Taming the boojum: Being theoretical about peculiarities of learning.

The case of the "biological constraints" movement in mid-20th-century psychology provides a reminder of the weight of psychology's reliance on theory and theory-driven methods. By 1980, a critical mass of demonstrations of the specificity of learning had eroded faith in general-process approaches. A common reaction was to call for a biological orientation. However, this proved not as straightforward as it had seemed, and much of the ostensibly biological research that followed was atheoretical. The successes in this context were due to careful theoretical work by people who appreciated the aims of the involved sciences and the interdependence of the aims with methods. Michael Domjan slowed the field's haphazard rush into ostensible biological research, and rather urged adoption of principled biological approaches. In 1982, his positive recommendation was for comparative psychology to begin to live up to its name, and adopt principled comparative methods as practised in biology. Although lauded, few followed this recommendation. Indeed, even Domjan's own subsequent research was mostly not comparative in the way he had described, but rather involved single species, guided by a behaviour systems approach. With reference to two major perspectives associated with Domjan-comparative methods and behaviour systems theory-I present Domjan's challenge not as being to make our field comparative per se, but to make it theoretical. This challenge remains current.

William D. Timberlake (1942-2019).

Presents the obituary of William D. Timberlake (1942-2019). William David Timberlake contributed to psychology in many ways. He is best known for his behavior systems approach to learning and for his disequilibrium theory of reinforcement. He also made important contributions to behavioral economics, circadian rhythms, time horizons, adjunctive behavior, and contrast effects. In these pursuits and others, Timberlake brought clarity to vexing theoretical problems through careful attention to the species-typical characters of the subjects and how these interact with the specifics of apparatus and procedures. He focused on understanding the animals as animals (what he called a theromorphic approach). Timberlake embraced the complexity of behavior, its organization, and its relation to the body as part of a whole, functioning organism (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Six clarifications for behaviour systems.

The precursors of contemporary behaviour systems theory were hotly debated, and yet a similar critical fervour has not followed the second generation of behaviour systems research. I raise six items of potential or extant misunderstanding concerning behaviour systems perspectives, and attempt to set straight some of the assumptions and what motivated them, with attention to historical and theoretical context. The six challenges in focus are: 1) variety of conceptualisation of consummation; 2) potential misapprehensions about the role of general search; 3) ambiguity of predictions concerning response form; 4) ambiguity concerning what aspects are modelled as hierarchical; 5) assumptions of directedness; and 6) the relevance of spontaneous activity. For each of these six issues, some clarification is offered.

Causal reasoning in rats' behaviour systems.

Conceiving of stimuli and responses as causes and effects, and assuming that rats acquire representational models of causal relations from Pavlovian procedures, previous work by causal model theory proponents attempted to train rat subjects to represent stimulus A as a cause of both stimulus B and food. By these assumptions, with formal help from Bayesian networks, self-production of stimulus B should reduce expectation of alternative causes, including stimulus A, and their effects, including food. Reduced feeder-directed responding to stimulus B when self-produced has been taken as evidence for a general causal reasoning capacity among rats involving mental maps of causal relations. Critics have rejoined that response competition can explain these effects. The present research replicates the key effect, but uses continuous and finer-grained measurement of a broader range of behaviours. Behaviours not recorded in previous studies contradict both prior explanations. Even results cited in support of these explanations, when measured in finer detail and continuously over longer periods, show patterns not expected by either view, but supportive of a specific-process approach with attention to motivational factors. Still, the abstract prediction from Bayesian networks holds, providing a potentially complementary normative analysis. Behaviour systems theory provides firmer framing for such theories than representational-map alternatives.

Do rats learn conditional independence?

If acquired associations are to accurately represent real relevance relations, there is motivation for the hypothesis that learning will, in some circumstances, be more appropriately modelled, not as direct dependence, but as conditional independence. In a serial compound conditioning experiment, two groups of rats were presented with a conditioned stimulus (CS1) that imperfectly (50%) predicted food, and was itself imperfectly predicted by a CS2. Groups differed in the proportion of CS2 presentations that were ultimately followed by food (25% versus 75%). Thus, the information presented regarding the relevance of CS2 to food was ambiguous between direct dependence and conditional independence (given CS1). If rats learnt that food was conditionally independent of CS2, given CS1, subjects of both groups should thereafter respond similarly to CS2 alone. Contrary to the conditionality hypothesis, subjects attended to the direct food predictability of CS2, suggesting that rats treat even distal stimuli in a CS sequence as immediately relevant to food, not conditional on an intermediate stimulus. These results urge caution in representing indirect associations as conditional associations, accentuate the theoretical weight of the Markov condition in graphical models, and challenge theories to articulate the conditions under which animals are expected to learn conditional associations, if ever.