Armando Machado

The process of recurrent choice

Recurrent choice has been studied for many years. A static law, matching, has been established, but there is no consensus on the underlying dynamic process. The authors distinguish between dynamic models in which the model state is identified with directly measurable behavioral properties (performance models) and models in which the relation between behavior and state is indirect (state models). Most popular dynamic choice models are local, performance models. The authors show that behavior in different types of discrimination-reversal experiments and in extinction is not explained by 2 versions of a popular local model and that the nonlocal cumulative-effects model is consistent with matching and that it can duplicate the major properties of recurrent choice in a set of discrimination-reversal experiments. The model can also duplicate results from several other experiments on extinction after complex discrimination training.

Toward a Richer View of the Scientific Method The Role of Conceptual Analysis

Within the complex set of activities that comprise the scientific method, three clusters of activities can be recognized: experimentation, mathematization, and conceptual analysis. In psychology, the first two of these clusters are well-known and valued, but the third seems less known and valued. The authors show the value of these three clusters of scientific method activities in the works of the quintessential scientist Galileo Galilei. They then illustrate how conceptual analysis can be used in psychology to clarify the grammar and meaning of concepts, expose conceptual problems in models, reveal unacknowledged assumptions and steps in arguments, and evaluate the consistency of theoretical accounts. The article concludes with a discussion of three criticisms of conceptual analysis.

Learning to Time: a perspective.

In the last decades, researchers have proposed a large number of theoretical models of timing. These models make different assumptions concerning how animals learn to time events and how such learning is represented in memory. However, few studies have examined these different assumptions either empirically or conceptually. For knowledge to accumulate, variation in theoretical models must be accompanied by selection of models and model ideas. To that end, we review two timing models, Scalar Expectancy Theory (SET), the dominant model in the field, and the Learning-to-Time (LeT) model, one of the few models dealing explicitly with learning. In the first part of this article, we describe how each model works in prototypical concurrent and retrospective timing tasks, identify their structural similarities, and classify their differences concerning temporal learning and memory. In the second part, we review a series of studies that examined these differences and conclude that both the memory structure postulated by SET and the state dynamics postulated by LeT are probably incorrect. In the third part, we propose a hybrid model that may improve on its parents. The hybrid model accounts for the typical findings in fixed-interval schedules, the peak procedure, mixed fixed interval schedules, simple and double temporal bisection, and temporal generalization tasks. In the fourth and last part, we identify seven challenges that any timing model must meet.

Testing the scalar expectancy theory (SET) and the learning-to-time model (LeT) in a double bisection task

Two theories of timing, scalar expectancy theory (SET) and learning-to-time (LeT), make substantially different assumptions about what animals learn in temporal tasks. In a test of these assumptions, pigeons learned two temporal discriminations. On Type 1 trials, they learned to choose a red key after a 1-sec signal and a green key after a 4-sec signal; on Type 2 trials, they learned to choose a blue key after a 4-sec signal and a yellow key after either an 8-sec signal (Group 8) or a 16-sec signal (Group 16). Then, the birds were exposed to signals 1 sec, 4 sec, and 16 sec in length and given a choice between novel key combinations (red or green vs. blue or yellow). The choice between the green key and the blue key was of particular significance because both keys were associated with the same 4-sec signal. Whereas SET predicted no effect of the test signal duration on choice, LeT predicted that preference for green would increase monotonically with the length of the signal but would do so faster for Group 8 than for Group 16. The results were consistent with LeT, but not with SET.

Acquisition and extinction under periodic reinforcement

This study reexamined the processes of acquisition and extinction under periodic reinforcement. During the first phase of the experiment, pigeons were exposed to a fixed-interval schedule either 40 or 80 s long. During the second phase, each session started with the fixed-interval schedule but changed to extinction at an unpredictable moment. The results showed that during phase 1 the curve for the average rate of pecking along the interval rotated across sessions, that is, the rate immediately after food decreased, whereas the rate at the end of the interval increased. The initial and terminal rates approached their steady state at different speeds. During the extinction trials of phase 2, behavior was characterized by pause-peck oscillations with a period slightly longer than the fixed-interval duration. These findings concerning acquisition and extinction under periodic reinforcement were then compared with the predictions of some current theories of timing.

Further tests of the Scalar Expectancy Theory (SET) and the Learning-to-Time (LeT) model in a temporal bisection task.

To contrast two models of timing, Scalar Expectancy Theory (SET) and Learning to Time (LeT), pigeons were exposed to a double temporal bisection procedure. On half of the trials, they learned to choose a red key after a 1s signal and a green key after a 4s signal; on the other half of the trials, they learned to choose a blue key after a 4-s signal and a yellow key after a 16-s signal. This was Phase A of an ABA design. On Phase B, the pigeons were divided into two groups and exposed to a new bisection task in which the signals ranged from 1 to 16s and the choice keys were blue and green. One group was reinforced for choosing blue after 1-s signals and green after 16-s signals and the other group was reinforced for the opposite mapping (green after 1-s signals and blue after 16-s signals). Whereas SET predicted no differences between the groups, LeT predicted that the former group would learn the new discrimination faster than the latter group. The results were consistent with LeT. Finally, the pigeons returned to Phase A. Only LeT made specific predictions regarding the reacquisition of the four temporal discriminations. These predictions were only partly consistent with the results.

Polymorphic response patterns under frequency-dependent selection

In a discrete-trials procedure, a frequency-dependent schedule shaped left-right choice proportion toward various equilibrium values between 0 and 1. At issue was (1) whether pigeons match when the overall reinforcement probabilities for two responses depend inversely on their recent frequency, and (2) how pigeons meet the schedule constraint in terms of local responding. That is, do they respond quasi-randomly (Bernoulli mode), or do they learn the stable pattern of the schedule (stable-pattern mode)? Molar choice behavior always tracked the equilibrium solution of the schedule, but the molecular response patterns varied substantially. Markov chains applied to the data revealed that responding was generally intermediate between the memoryless Bernoulli mode, and the perfect memory stable-pattern mode. The polymorphism of molecular patterns, despite molar regularities in behavior, suggests that (1) in order to engender the Bernoulli or stable-pattern modes, the reinforcement rule must strongly discourage competing response patterns (e.g., perseveration), and (2) under frequency-dependent schedules, molar matching is apparently not the outcome of momentary maximizing.

Context effects in a temporal discrimination task" further tests of the Scalar Expectancy Theory and Learning-to-Time models.

Pigeons were trained on two temporal bisection tasks, which alternated every two sessions. In the first task, they learned to choose a red key after a 1-s signal and a green key after a 4-s signal; in the second task, they learned to choose a blue key after a 4-s signal and a yellow key after a 16-s signal. Then the pigeons were exposed to a series of test trials in order to contrast two timing models, Learning-to-Time (LeT) and Scalar Expectancy Theory (SET). The models made substantially different predictions particularly for the test trials in which the sample duration ranged from 1 s to 16 s and the choice keys were Green and Blue, the keys associated with the same 4-s samples: LeT predicted that preference for Green should increase with sample duration, a context effect, but SET predicted that preference for Green should not vary with sample duration. The results were consistent with LeT. The present study adds to the literature the finding that the context effect occurs even when the two basic discriminations are never combined in the same session.

ASSOCIATIVE SYMMETRY BY PIGEONS AFTER FEW‐EXEMPLAR TRAINING

The present experiment investigated whether pigeons can show associative symmetry on a two-alternative matching-to-sample procedure. The procedure consisted of a within-subject sequence of training and testing with reinforcement, and it provided (a) exemplars of symmetrical responding, and (b) all prerequisite discriminations among test samples and comparisons. After pigeons had learned two arbitrary-matching tasks (A-B and C-D), they were given a reinforced symmetry test for half of the baseline relations (B1-A1 and D1-C1). To control for the effects of reinforcement during testing, two novel, nonsymmetrical responses were concurrently reinforced using the other baseline stimuli (D2-A2 and B2-C2). Pigeons matched at chance on both types of relations, thus indicating no evidence for symmetry. These symmetrical and nonsymmetrical relations were then directly trained in order to provide exemplars of symmetry and all prerequisite discriminations for a second test. The symmetrical test relations were now B2-A2 and D2-C2 and the nonsymmetrical relations were D1-A1 and B1-C1. On this test, 1 pigeon showed clear evidence of symmetry, 2 pigeons showed weak evidence, and 1 pigeon showed no evidence. The previous training of all prerequisite discriminations among stimuli, and the within-subject control for testing with reinforcement seem to have set favorable conditions for the emergence of symmetry in nonhumans. However, the variability across subjects shows that methodological variables still remain to be controlled.

Shifts in the psychophysical function in rats

The primary goal was to compare results from a free-operant procedure with pigeons [Machado, A., Guilhardi, P., 2000. Shifts in the psychometric function and their implications for models of timing. J. Exp. Anal. Behav. 74, 25-54, Experiment 2] with new results obtained with rats. The secondary goal was to compare the results of both experiments with dependent variables that were not used in the original publication. As in the original study with pigeons, rats were trained on a two-alternative free-operant psychophysical procedure in which left lever press responses were reinforced during the first and second quarters of a 60-s trial, and right lever press responses were reinforced during the third and fourth quarters of the trial. The quarters were reinforced according to four independent variable interval (VI) schedules of reinforcement. The VI duration was manipulated in each quarter, and shifts in the psychophysical functions that relate response rate with time since trial onset were measured. The results obtained with rats were consistent with those previously obtained with pigeons. In addition, results not originally reported were also consistent between rats and pigeons, and provided insights into the perception, memory, and decision processes in Scalar Expectancy Theory and Learning-to-Time Theory.