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When short-term memory is assessed in the delayed matching-to-sample (DMTS) procedure, performance is better when cues signal larger reinforcer magnitudes or higher reinforcer probabilities for correct responding. Previous studies demonstrating signaled-magnitude or signaled-probability effects presented cues for a prolonged period during the sample stimulus and/or retention interval. The present study asked whether a signaled-probability effect would occur with brief post-sample cues that signaled the presence or absence of reinforcement. Five pigeons responded in a DMTS task in which sample stimuli were sometimes followed by a 0.5-s cue signaling that reinforcers would either be available or not available in the current trial, and the retention interval varied from 0.5 s to 20 s. A reliable signaled-probability effect was found when reinforcers were arranged independently and for all correct responses, whereas a smaller, less systematic effect was found when reinforcers were arranged dependently and probabilistically. These findings highlight the importance of reinforcement contingencies and contingency discriminability in remembering, and add to the evidence showing that cues signaling differential reinforcement in DMTS may affect processes during the retention interval and comparison phase, rather than attention to the sample stimulus., (Copyright © 2022 Elsevier B.V. All rights reserved.)

When reinforcer availability on one alternative of a concurrent schedule is signaled by a discriminative stimulus, responding on that alternative decreases. We investigated how the correlation between signal presentation and reinforcement (signal reliability) affects choice between signaled and unsignaled alternatives. Six pigeons responded in a concurrent schedule, in which reinforcers on one alternative were signaled by a key-color change. Across conditions, the probability of reinforcement following signal presentation varied (the probability in its absence was the complement). As signal reliability increased, response rates and latencies following signal onset on the signaled alternative decreased, whereas responding on the unsignaled alternative remained unchanged. Because the signal did not alter overall reinforcer rates, these findings are consistent with matching theories and research suggesting that responding on one alternative of a concurrent schedule depends on reinforcer, but not response, rates on other alternatives. However, these findings are inconsistent with others demonstrating concomitant changes in responding on signaled and unsignaled alternatives. We consider whether a response-competition account of concurrent performance can explain these discrepancies, and suggest avenues for future studies to investigate the mechanisms underlying effects of signaled reinforcement in concurrent schedules., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Stimulus generalization is typically assessed by analyzing overall response rates. Studies of generalization of response-rate patterns across time are less common, despite the ubiquitous nature of time and the strong temporal control over behavior in the natural world. Thus, we investigated generalization of response-rate patterns across time using a multiple peak procedure in pigeons. The frequency (fast or slow) at which the color of a keylight changed signaled a fixed-interval (FI) 5-s or 20-s schedule, counterbalanced across subjects. In peak trials, the frequency of keylight-color changes was varied. For the fast and slow training stimuli, response rates in peak trials were controlled by the arranged FI schedule value; they increased as the arranged reinforcer time approached, and decreased thereafter. Response-rate patterns to all test stimuli were similar to response-rate patterns to the slow training stimulus for all subjects. Thus, overall, strong generalization from the slow training stimulus to all test stimuli was evident, whereas there was little to no generalization from the fast training stimulus. These findings extend past research examining generalization of temporally controlled response-rate patterns, and provide a useful starting point for future investigations of generalization of fixed-interval responding. A thorough understanding of generalization processes requires analysis of dependent variables other than overall response rates, especially when responding is likely to be temporally controlled., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Several studies suggest that the degree of control by reinforcer ratios (environment tracking) and by exteroceptive stimuli that signal future reinforcer availability (signal following) depends on environmental certainty: As reinforcers become more likely at one location, environmental contingencies exert stronger control and exteroceptive stimuli exert weaker control. This research has not yet been extended to environments in which reinforcer availability changes across time, even though such changes are present in most natural environments. Thus, in the present experiment, we examined environment tracking and signal following in a concurrent schedule in which the reinforcer ratio reversed to its reciprocal 30 s after a reinforcer delivery and keylight-color stimuli signaled the likely or definite time or location of the next reinforcer. Across conditions, we manipulated environmental certainty by varying the probability of reinforcer deliveries on the locally richer key. This made the location of future reinforcers at a particular time more or less certain, but did not change the overall reinforcer ratio. Changes in local environmental certainty had little to no effect on environment tracking and signal following; in all conditions, keylight-color stimuli strongly controlled choice and reinforcer ratios exerted weak control. The present findings suggest that the extent of environment tracking and signal following is primarily determined by global, not local, environmental certainty., (Copyright © 2018 Elsevier B.V. All rights reserved.)

From a model that generates event records, we may generate predictions for any dependent variable computable from those event records. In the present paper, we examined an implementation of Shimp's (1978) Associative Learner for two-alternative concurrent variable-interval variable-interval schedules in transition. In general, our Associative Learner implementation had difficulty accounting for the inter-response times as a function of the reinforcer ratio, the general frequency of inter-response times, the acquisition of consecutive reinforcers from the same alternative, and the response rates to the not-just-reinforced alternative after a reinforcer. An extended Associative Learner implementation was designed with provisions for increasing responding to the just-reinforced alternative after a reinforcer and organising bout-like responses. The extended implementation rectified many of the weaknesses of the base implementation., (Copyright © 2018 Elsevier B.V. All rights reserved.)

In concurrent schedules with a changeover delay (COD), choice often strongly favours the just-reinforced alternative immediately after a reinforcer delivery. These 'preference pulses' may be caused by a change in reinforcer availability created by the COD, and/or because the COD decreases the overall probability of switching. We investigated which explanation better accounts for preference pulses by arranging concurrent schedules that allowed us to separate the COD's effects on reinforcer availability from its effects on the probability of switching. When the reinforcer ratio was 1:1, pulses were inconsistently accompanied by changes in reinforcer availability, but consistently accompanied by longer visits. These pulses appeared to be related only to the decreased probability of switching caused by the COD, providing the first evidence of pulses after reinforcers caused by the probability of switching alone. When the reinforcer ratio was 1:5 or 5:1; preference pulses were accompanied by changes in reinforcer availability and by longer visits. These pulses appeared to be related to the COD's effects on reinforcer availability, although a small portion appeared to be related to low probability of switching. These findings suggest that the COD affects preference pulses by both decreasing the probability of switching and creating a change in reinforcer availability., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Catania's Operant Reserve (COR; Catania, 2005) is a computational model of operant behaviour. In COR, responding depletes the reserve while reinforcement replenishes the reserve. The replenishment to the reserve depends on the location of responses within the most recent inter-reinforcement interval. The rule that maps replenishment to the responses within an inter-reinforcement interval is given by a delay-of-reinforcement gradient (DOR). Previous research (Berg and McDowell, 2011) found that non-linear DORs produce sigmoidal response rates on single variable-interval schedules while a linear DOR produces hyperbolic response rates. Berg and McDowell took these sigmoidal response rates as evidence against the viability of COR for modelling variable-interval performance. However, Berg and McDowell did not consider the effect of the slope of each DOR. The present conjecture is that the response rates from COR can be made hyperbolic by manipulating the area under the DOR. Our results show that the manipulation of the area under the DOR allows COR to produce hyperbolic response rates regardless of the parametric form of the DOR. Hence, if COR is to be used to model single variable-interval performance, the reinforcement effect over time should be taken into consideration through the manipulation of the area under the DOR., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Both the response-reinforcer and stimulus-reinforcer relation are important in discrimination learning; differential responding requires a minimum of two discriminably-different stimuli and two discriminably-different associated contingencies of reinforcement. When elapsed time is a discriminative stimulus for the likely availability of a reinforcer, choice over time may be modeled by an extension of the Davison and Nevin (1999) model that assumes that local choice strictly matches the effective local reinforcer ratio. The effective local reinforcer ratio may differ from the obtained local reinforcer ratio for two reasons: Because the animal inaccurately estimates times associated with obtained reinforcers, and thus incorrectly discriminates the stimulus-reinforcer relation across time; and because of error in discriminating the response-reinforcer relation. In choice-based timing tasks, the two responses are usually highly discriminable, and so the larger contributor to differences between the effective and obtained reinforcer ratio is error in discriminating the stimulus-reinforcer relation. Such error may be modeled either by redistributing the numbers of reinforcers obtained at each time across surrounding times, or by redistributing the ratio of reinforcers obtained at each time in the same way. We assessed the extent to which these two approaches to modeling discrimination of the stimulus-reinforcer relation could account for choice in a range of temporal-discrimination procedures. The version of the model that redistributed numbers of reinforcers accounted for more variance in the data. Further, this version provides an explanation for shifts in the point of subjective equality that occur as a result of changes in the local reinforcer rate. The inclusion of a parameter reflecting error in discriminating the response-reinforcer relation enhanced the ability of each version of the model to describe data. The ability of this class of model to account for a range of data suggests that timing, like other conditional discriminations, is choice under the joint discriminative control of elapsed time and differential reinforcement. Understanding the role of differential reinforcement is therefore critical to understanding control by elapsed time., (Copyright © 2016 Elsevier B.V. All rights reserved.)

Five pigeons were trained in a procedure in which, with a specified probability, food was either available on a fixed-interval schedule on the left key, or on a variable-interval schedule on the right key. In Phase 1, we arranged, with a probability of 0.5, either a left-key fixed-interval schedule or a right-key variable-interval 30s, and varied the value of the fixed-interval schedule from 5s to 50s across 5 conditions. In Phase 2, we arranged either a left-key fixed-interval 20-s schedule or a right-key variable-interval 30-s schedule, and varied the probability of the fixed-interval schedule from 0.05 to 1.0 across 8 conditions. Phase 3 always arranged a fixed-interval schedule on the left key, and its value was varied over the same range as in Phase 1. In Phase 1, overall preference was generally toward the variable-interval schedule, preference following reinforcers was initially toward the variable-interval schedule, and maximum preference for the fixed-interval schedule generally occurred close to the arranged fixed-interval time, becoming relatively constant thereafter. In Phase 2, overall left-key preference followed the probability of the fixed-interval schedule, and maximum fixed-interval choice again occurred close to the fixed-interval time, except when the fixed-interval probability was 0.1 or less. The pattern of choice following reinforcers was similar to that in Phase 1, but the peak fixed-interval choice became more peaked with higher probabilities of the fixed interval. Phase 3 produced typical fixed-interval schedule responding. The results are discussed in terms of reinforcement effects, timing in the context of alternative reinforcers, and generalized matching. These results can be described by a quantitative model in which reinforcer rates obtained at times since the last reinforcer are distributed across time according to a Gaussian distribution with constant coefficient of variation before the fixed-interval schedule time, changing to extended choice controlled by extended reinforcer ratios beyond the fixed-interval time. The same model provides a good description of response rates on single fixed-interval schedules., (Copyright © 2013 Elsevier B.V. All rights reserved.)

Six pigeons responded on a four-key concurrent variable-interval schedule in which a 27:9:3:1 distribution of reinforcers between the keys changed every 10 reinforcers. Their behaviour quickly came under the control of this changing four-way reinforcer ratio. However, preference between a pair of keys depended not only on the relative reinforcer rates on those keys, but also on the absolute levels of those rates. This contradicts the constant-ratio rule that underpins the matching approach to choice, but is predicted by a contingency-discriminability model that assumes that organisms may occasionally misattribute reinforcers to a response that did not produce them. Reinforcers produced strong preference pulses, or transient increases in responding on the just-reinforced key. Despite accurate tracking of the reinforcer ratio, reinforcers obtained late in components and from leaner keys still produced strong pulses, suggesting both extended and local control of behaviour. Patterns of switching between keys were graded and similarly controlled by the reinforcer rates on each key. Whether considered in terms of switching, local preference pulses, or extended preference, behaviour was controlled by a rapidly changing four-way reinforcer ratio in a graduated, continuous manner that is unlikely to be explained by a simple heuristic such as fix-and-sample., (Copyright (c) 2009 Elsevier B.V. All rights reserved.)

Using data from two conditions of an experiment that arranged response-contingent foods and red keylight illuminations, we compared time-indexed and response-indexed preference pulses. The interpretation of red keylight effects (relative to food effects) differed according to whether time or behaviour was used to index choice in the post-event period: preference after a red keylight was more extreme than after a food in the response pulses while preference after a food was more extreme than after a keylight in the time pulses. This was due to different response latencies following the two events in combination with a tendency for initial preference to decrease as latency increased: responding began sooner after non-foods and responding that began later, after any event, tended towards indifference. Our finding suggests that preference pulses ought to be indexed according to time since the last event delivery, particularly if the response-contingent events may result in systematically different response latencies., (Copyright (c) 2009 Elsevier B.V. All rights reserved.)

In the quantitative analysis of behaviour, choice data are most often plotted and analyzed as logarithmic transforms of ratios of responses and of ratios of reinforcers according to the generalized-matching relation, or its derivatives such as conditional-discrimination models. The relation between log choice ratios and log reinforcer ratios has normally been found using ordinary linear regression, which minimizes the sums of the squares of the y deviations from the fitted line. However, linear regression of this type requires that the log choice data be normally distributed, of equal variance for each log reinforcer ratio, and that the x (log reinforcer ratio) measures be fixed with no variance. We argue that, while log transformed choice data may be normally distributed, log reinforcer ratios do have variance, and because these measures derive from a binomial process, log reinforcer ratio distributions will be non-normal and skewed to more extreme values. These effects result in ordinary linear regression systematically underestimating generalized-matching sensitivity values, and in faulty parameter estimates from non-linear regression to assume hyperbolic and exponential decay processes. They also lead to model comparisons, which assume equal normally distributed error around every data point, being incorrect. We describe an alternative approach that can be used if the variance in choice is measured.