Jablonka & Lamb's (J&L's) book is refreshing in that it debunks the exclusively gene-centered approach used these days to explain almost anything about life and human behavior. The book is very accessible and most convincing when the authors discuss biological theories of genetic and epigenetic inheritance, but it does not shy away from the more slippery terrain of behavioral and symbolic inheritance, and specifically the origins of language. But is the analogy appropriate?

Manipulations that draw attention to extensional or set-based considerations are neither sufficient nor necessary for enhanced use of base rates in intuitive judgments. Frequency formats are only one part of the puzzle of base-rate use and neglect. The conditions under which these and other manipulations promote base-rate use may be more parsimoniously organized under the broader notion of case-based judgment.

A well-recognized framework for modeling human intelligence centers around Spearman's g, a common central factor accounting for individual differences in cognitive performance across a variety of complex tasks (Spearman 1904). The neural basis of g may be better characterized by posterior-frontal integration, rather than parietal, which may be just one of many posterior regions that are controlled by the prefrontal cortex (PFC).

Byrne implies that working memory development underpins children's ability to represent counterfactuals as possibilities at 3 to 4 years of age. Recent findings suggest that (1) developments in the ability to consider alternatives to reality in children of this age are underpinned by improvements in inhibitory control, not working memory, and (2) children do not develop an understanding of counterfactuals as possibilities until mid-childhood.

Game theory provides a descriptive or a normative account of an important class of decisions. Given the cognitive sciences' emphasis on explanation, unification with the behavioral sciences under a descriptive model would constitute a step backwards in their development. I argue for the interdependence of the cognitive and behavioral sciences and suggest that meaningful integration is already occurring through problem-based interdisciplinary research programs.

Imagination and rational thought may be guided by identical principles, and Byrne's (2005) analysis expertly synthesizes a diverse literature on counterfactual thinking. Further attention should be paid to metacognitive experiences, like ease or difficulty of thought generation, which accompany the imaginative process. Only by considering metacognitive experiences along with the content of what people imagine can we fully understand imagination.

Intelligence studies are confounded by an inability to image the mind, as well as by heterogeneity in intelligence constructs, gender, and age. The ghost (of future, not past) sitting at the table is a molecular one. Biochemistry and molecular biology factors can contribute to or take away from intelligence to a great and not yet fully explored extent.

A strength of Jablonka & Lamb's (J&L's) book lies in its accessible as well as thorough treatment of genetic and epigenetic inheritance. The authors also provide a stimulating framework integrating evolutionary research across disciplines. A weakness is its unsystematic treatment of the interaction between behavioral and symbolic inheritance, particularly in their discussion of language.

Barbey & Sloman (B&S) advocate a dual-process (two-system) approach by comparing it with an alternative perspective (ecological rationality), claiming that the latter is unwarranted. Rejecting this alternative approach cannot serve as sufficient evidence for the viability of the former.

With a few incisive (and legitimate) criticisms of crucial experiments in psychology that purported to bring down the foundations of modern economics, together with a broad scholarly review that is praiseworthy, Gintis attempts to build a unifying framework for the behavioral sciences. His efforts fail, however, because he fails to break with the conventional methodology, which, regrettably, is the unifying basis of the behavioral sciences. As a result, his efforts will merely recapitulate the story of the past: interesting, provocative results that are soon overthrown because they are limited to the conditions of the experiment. Gintis is keenly aware of this limitation – and thus meets Brunswik, but fails to recognize him; this we know because he seems unaware of the fact that Brunswik said it all – and provided a detailed defense – a half century ago.

For Herbert Gintis, the “rational actor,” or “beliefs, preferences, and constraints (BPC),” model is central to his unifying framework for the behavioral sciences. It is not argued here that this model is refuted by evidence. Instead, this model relies ubiquitously on auxiliary assumptions, and is evacuated of much meaning when applied to both human and nonhuman organisms. An alternative perspective of “program-based behavior” is more consistent with evolutionary principles.

The hypothesis that structural properties and not frequencies per se improve base-rate sensitivity is supported from the perspective of natural sampling. Natural sampling uses a special frequency format that makes base-rates redundant. Unfortunately, however, it does not allow us to empirically investigate human understanding of essential properties of uncertainty – most importantly, the understanding of conditional probabilities in Bayes' Theorem.

Byrne's criteria for considering imagination rational do not accord with standard notions of rationality. A different criterion – that is, the correspondence between an inference strategy and its domain of application – is offered and illustrated with recent work on possibility judgment. This analysis suggests that, although imagination can be put to rational purposes, imagination itself should not be considered rational.

The commentaries on Evolution in Four Dimensions reflect views ranging from total adherence to gene-centered neo-Darwinism, to the acceptance of non-genetic and Lamarckian processes in evolution. We maintain that genetic, epigenetic, behavioral, and cultural variations have all been significant, and that the developmental aspects of heredity and evolution are an important bridge that can unite seemingly conflicting research programs and different disciplines.

Performance on abstract unfamiliar tasks used to measure intelligence has not been found to correlate with individual differences in highly skilled and expert performance. Given that cognitive and neural structures and regions mediating performance change as skill increases, the structures highlighted by parieto-frontal integration theory are unlikely to account for individual differences in skilled cognitive achievement in everyday life.

A parieto-frontal integration theory (P-FIT) model of human intelligence has been proposed based on a review of neuroimaging literature and lesion studies. The P-FIT model provides an important basis for future research. Future studies involving connectivity analyses and an integrative approach of imaging modalities using the P-FIT model should provide vastly increased understanding of the biological bases of intelligence.

Barbey & Sloman (B&S) attribute all instances of normative base-rate usage to a rule-based system, and all instances of neglect to an associative system. As it stands, this argument is too simplistic, and indeed fails to explain either good or bad performance on the classic Medical Diagnosis problem.

We critique the distinction Byrne makes between strong causes and enabling conditions, and its implications, on both theoretical and empirical grounds. First, we believe that the difference is psychological, not logical. Second, we disagree that there is a strict “dichotomy between the focus of counterfactual and causal thoughts.” Third, we disagree that it is easier for people to generate causes than counterfactuals.

Innovation is a key component of most definitions of culture and intelligence. Additionally, innovations may affect a species' ecology and evolution. Nonetheless, conceptual and empirical work on innovation has only recently begun. In particular, largely because the existing operational definition (first occurrence in a population) requires long-term studies of populations, there has been no systematic study of innovation in wild animals. To facilitate such study, we have produced a new definition of innovation: Innovation is the process that generates in an individual a novel learned behavior that is not simply a consequence of social learning or environmental induction. Using this definition, we propose a new operational approach for distinguishing innovations in the field. The operational criteria employ information from the following sources: (1) the behavior's geographic and local prevalence and individual frequency; (2) properties of the behavior, such as the social role of the behavior, the context in which the behavior is exhibited, and its similarity to other behaviors; (3) changes in the occurrence of the behavior over time; and (4) knowledge of spontaneous or experimentally induced behavior in captivity. These criteria do not require long-term studies at a single site, but information from multiple populations of a species will generally be needed. These criteria are systematized into a dichotomous key that can be used to assess whether a behavior observed in the field is likely to be an innovation.

The argument for unifying behavioral sciences can be enhanced by highlighting concrete, vivid, and useful benefits that coherent behavioral models could provide. Shifting sets of behavioral assumptions underlie every legal system's efforts to modify behaviors by changing incentives in the legal environment. Consequently, where those assumptions are flawed, improved behavioral models could improve law's effectiveness and efficiency in regulating behavior.