This essay in the “anthropology of science” is about how cognition constrains culture in producing science. The example is folk biology, whose cultural recurrence issues from the very same domain-specific cognitive universals that provide the historical backbone of systematic biology. Humans everywhere think about plants and animals in highly structured ways. People have similar folk-biological taxonomies composed of essence-based, species-like groups and the ranking of species into lower- and higher-order groups. Such taxonomies are not as arbitrary in structure and content, nor as variable across cultures, as the assembly of entities into cosmologies, materials, or social groups. These structures are routine products of our “habits of mind,” which may in part be naturally selected to grasp relevant and recurrent “habits of the world.” An experiment illustrates that the same taxonomic rank is preferred for making biological inferences in two diverse populations: Lowland Maya and Midwest Americans. These findings cannot be explained by domain-general models of similarity because such models cannot account for why both cultures prefer species-like groups, although Americans have relatively little actual knowledge or experience at this level. This supports a modular view of folk biology as a core domain of human knowledge and as a special player, or “core meme,” in the selection processes by which cultures evolve. Structural aspects of folk taxonomy provide people in different cultures with the built-in constraints and flexibility that allow them to understand and respond appropriately to different cultural and ecological settings. Another set of reasoning experiments shows that Maya, American folk, and scientists use similarly structured taxonomies in somewhat different ways to extend their understanding of the world in the face of uncertainty. Although folk and scientific taxonomies diverge historically, they continue to interact. The theory of evolution may ultimately dispense with the core concepts of folk biology, including species, taxonomy, and teleology; in practice, however, these may remain indispensable to doing scientific work. Moreover, theory-driven scientific knowledge cannot simply replace folk knowledge in everyday life. Folk-biological knowledge is not driven by implicit or inchoate theories of the sort science aims to make more accurate and perfect.

Byrne & Russon propose an account of imitation that mirrors levels of behavioral organization, but they perpetuate a tendency to dismiss imitation by members of most species as the result of more primitive processes, even though these alternative phenomena are often poorly understood. They argue that the prerequisites to program-level imitation are present in great apes, but the same prerequisites appear to be present in a broad range of species. The distribution of imitative capacity across species may be more limited by research methodology than by cognitive ability.

Two issues are addressed in this commentary: the universality and the “psychological reality” of locus equations as cues to place of articulation. Preliminary data collected in our laboratory suggest that locus equations do not reliably distinguish place of articulation for fricatives. Additionally, perception studies show that listeners can identify place of articulation based on much less temporal information than that required for deriving locus equations.

Investigations of innate talent should narrow the definition of talent to deal with constituent abilities, identify touchstone phenomena, and provide detailed explanations of these phenomena. A list of relevant phenomena is proposed.

Differences in mutation rates, transmission chain-length, phenotypic manifestations, or the relative complexity of the mental representations in which they are embedded do not distinguish between “core” (intramodular) and “developing” (intermodular) memes, as Atran suggests. Dividing memes into types seems premature when our knowledge of mental representation is as imprecise as the unit of biological inheritance was in Darwin's time.

Much of Halford et al.'s discussion of vector models for representing relations concerns the perceived inadequacies of alternative methods with respect to chunking, binding, systematicity, and resource requirements. Vector-based models for storing relations are in their infancy, however, and the relative merits of different schemes are not so clearly in favor of their STAR scheme as Halford et al. portray.

The effort to understand speech perception on the basis of relationships between acoustic parameters of speech sounds is to be recommended. Neural specializations (combination-sensitivity) for echolocation, communication, and sound localization probably constitute the common mechanisms of vertebrate auditory processing and may be essential for speech production as well as perception. There is, however, no need for meaningful maps.

The target article by Byrne & Russon treats imitation as an achievement that originates from observation. In my commentary I propose extending the database to the role of listening. Referring to current studies on song learning in birds, I suggest that at least some features of this accomplishment also may be based on learning by imitation.

Clear evidence of large individual differences in children's performance in talent areas can be explained either in terms of innate gifts (the “talent account”) or in terms of early exposure (the “no talent account” proposed by Howe et al.). At this point, there is no conclusive support for either account, and it is doubtful that talent could be explained exclusively by only one of them.

Semantic realism fits Millikan's account of kind terms in its focus on information-theoretic abilities and strategic ways of gathering information in human communication. Instead of the traditional logical necessity, we should interpret rigid designation in a dynamic semantics as a legislative act to constrain possible ways in which our belief may change.

Byrne & Russon redefine the process of emulation learning as “goal emulation” and thereby distort its most distinctive characteristic: the criterion that the observer focuses on environmental rather than behavioral processes. The two empirical examples recounted – gorilla plant processing and orangutan manipulation of human artifacts – are hierarchically organized behaviors, but there is very little evidence that they involve imitative learning, program-level or otherwise.

The position advocated in the target article should be called “absurd environmentalism.” Literature showing that general intelligence is related to musical ability is not cited. Also ignored is the heritability of musical talent. Retrospective studies supporting practice over talent are incapable of showing differences in talent, because subjects are self-selected on talent. Reasons for the popularity of absurd environmentalism are discussed.

Although neural encoding by bats and owls presents seductive analogies, the major contribution of locus equations and orderly output constraints discussed by Sussman et al. is the demonstration that important acoustic information for speech perception can be captured by elegant and neurally-plausible learning processes.

Atran's account of cultural transmission can be further refined by considering constraints from early-developed, domain-specific intuitive ontological understanding. These suggest specific predictions about the cultural survival of “memes,” depending on the way they activate intuitive understanding. There is no general dynamic of cultural inheritance; only complex predictions for domain-specific competencies that cut across cultural domains.

Evidence from language acquisition suggests that words are powerful mechanisms in the acquisition of substance concepts. Infants initially approach language with the general expectation that words refer to real kinds, regardless of grammatical cues to the contrary.

The metric devised by Halford, Wilson & Phillips may have considerable potential in distinguishing between the working memory demands of different tasks but may be less effective in distinguishing working memory capacity between individuals. Despite the strengths of the metric, determining whether an effect is caused by relational complexity or by differential levels of expertise is currently problematic.

Halford et al.'s analysis of relational complexity provides a possible framework for characterizing the symbolic functions of the prefrontal cortex. Studies of prefrontal patients have revealed that their performance is selectively impaired on tasks that require integration of two binary relations (i.e., tasks that Halford et al.'s analysis would identify as three-dimensional). Analyses of relational complexity show promise of helping to understand the neural substrate of thinking.

A concern for cultural specificity, the staple of traditional anthropological research, survives the transition to domain-specific accounts of cognitive structuring such as Atran's, and is arguably better off for having made the transition. The identification of domain-specific processes provide us with criteria for sorting cultural differences and integrating cultural concerns within cognitive science.

I have no problem with Millikan's saying that Mama, milk, and mouse are substances, but I do not see why this list cannot be extended with white, red cows, things, vovetas, lhenxa, GRUE, and so on. In the right circumstances, given the right training, the characteristics of substances that Millikan provides work equally well for each of them.

In the context of the motor skill literature on observational learning and hierarchical skill structuring, Byrne & Russon's findings call into question their standpoint that great apes imitate the behaviour of role models at the programme level. The authors impose a hierarchical model on their observations without properly considering alternative explanations. One such possibility, which stems from a constraints perspective that they dismiss, is put forward.