective shortening model, seems congruent with the analogical coding of duration. Thirdly, the effect described here seems

sensitive to the temporal location of the nontemporal task during the temporal stimulus, as the choose-short effect is parametrically related to the duration of the retention delay. Our results also are similar to data described in Cabeza de Vaca et al. (1994). Using a Peak Interval procedure of 30 s and pigeons as subjects, this experiment manipulated the duration and the location of breaks and yielded shifts of peak time which were proportional to the delay preceding the gap in the peak trials. Thus, at the behavioral level, dual tasks, retention intervals and breaks seem to induce similar outcomes. It remains to specify the mechanisms responsible for the obtained effects. Cabeza de Vaca and collaborators suggested that data from the break location manipulation seemed close to predictions made by an exponential model of decay, according to which peak time shifts vary linearly with break location and are a nonlinear function of break duration. They also suggested that this decay process operates at the level of working memory. We rather propose that data described here may depend on attentional shifts operating at the level of the switch, and to a lesser expent, at the level of the accumulator, i.e. at the level of duration coding instead of duration memory. The findings obtained in the present study seem to lend support to the hypothesis that attention has a similar role in humans and in animals’ timing processes. However, it has been questioned whether attentional processes can be considered to be identical in humans and animals. Researchers such as Rescorla and Wagner (1972) or Mackintosh (1975, 1983) assigned to attention a very narrow meaning in the context of animals’ discrimination learning and conditioning processes. In contrast, researchers like Blough (1989, 1991) or Hinson and Tennison (1997) recently argued that there is sufficient evidence available today pleading for the utility of attentional processes in theories of animal conditioning. Hinson and Tennison further elaborated the concept of animals’ attention. They conceived an attentional model for explaining the dimensional contrast effects in animals. These effects refer to an enhancement of discrimination performance be-

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tween positive (S + ) and negative (S − ) stimuli which are relatively similar. For instance, if, on a wavelength continuum, a S− is contrasted to several S+, responding is higher for the wavelength values which are closest to the S − (positive dimensional contrast), and vice versa (negative dimensional contrast). In other words, stimuli which are more difficult to discriminate are better discriminated than less similar ones. A related phenomenon was observed in humans on a temporal generalization task, where the generalization gradient was steeper with comparison durations closer to the standard duration, than with durations which were temporally more remote (Ferrara et al., 1997). Both sets of data were tentatively interpreted as deriving from a nonuniform allocation of attentional ressources. Hinson and Tennison (1997) suggested that it would be worthwhile to investigate in animals the effect of dual discrimination tasks, in order to clarify what is implied by the concept of resources. The dual task methodology was actually utilized here and the notion of limited capacity and of the need to divide attention between temporal and nontemporal information processing while making temporal judgments was supported. This finding is similar to what was obtained for humans’ prospective timing processes (review in Brown, 1997). The interpretation that timing processes in animals involve attentional mechanisms which are similar to those at work in human prospective timing is in line with the recent ‘ attentional gate model’ (Block and Zakay, 1996; Zakay and Block, 1997) which proposes a ‘ merger’ between scalar timing properties and cognitive factors such as attention. The attentional gate model adds a module (the ‘gate’) at the level of clock stage of the TIP model, between the pacemaker and the switch. The gate constrains the transfer of pulses produced by the pacemaker, because its opening depends on attention allocation to time. If attention is captured by nontemporal events, the gate remains closed and the available attention is reallocated to their processing, as is the case in humans performing a retrospective timing task. This model thus suggests that a same theoretical frame might be common to all species. Yet, one can think of some important aspects in which humans

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and animals differ in terms of how attention influences timing processes. One such major difference is the ability to deliberately allocate attention to either temporal or nontemporal information processing (as was explicitly required from the subjects in the experiments by Macar et al., 1994 and Casini and Macar, 1997), besides the more basic automatic attention allocation which animals and humans seem to share. In conclusion, it may be suggested that the dual-task methodology used in humans to test the attentional models of timing can be successfully transposed to non-human species. Our data are best accounted for as resulting from attentional mechanisms operating on durations coded in analogical terms. The switch located at the clock level of the temporal information processing model may be the likely (but not exclusive) target of attention shifts. Further research is needed in order to test the applicability of the attentional model in its full range to animals’ performance and to answer the question of the functional differences between breaks, retention intervals and dual tasks. The generality of this model takes on a fundamental importance for both timing and attention models and concepts.

Acknowledgements The authors are indebted to Dr John Wearden for insightful comments on an earlier version of this article. They also are indebted to Fre´de´ric Simons, Andre´ Ferrara, Miche`le Vandenberg and Sophie Vercheval for assistance in software design, data analysis and animal testing.

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