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This chapter examines the fundamental link between cognitive systems, movement, and the organization of the brain; what psychobiologist Karl Lashley emphasized in his essay on the “serial order of behavior” in which he also discusses music. Many different cognitive and motor systems fuel our ability to organize action, thought, and music. Musical expression is just one example of serial orders of behavior and diverse human creative expression. The chapter first considers the relationship between speech, song, and language in the evolutionary context before discussing how cognitive motor systems are embedded in language and gestures. It then looks at the neurotransmitter dopamine, a vital chemical for syntax, song, movement, discrepancy, and the prediction of reward. It also explains how, from an evolutionary point of view, the organization of thought is embedded in the organization of action. Finally, it provides an overview of procedural and declarative cognitive/memory systems.

This chapter lays the groundwork for discussing Psi theory and Micro Psi by giving a short introduction to the philosophical and methodological concepts of cognitive architectures, especially the computational theory of the mind and the language of thought hypothesis. It highlights how cognitive models have been established in artificial intelligence research and psychology as a paradigm of understanding the mind, and explains their current main families: symbolic, distributed, and neuro-symbolic models.

This chapter examines how music fits into the evolution of human cognitive capabilities and how the auditory system, larynx, motor systems, and cephalic expansion underlie musical expression as well as the evolution of social contact. The specific adaptation for decoding facial responses, and the more general aptitudes such as applying numerical capabilities to diverse problems, pervade a biological understanding of cognitive adaptation. Cognitive systems are distributed across neural systems that traverse the brain stem to the forebrain. The chapter first provides an overview of some of the core features of problem solving and human expression before discussing the concepts of time and calculations that are embedded in our cognitive capabilities. It also explores the importance of hearing and vocal expression for music and concludes by suggesting that the roots of music may be in the inherent shared features of our social brain.

This chapter proposes a systems-based principle of demarcation. A state is cognitive if and only if it is the state of a mechanism that is a component of an integrated cognitive system. Informal and formal descriptions of integration are given. The systems-based approach is claimed to yield a nonextended view in the case of the typical human, and to provide the best explanation of the success of standard experimental methods in cognitive psychology and cognitive neuroscience. Given the empirical facts, the systems-based view may entail some extended human cognition when applied; nevertheless, this is not likely to be of the sort that causes paradigm shift in the study of core cognitive phenomena. Objections are considered, and replies provided. Throughout, the following reply recurs: insofar as the extended view explains the extant success of cognitive psychology and related disciplines, it does so by recreating the structure of nonextended explanations.

This chapter explores a way in which visual processing may involve innate constraints and attempts to show how such processing overcomes one enduring challenge to nativism. In particular, many challenges to nativist theories in other areas of cognitive psychology (e.g., ‘theory of mind’, infant cognition) have focused on the later development of such abilities, and have argued that such development is in conflict with innate origins (since those origins would have to be somehow changed or overwritten). Innateness, in these contexts, is seen as antidevelopmental, associated instead with static processes and principles. In contrast, certain perceptual models demonstrate how the very same mental processes can both be innately specified and yet develop richly in response to experience with the environment. This process is entirely unmysterious, as shown in certain formal theories of visual perception, including those that appeal to spontaneous endogenous stimulation and those based on Bayesian inference.

This chapter summarizes the book's arguments against the extended view, as well as the primary conciliatory contentions advanced with regard to the embedded and embodied views. The chapter closes with comments on the positive importance of the embodied and embedded programs, particularly in respect of such philosophical issues as reductionism and naturalized epistemology.

This chapter argues that human and animal minds indeed depend on a collection of domain-specific, task-specific, and encapsulated cognitive systems: on a set of cognitive ‘modules’ in Fodor's sense. It also argues that human and animal minds are endowed with domain-general, central systems that orchestrate the information delivered by core knowledge systems. The chapter begins by reviewing the literature on spatial reorientation in animals and in young children, arguing that spatial reorientation bears the hallmarks of core knowledge and of modularity. It then considers studies of older children and adults, arguing that human spatial representations change qualitatively over development and show capacities not found in any other species. Finally, it presents two new experiments that investigate the role of emerging spatial language in uniquely human navigation performance.

The question that frames this chapter is how humans have managed to learn such amazing things as the age of the universe. After briefly reviewing logical, methodological, historical, and social approaches to this question, the chapter focuses on contributions of the cognitive study of science. This leads to a comparison of the cognitive study of science and the psychology of science, which study how fundamental cognitive mechanisms operate in the context of generating scientific knowledge. There is, however, a second way humans use their psychological powers in the pursuit of knowledge, namely, by designing material and symbolic artifacts that greatly increase their cognitive powers. The resulting physical-computational-human systems have been incorporated into the cognitive sciences as “distributed cognitive systems.” The chapter proposes adoption of an agent-centered approach, in which ever more ubiquitous distributed cognitive systems can be fully cognitive without being fully computational.

How do we reconcile the insights of the judgement theorists into emotion with the empirical data from the psychologists? Following the neuroscientist Joseph LeDoux, it is suggested that there are two different processing systems in emotion, a very rapid instinctive appraisal system that occurs too fast for cognitive mediation and a slower cognitive system that monitors the results of the fast affective non-cognitive system. An emotional response is a process in which a physiological response caused by an affective appraisal fastens attention on events in the (inner or outer) environment that are very significant to a person's (or animal's) survival and/or well-being, and prepares the person (animal) to deal with this situation. The affective appraisal is a coarse-grained appraisal that is in turn monitored by a more-fined cognitive appraisal.

This chapter is an introduction to Section 4 (Neuroscience). In the first chapter, the target article, resource-sharing framework for the comparative study of language and music is presented. Resource sharing is based on two principles: language and music involve domain-specific representations, and when similar cognitive processes are conducted on these representations, the brain shares neural resources between the two domains. This is followed by commentaries. The second target article focuses on modularity in language and music. That chapter suggests that an updated view of modularity can provide a useful framework within which to study cognitive systems (including language and music) and expands the modularity position to singing and speaking (hence, modularity in action), This is followed by commentaries.

In this chapter it is argued that the difficulty in understanding evolution by natural selection does not stem solely from the complexity of the theory. Rather, the difficulty in teaching, learning, and understanding evolutionary biology can be traced to a clash between the basic tenets of evolutionary theory and the basic architecture of the cognitive systems used to understand the world in general, and the biological world in particular. Evidence from cognitive psychology, developmental psychology, and cognitive anthropology is presented that shows that people naturally develop a sophisticated conceptual system, or folk biology, that allows us to intuitively categorize, reason about, and understand the biological world. These same intuitive ways of understanding the biological world may be largely responsible for the difficulty in teaching, learning and understanding evolution

Building on the cognitive-affective personality system (CAPS) framework offered by Mischel and Shoda (1995), the authors emphasize the importance of considering abstract properties of situations to improve behavioral prediction. The CAPS model incorporates a person-by-situation interactionist perspective, holding that specific features of situations activate specific cognitive and effective elements in individuals that then produce responses to situations. The authors argue that the notion of “situation” in the CAPS model is not at an appropriately abstract level to allow for a priori prediction of what specific cognitive-affective elements would be activated. To help overcome this limitation, they review recent developments by interdependence theorists to produce a comprehensive theory of situations. The authors describe six key dimensions of situations and review recent work on the risk regulation model, a model that describes the delicate balancing act of being dependent on a partner and the need to maintain positive feelings about the self.

From a Liberal Naturalists' point of view, the class of cognitive systems supporting experience must be like human cognition in certain sophisticated respects. Robert Kirk's basic package exemplifies this intuition as well and proposes that these elements are necessary conditions for the existence of consciousness. Thus, in this chapter, the author explores the idea of finding appropriate fundamental laws that meet a set of constraints like Kirk's and argues that these are unlikely. It also aims to examine whether other putative fundamental laws would have a character or consequences less implausible than panexperientialism itself. Two arguments will be presented by the author in this chapter.

This chapter revisits an old argument that theories of human emotion can give insight into the design and control of complex cognitive systems. In particular, it argues that appraisal theories of emotion provide essential insight into the influences of emotion over cognition and can help translate such findings into concrete guidance for the design of cognitive systems. According to appraisal theory, emotion plays a central and functional role in sensing external events, characterizing them as opportunity, or threats, and recruiting the cognitive, physical, and social resources needed to respond adaptively. In addition, because it argues for a close association between emotion and cognition, the theoretical claims of appraisal theory can be recast as a requirement specification for how to build a cognitive system. This specification asserts a set of judgments that must be supported to interpret correctly and to respond to stimuli and provides a unifying framework for integrating these judgments into a coherent physical or social response.

This chapter examines robot emotions from a functional perspective. It suggests that emotion-inspired mechanisms can improve the way autonomous robots operate in a human environment with people, and can improve the ability of these robots to effectively achieve their own goals. It describes the design of Kismet, an anthropomorphic robot that can interact with a human in a social way. Kismet's architecture includes a cognitive system that is tightly coupled to a separate emotive system, and each is designed as interacting networks of specialists that are activated when specific conditions are met.

Cerebral systems have proper procedures, which do not possess survival value (have no vital meaning). The concept of system turns out to be a sophistication of the notion of structure. As such a system does not need to be localized but can be distributed across several brain areas. Instead, functions (like behavior, learning, and memory) are (by definition) aimed at satisfying vital needs.

This chapter examines the basic principles governing emotional processing. It re-evaluates the concept of the limbic system and identifies the amygdala as a crucial component of the system involved in the acquisition, storage, and expression of fear memory. Amygdala acts as a species-specific danger detector that can be quickly activated by threatening stimuli, and that can be modulated by higher cognitive systems. The amygdala influences the cognitive system by way of projections to arousal centres that control the way actions and perceptions are performed.

This chapter discusses intentional systems. Cognitive systems such as language (speech, reading, and writing), spatial skills, and motor skills provide the knowledge of how to interact and operate within the environment, but they do not provide the knowledge of when to interact. There are three intentional, or “when,” decisions a normal person must make: when to act, when to continue acting or persist, and when not to act. The frontal lobes play a critical role in these decisions. The ability to carry out goal-oriented behavior requires both cognitive knowledge (stored primarily in the temporal and parietal lobes) and motivation or biological drives.

After some general considerations, this chapter discusses the phylogenetic brain stratification (the mammal’s brain becomes the center of the analysis), and study the brain as a system for integrating information from different sources and for developing coordinated behaviors.