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This chapter presents a response to the commentaries in Chapters 28–31. It addresses the four points raised by Besson and Schön on their comments questioning the usefulness of the modularity frame. Skoe and Kraus provide a useful reminder and compelling case for considering that cortical modules do not function in isolation from subcortical neural systems. They remind us of the importance of top-down processing or corticofugal influences on the early tuning of brainstem responses to auditory input. Goswami draws attention to the role of prosody and rhythm in both music and speech from development and animal cognition. This chapter thanks Goswami for bringing to attention a study in which auditory chimera were created by interchanging sentences for melodies in using the envelope of one sentence or melody and the fine time structure of another.

A great deal of cognitive problem solving takes the form of thinking in mental imagery. This chapter illustrates these capacities and analyzes imagistic cognition into several aspects: object tracking, imagistic representation of causation, and perceptual similarity spaces, which include acquired dimensions grounded in representations of particular objects. The chapter also argues that the cognitive powers of nonhuman animals and prelinguistic human infants are limited to imagistic cognition. As case studies, the chapter examines the achievements of infants in Paul C. Quinn's experiments and the achievements of chimpanzees in Sue Savage‐Rumbaugh's experiments and argues that they can be explained in terms of imagistic cognition.

“Near-persons” are like persons insofar as they have a robust, conscious sense of their past and future, and this ability gives their lives special moral significance in comparison to “merely sentient” individuals which lack this ability. This chapter surveys the available scientific evidence for episodic memory, mirror self-recognition, and the use of a theory of mind and certain other kinds of planning in a range of non-human animals. This chapter concludes that while “the usual suspects” (great apes, elephants, and cetaceans) are good candidates for near-personhood, there is at least one surprising “contender” (scrub jays) and that we may one day have strong evidence for a much wider range of mammals and birds.

Why do animals attend to the lives of others? Social situations have provided important pressures in the evolution of behavior. In fact, some have argued that the complexities of social life require sophisticated mental abilities such that individuals of highly social species will evolve intelligent ways to cope with this complexity. The chapter explores three key components critical for social decision making. First, although the social milieu might be complex and ever changing, the use of simple decision mechanisms such as heuristics or “rules of thumb” may allow animals to navigate this complexity. Simple rules can provide good responses to complex problems. Reasonable decision mechanisms cannot be developed without considering the requisite cognitive capacities needed to implement these mechanisms. For example, investigating these cognitive capacities has been useful in reassessing the decision mechanisms used in cooperative situations. Finally, the animal literature is particularly useful for testing questions of ecological rationality—where decision rules are adapted to the structure of the physical and social environment—because different species have evolved in different environments. Each species' environment may uniquely shape its decision processes, and the social environment is a particularly important selective force on decision making. In summary, decision mechanisms, cognitive capacities, and the environment of a species must be investigated to understand properly its decisions. This perspective integrates the evolutionary and cognitive study of decision making to explore how animals navigate the complexities of their social worlds.

It has long been hypothesized that the demands of establishing and maintaining social relationships in complex societies place strong selective pressures on cognition and intelligence. What has been less clear is whether these relationships, and the skills they require, confer any reproductive benefits, and whether such benefits vary across individuals. Over the last few years, much progress has been made in resolving some of these questions. There is now evidence from a variety of species that animals are motivated to establish close, long-term bonds with specific partners, and that these bonds enhance longevity and offspring survival. The cognitive and emotional mechanisms underlying cooperation, however, are still not understood. Most investigations with captive primates indicate that cooperation is seldom contingency-based; however, several experiments conducted under more natural conditions suggest that animals do take into account recent interactions when supporting others. Pairs with strong bonds have strongly reciprocal interactions over extended time periods. These results suggest that the apparent rarity of contingent cooperation in animals may not stem from cognitive constraints. Instead, animals may tolerate short-term inequities in favors given and received because most cooperation occurs among long-term reciprocating partners.

Human language and cognition are often described as having the property of displacement. Displacement may be both temporal and spatial. Thus, we may think or communicate about events that occurred at some time in the past or that will occur at some time in the future. This ability is referred to as cognitive time travel, and memories of personal events that occurred at specific times in the past are referred to as episodic memories. People also can think or communicate about places distant from their current location, and we might call this cognitive spatial travel. This chapter examines whether these displacement abilities of humans can be found in animals. With regard to the temporal displacement question, it considers the hypothesis that animals are “stuck in time.” A parallel “stuck-in-space” hypothesis may be advanced regarding spatial displacement. This chapter reviews some of the evidence on the stuck-in-time hypothesis concerning both the possibility of episodic memory in animals and the anticipation of future events. The questions of temporal and spatial displacement in animal cognition are discussed.

This chapter outlines the different types of question posed by the forms of psychological explanations of the behavior of nonlinguistic creatures given in various parts of the cognitive and behavioral sciences. Due to the cognitive turn in the behavioral and cognitive sciences in the modern age, high-level cognitive abilities are being investigated in an ever-increasing number of species and at earliest stages of human development. This chapter explores the development in the scientific study of human characteristics and animal behavior. The new discipline of cognitive ethology is essential in the study of the mental states of animals and of how those mental states manifest themselves in behavior. The three areas of cognitive ethology, developmental, psychological, and cognitive archaeology are becoming ever more closely integrated. Research into animal cognition is now employing the dishabituation paradigm.

The chapter tackles the placement of self-reflective consciousness amongst the numberless gradations by Darwin. Discussions of self-consciousness inevitably lead to Descartes' dictum, “I think, therefore I am”. The goal is a rapprochement between this view and the Cartesian view, emphasizing this kind of consciousness applicable only to humans. Descartes maintained that animals are unable to engage in self-reflection. Negative results of various ape language projects and broad advances in animal cognition suggest that Descartes was right about the uniqueness of language but that he was wrong about animal's capacity for thought and self-reflection. There is abundant evidence that nonhuman pirates can form representations and use them to solve problems. The concept of autonoetic consciousness, as Tulving calls it, seemed close to the construct of self-reflective consciousness and metacognition which was the concern. Thus, instead of focusing on language, more fundamental capabilities are considered—the origins of self-reflective consciousness.

Part of the rationale for this chapter was that the exploration of animal cognition might give some insight into such questions as whether some animals might be conscious, and some not, and whether some animals might be more conscious than others. It is seen that associative processes are ubiquitous in animals, and have been unable to find evidence for a significant ‘leap’ in cognition between one animal species and another — with one exception. If there is a strong link between consciousness and cognition, this suggests a difference in consciousness between animals and humans. But whether cognition is related to consciousness is an interesting question. Is language merely a cognitive leap, or is it the Rubicon between unconsciousness and consciousness? This is the central question that this chapter attempts to explore.

‘Phonology in Evolutionary Perspective’ discusses the evolution of language, the properties of phonological computation, and the linguistic externalization system, using animal cognition studies to identify which components of phonology may not be unique to humans and/or to language. It demonstrates on the basis of behavioral and physiological studies on primates, songbirds, and a wide variety of other species that the cognitive abilities underlying human phonological representations and operations are present in creatures other than humans and in domains other than language.

This chapter discusses the results of experiments that investigated animal cognition in an integrative fashion by combining the methodology and insights of experimental psychology and evolutionary biology. This combination can be extraordinarily fruitful, yielding novel perspectives that can be applied broadly to the study of animal learning and memory. The chapter focuses on selective attention, priming, and foraging behavior in animals, along with spatial cognition and transitive inference. Considerations of how foraging animals might use selective attention while searching for cryptic prey have resulted in interesting questions that focus on the mechanisms of selective attention. Two naturally occurring foraging patterns, hunting by expectation and searching image, are related to two phenomena studied under laboratory conditions, associative priming and sequential priming.

The current ecological crisis is of enormous relevance to psychology teaching, as it is essentially a problem of human behaviour. Despite this, psychology has been slow to contribute. As a result, our environmental problems deepen, while our knowledge, skills and values as teachers of psychology remain largely untapped. This chapter urges psychology educators to consider how they can nurture the psychologically literate citizen through a focus on ecological sustainability. We present four case studies from New Zealand psychology departments. Two are laboratory exercises, one based on a social dilemma, the Tragedy of the Commons, and the other on perceptions of animal cognition. The third is a fourth year class that is open to students from different disciplines. The final case study is an action research and teaching project designed to create a sustainable school. Participating in these experiences highlights for students the ecological issues faced by people everywhere, how to cooperate in the sustainable and equitable use of resources, how cognitions and moral reasoning are affected by culture and how to use one’s psychological literacy to effect social change.

The Centre for Adaptive Behavior and Cognition (ABC) has hypothesized that much human decision making can be described by simple algorithmic process models (heuristics). This chapter explains this approach and relates it to research in biology on rules of thumb, which we also review. As an example of a simple heuristic, consider the lexicographic strategy of take-the-best for choosing between two alternatives: Cues are searched in turn until one discriminates, then search stops and all other cues are ignored. Heuristics consist of building blocks, and building blocks exploit evolved or learned abilities such as recognition memory; it is the complexity of these abilities that allows the heuristics to be simple. Simple heuristics have an advantage in making decisions fast and with little information, and in avoiding overfitting. Furthermore, humans are observed to use simple heuristics. Simulations show that the statistical structures of different environments affect which heuristics perform better, a relationship referred to as ecological rationality. We contrast ecological rationality with the stronger claim of adaptation. Rules of thumb from biology provide clearer examples of adaptation because animals can be studied in the environments in which they evolved. The range of examples is also much more diverse. To investigate them, biologists have sometimes used similar simulation techniques to ABC, but many examples depend on empirically driven approaches. ABC's theoretical framework can be useful in connecting some of these examples, particularly the scattered literature on how information from different cues is integrated. Optimality modeling is usually used to explain less detailed aspects of behavior but might more often be redirected to investigate rules of thumb.

Serial learning is one of the oldest and most widely studied phenomena of experimental psychology. Lashley argued that chaining theory could not account for knowledge of relationships between non-adjacent items in serially organized behavior. Hierarchical organization, a level of complexity that cannot be derived from chaining theory, is central to the concept of chunking and contemporary theories of language. Because Lashley did not use examples of animal behavior in his critique of chaining theory, its implication for animal cognition is less clear than it is for human cognition. Recent advances in our understanding of serially organized behavior in animals have confirmed that Lashley's critique of chaining theory applies with the same force to sequence learning by animals as it does to sequence learning by humans. Maze learning is the classic example of sequential learning by animals. This chapter discusses simultaneous chains and compares them with cognitive maps. It presents results of experiments that studied serially organized behavior in pigeons and monkeys.

This chapter first establishes a ‘baseline’ of animal cognition, against which to compare the cognition of great apes. The proper group to use for this is the Old World monkeys, diverging from the ape line at about 30 Ma. Then, evidence that great apes differ cognitively from monkeys is reviewed. Unfortunately, as yet the picture of cognitive differences between the various great apes is sketchy; the pattern seen in recent years is for an ability, first detected with the much-studied common chimpanzee, to be later found in other, and perhaps all, ape species. Once the genuine differences among the apes are worked out, it will be possible to trace human cognitive evolution in some detail from 14 Ma to 5 Ma, but at present this would be premature speculation.

This chapter compares cognitive and associative accounts of behaviour by animals on transitive inference tasks. It explains that transitive relationships are often important to animals and that transitive inference would permit an animal to behave in a way appropriate to the dominance relation between other animals even if their relationship has not been directly ascertained. It illustrates a more general methodological dispute between ethological and experimental approaches to animal cognition.