The phenomenon of base-rate neglect has elicited much debate. One arena of debate concerns how people make judgments under conditions of uncertainty. Another more controversial arena concerns human rationality. In this target article, we attempt to unpack the perspectives in the literature on both kinds of issues and evaluate their ability to explain existing data and their conceptual coherence. From this evaluation we conclude that the best account of the data should be framed in terms of a dual-process model of judgment, which attributes base-rate neglect to associative judgment strategies that fail to adequately represent the set structure of the problem. Base-rate neglect is reduced when problems are presented in a format that affords accurate representation in terms of nested sets of individuals.

The human imagination remains one of the last uncharted terrains of the mind. People often imagine how events might have turned out “if only” something had been different. The “fault lines” of reality, those aspects more readily changed, indicate that counterfactual thoughts are guided by the same principles as rational thoughts. In the past, rationality and imagination have been viewed as opposites. But research has shown that rational thought is more imaginative than cognitive scientists had supposed. In The Rational Imagination, I argue that imaginative thought is more rational than scientists have imagined. People exhibit remarkable similarities in the sorts of things they change in their mental representation of reality when they imagine how the facts could have turned out differently. For example, they tend to imagine alternatives to actions rather than inactions, events within their control rather than those beyond their control, and socially unacceptable events rather than acceptable ones. Their thoughts about how an event might have turned out differently lead them to judge that a strong causal relation exists between an antecedent event and the outcome, and their thoughts about how an event might have turned out the same lead them to judge that a weaker causal relation exists. In a simple temporal sequence, people tend to imagine alternatives to the most recent event. The central claim in the book is that counterfactual thoughts are organised along the same principles as rational thought. The idea that the counterfactual imagination is rational depends on three steps: (1) humans are capable of rational thought; (2) they make inferences by thinking about possibilities; and (3) their counterfactual thoughts rely on thinking about possibilities, just as rational thoughts do. The sorts of possibilities that people envisage explain the mutability of certain aspects of mental representations and the immutability of other aspects.

The various behavioral disciplines model human behavior in distinct and incompatible ways. Yet, recent theoretical and empirical developments have created the conditions for rendering coherent the areas of overlap of the various behavioral disciplines. The analytical tools deployed in this task incorporate core principles from several behavioral disciplines. The proposed framework recognizes evolutionary theory, covering both genetic and cultural evolution, as the integrating principle of behavioral science. Moreover, if decision theory and game theory are broadened to encompass other-regarding preferences, they become capable of modeling all aspects of decision making, including those normally considered “psychological,” “sociological,” or “anthropological.” The mind as a decision-making organ then becomes the organizing principle of psychology.

“Is there a biology of intelligence which is characteristic of the normal human nervous system?” Here we review 37 modern neuroimaging studies in an attempt to address this question posed by Halstead (1947) as he and other icons of the last century endeavored to understand how brain and behavior are linked through the expression of intelligence and reason. Reviewing studies from functional (i.e., functional magnetic resonance imaging, positron emission tomography) and structural (i.e., magnetic resonance spectroscopy, diffusion tensor imaging, voxel-based morphometry) neuroimaging paradigms, we report a striking consensus suggesting that variations in a distributed network predict individual differences found on intelligence and reasoning tasks. We describe this network as the Parieto-Frontal Integration Theory (P-FIT). The P-FIT model includes, by Brodmann areas (BAs): the dorsolateral prefrontal cortex (BAs 6, 9, 10, 45, 46, 47), the inferior (BAs 39, 40) and superior (BA 7) parietal lobule, the anterior cingulate (BA 32), and regions within the temporal (BAs 21, 37) and occipital (BAs 18, 19) lobes. White matter regions (i.e., arcuate fasciculus) are also implicated. The P-FIT is examined in light of findings from human lesion studies, including missile wounds, frontal lobotomy/leukotomy, temporal lobectomy, and lesions resulting in damage to the language network (e.g., aphasia), as well as findings from imaging research identifying brain regions under significant genetic control. Overall, we conclude that modern neuroimaging techniques are beginning to articulate a biology of intelligence. We propose that the P-FIT provides a parsimonious account for many of the empirical observations, to date, which relate individual differences in intelligence test scores to variations in brain structure and function. Moreover, the model provides a framework for testing new hypotheses in future experimental designs.

In his theory of evolution, Darwin recognized that the conditions of life play a role in the generation of hereditary variations, as well as in their selection. However, as evolutionary theory was developed further, heredity became identified with genetics, and variation was seen in terms of combinations of randomly generated gene mutations. We argue that this view is now changing, because it is clear that a notion of hereditary variation that is based solely on randomly varying genes that are unaffected by developmental conditions is an inadequate basis for evolutionary theories. Such a view not only fails to provide satisfying explanations of many evolutionary phenomena, it also makes assumptions that are not consistent with the data that are emerging from disciplines ranging from molecular biology to cultural studies. These data show that the genome is far more responsive to the environment than previously thought, and that not all transmissible variation is underlain by genetic differences. In Evolution in Four Dimensions (2005) we identify four types of inheritance (genetic, epigenetic, behavioral, and symbol-based), each of which can provide variations on which natural selection will act. Some of these variations arise in response to developmental conditions, so there are Lamarckian aspects to evolution. We argue that a better insight into evolutionary processes will result from recognizing that transmitted variations that are not based on DNA differences have played a role. This is particularly true for understanding the evolution of human behavior, where all four dimensions of heredity have been important.

The question of reductionism is an obstacle to unification. Many behavioral scientists who study the more complex or higher mental functions avoid regarding them as selected by motivation. Game-theoretic models in which complex processes grow from the strategic interaction of elementary reward-seeking processes can overcome the mechanical feel of earlier reward-based models. Three examples are briefly described.

The conclusions of Barbey & Sloman (B&S) crucially depend on evidence for different representations of statistical information. Unfortunately, a muddled distinction made among these representations calls into question the authors' conclusions. We clarify some notions of statistical representations which are often confused in the literature. These clarifications, combined with new empirical evidence, do not support a dual-process model of judgment.

Jablonka & Lamb (J&L) reject “the dreaded memes,” but memetics can explain human uniqueness and culture (as a product of the ability to imitate) without depending on their slippery notion of symbolism. Modern memes show the beginnings of a division into replicators and vehicles, and the replacement of reconstructive processes with systems of blind copying, variation, and selection.

Byrne's book is intended to explain why people imagine the things they do when they create alternatives to reality. Two fruitful areas of further research are: (1) How can her approach explain dreams and daydreams? (2) What is the developmental time course of the child's understanding of reality and imagination?

The target article provides a thoughtful review and synthesis of studies examining the neural basis of cognitive abilities associated with intelligence test performance. In its attempt to present a new or generative theory of the neural basis for intelligence, however, the review faces specific limits to its theoretical model that relate to processes of development and the role of automaticity in cognition.

The tendency to neglect base-rates in judgment under uncertainty may be “notorious,” as Barbey & Sloman (B&S) suggest, but it is neither inevitable (as they document; see also Koehler 1996) nor unique. Here we would like to point out another line of evidence connecting ecological rationality to dual processes, the failure of individuals to appropriately judge cumulative probability.

This book presents a survey of the molecular basis for the genetic control of living organisms and their evolution. The authors consider four dimensions of control over what shapes life forms: genetic, epigenetic, behavioral, and symbolic/cultural. They pay particular attention to the epigenetic realm, and they defend a view recognizing the genetic incorporation of acquired characteristics – a neo-Lamarckian tack.

Unlike physics and chemistry, the behavioral sciences are historical sciences that explain the fuzzy complexity of social life through historical narratives. Unifying the behavioral sciences through evolutionary game theory would require a nested hierarchy of three kinds of historical narratives: natural history, cultural history, and biographical history.

In this commentary we make two rejoinders to Jung & Haier (J&H). First, we highlight the response selection component in tasks as a confounding variable that may explain the parieto-frontal involvement in studies of human intelligence. Second, we suggest that efficient response selection may be an integral part of the definition of intelligence.

If imagination is guided by the same principles as rational thoughts, then we ought not to stop at the way people make inferences to get insights about the workings of imagination; we ought to consider as well the way they make rational choices. This broader approach accounts for the puzzling effect of reasons to act on the mutability of actions.

Barbey & Sloman's (B&S's) base-rate respect model is anticipated by Reyna's denominator neglect model. There are parallels at three levels: (a) explanations are grounded in a general cognitive theory (rather than in domain-specific ideas); (b) problem structure is treated as a key source of reasoning errors; and most importantly, (c) nested set relations are seen as the cause of base-rate neglect.

The notion of mutation is applicable to the generation of novel designs and solutions in engineering and science. This suggests that engineers and scientists have to work against the biases identified in counterfactual thinking. Therefore, imagination appears a lot less rational than claimed in the target article.

Although the beliefs, preferences, and constraints (BPC) model may account for individuals independently making simple decisions, it becomes less useful the more complex the social setting and the decisions themselves become. Perhaps rather than seek to unify their field under one model, behavioral scientists could explore when and why the BPC model generally applies versus fails to apply as a null hypothesis.

Neuroimaging evidence, both within and between research strategies, is largely heterogeneous. This results from the way the construct of interest (i.e., intelligence) is measured. Every single available measure comprises several cognitive abilities, although the so-called g factor is always present. Here I suggest that studies must always control for this empirical fact to arrive at solid conclusions.

Environment can provide information used in development – information that can appear to be genetically given and that was previously assumed to be so. Examples include growth of the eye until it achieves good focus, and structuring of receptive fields in the visual cortex by environmental information. The process can be called one-generation Lamarckism because information acquired from the environment is used to structure the organism and because the capacity to acquire this information is inherited.