International Journal of Comparative Psychology

The study of human and animal behavior in psychology is almost always framed at either the associative or the cognitive level of explanation. Despite continued debate between proponents of each approach, we appear to be no closer to a consensus view than we were when the debate began in earnest in the 1960 s. Could it be that the two levels of explanation are irreconcilable? Or is it possible that both frameworks are useful, though incompatible? Perhaps these frameworks merely account for the same behaviors but at different levels of explanation, as characterized by hardware-software or genotype-phenotype analogies. This special issue provides a venue for contemporary scientists involved in this debate to express their views, and follows from a Focus Session of the same title held at the 2010 meeting of the Winter Conference in Animal Learning & Behavior.

The standard methodology of comparative psychology has long relied upon a distinction between cognition and ‘mere association’; cognitive explanations of nonhuman animals behaviors are only regarded as legitimate if associative explanations for these behaviors have been painstakingly ruled out. Over the last ten years, however, a crisis has broken out over the distinction, with researchers increasingly unsure how to apply it in practice. In particular, a recent generation of psychological models appear to satisfy existing criteria for both cognition and association. Salvaging the standard methodology of comparative psychology will thus require significant conceptual redeployment . In this article, I trace the historical development of the distinction in comparative psychology,distinguishing two styles of approach. The first style tries to make out the distinction in terms of the properties of psychological models, for example by focusing on criteria like the presence of rules & propositions vs. links & nodes. The second style of approach attempts to operationalize the distinction by use of specific experimental tests for cognition performed on actual animals. I argue that neither style of criteria is self-sufficient, and both must cooperate in an iterative empirical investigation into the nature of animal minds if the distinction is to be reformed.

One particular concern of the 2010 Winter Conference on Animal Learning and Behaviour was the degree to which the behaviours of human and nonhuman animals might be interpreted as the result ofthe same cognitive mechanisms. Here, we examine three examples in rats (causal-reasoning, sensitivity to the absence of stimuli, and the relationship between effort and reward) where higher ordermental processes might be invoked as explanations of the observed behaviour. In each case we argue that alternative accounts, based on “lower” mental processes, are also consistent with the observed data. On the basis of the principle of parsimony, enshrined as a grounding assumption of comparative psychology in C. Lloyd Morgan’s Canon, the existence of such alternative accounts means that the available evidence does not licence the conclusion that non-human animals display evidence of human-like cognitive processes in these areas.

The propositional or rationalist Bayesian approach to learning is contrasted with an interpretation of causal learning in associative terms. A review of the development of the use of rational causal models in the psychology of learning is discussed concluding with the presentation of three areas of research related to cause-effect learning. We explain how rational context choices, a selective association effect (i.e., blocking of inhibition) as well as causal structure can all emerge from processes that can be modeled using elements of standard associative theory. We present the auto-associator (e.g., Baetu & Baker, 2009) as one such simple account of causal structure.

This paper reviews some of the literature on Pavlovian and instrumental conditioning as they relate to“cognitive” factors in behavior. Studies of Pavlovian learning have centered around the notion that a representation of the unconditioned stimulus plays a critical role in performance. However, much work will need to go into characterizing the nature of the representations that mediate learning. In particular, current research illustrates that “images” and “expectancies” of reward may differ in fundamental ways, and also that learning about temporal, motivational, and sensory properties of reward might involve different systems. The study of instrumental learning also poses challenges for addressing the question of what representations, i.e., associative structures, underlie such learning.Current work reveals a host of associative structures that may participate in learning and performance though how these different structures participate in a unified approach is currently unknown. The associative approach can be contrasted with inferential reasoning approaches to instrumental action, and there are two key findings that seem outside the scope of a reasoning approach. Nevertheless, future work will be required to determine just how far purely associative models will be able to go in order to account for complex behavior.

The interface of learning and cognition applied to the study of animal behavior represents a target for significant progress if conceptual barriers can be reduced. Is animal behavior exclusively a product of learning or cognition, or are both implicated? Are special (i.e., new) methods required to study cognition or will the enterprise be accomplished by using well-established methods from learning? What types of hypotheses need to be tested to dissociate cognition from learning, and may these hypotheses be profitably tested? This article addresses the above questions by focusing on conceptual, methodological, and hypothesis-testing perspectives for navigating the interface between learning and cognition. Examples from contemporary research are used to develop some suggestions for best practices. The development of a rodent model of episodic memory is used as a case study tofeature the validation of an animal model of cognition.

Evidence from serial pattern learning research has been used to support the controversial claim that rats detect, encode, and use abstract rules. To understand why the evidence indicates that rats’ “rules”are abstract, we examine the basis of “pattern structure” in sequential tasks, how rats respond to pattern structure in highly-organized sequences, the role of “rules” in rats’ representation of patterned sequences, and the notion that rats’ “rules” differ from generalization. We show that “pattern structure” reflects systematic abstractions from stimuli that can be described by abstract relationships,that rats are flexible in representing sequential patterns, that rats use “rules” along with other forms of representation concurrently in serial pattern learning, and that associative/generalization models do not always predict rats’ “rule-governed” behavior. Both behavioral and neurobiological evidence suggest that “rules” are not simply emergent properties of associative networks, that instead rule abstraction and associative processes are mediated by separate concurrently active systems in serial pattern learning. It is not known how “rules” are instantiated in the nervous system, and a key problem at a more molar level of analysis is what determines the output of multiple concurrently active cognitive systems in serial pattern learning.