In this commentary, we highlight a difficulty for metric navigation arising from recent data with grid and place cells: the integration of piecemeal representations of space in environments with repeated boundaries. Put simply, it is unclear how place and grid cells might provide a global representation of distance when their fields appear to represent repeated boundaries within an environment. One implication of this is that the capacity for spatial inferences may be limited.

As a comment on Kurzban et al.'s opportunity cost model, we propose an alternative view of mental effort and the action selection mechanism in the brain. Our hypothesis utilizes local resource depletion within neuronal networks, which justifies from a neurophysiological perspective why mental fatigue diminishes after switching to a novel task and explains action selection by means of neural competition theory.

One among many misleading quotations about the alleged mysteries of quantum theory is from Feynman (1965): “I think I can safely say that nobody understands quantum mechanics.” Today we know that quantum theory describes many aspects of our world in a fully intelligible fashion. Pothos & Busemeyer (P&B) propose ways in which this may include psychology and cognitive science.

The bicoded cognitive maps described by Jeffery et al. are compared to metric perceptual representations. Systematic biases in perceptual experience of egocentric distance, height, and surface orientation may reflect information processing choices to retain information critical for immediate action (Durgin et al. 2010a). Different information processing goals (route planning vs. immediate action) require different metric information.

In spite of the remarkable progress made in the burgeoning field of social neuroscience, the neural mechanisms that underlie social encounters are only beginning to be studied and could – paradoxically – be seen as representing the “dark matter” of social neuroscience. Recent conceptual and empirical developments consistently indicate the need for investigations that allow the study of real-time social encounters in a truly interactive manner. This suggestion is based on the premise that social cognition is fundamentally different when we are in interaction with others rather than merely observing them. In this article, we outline the theoretical conception of a second-person approach to other minds and review evidence from neuroimaging, psychophysiological studies, and related fields to argue for the development of a second-person neuroscience, which will help neuroscience to really “go social”; this may also be relevant for our understanding of psychiatric disorders construed as disorders of social cognition.

Among other things, Baumard et al.'s “A Mutualistic Approach to Morality” considers the enforcement and establishment of moral norms, the interpersonal comparison of welfare, and the structure of fairness norms. This commentary draws attention to the relevance of the game theory literature to the first and second topic, and the social psychology literature to the third topic.

The Hilbert space formalism is a powerful language to express many cognitive phenomena. Here, relevant concepts from signal detection theory are recast in that language, allowing an empirically testable extension of the quantum probability formalism to psychophysical measures, such as detectability and discriminability.

This commentary situates the second person account within a broader framework of ecological validity for experimental paradigms in social cognitive neuroscience. It then considers how individual differences at psychological and genetic levels can be integrated within the proposed framework.

We discuss the idea that environmental factors influence the neural mechanisms that evolved to enable navigation, and propose that a capacity to learn different spatial relationship rules through experience may contribute to bicoded processing. Recent experiments show that free-flying bees can learn abstract spatial relationships, and we propose that this could be combined with optic flow processing to enable three-dimensional navigation.

The depletion effect, a decreased capacity for self-control following previous acts of self-control, is thought to result from a lack of necessary psychological/physical resources (i.e., “ego depletion”). Kurzban et al. present an alternative explanation for depletion; but based on statistical techniques that evaluate and adjust for publication bias, we question whether depletion is a real phenomenon in need of explanation.

An individual obtains an unfair benefit and faces the dilemma of either hiding it (to avoid being excluded from future interactions) or disclosing it (to avoid being discovered as a deceiver). In line with the target article, we expect that this dilemma will be solved by a fixed individual strategy rather than a case-by-case rational calculation.

Recent research investigating the language–thought interface in the spatial domain points to representations of the horizontal and vertical dimensions that closely resemble those posited by Jeffery et al. However, the findings suggest that such representations, rather than being tied to navigation, may instead reflect more general properties of the perception of space.

The target article's approach is applauded, but it is suggested that the “dark matter” may be much larger than even the current authors suspect. Cartesian and mechanistic assumptions infuse not only the discipline of cognitive psychology, but all societal accounts of the person. A switch to dynamical accounts in which lawfulness is observed within a given systemic context is suggested.

Kurzban et al. argue that the experiences of “effort,” “boredom,” and “fatigue” are indications that the costs of a task outweigh its benefits. Reducing the costs of tasks to “opportunity costs” has the effect of rendering tasks costless and of denying that they can be inherently boring or tedious, something that “vigilance tasks” were intentionally designed to be.

Baumard et al. propose a functional explanation for the evolution of a sense of fairness in humans: Fairness preferences are advantageous in an environment where individuals are in strong competition to be chosen for social interactions. Such conditions also exist in nonhuman animals. Therefore, it remains unclear why fairness (equated with morality) appears to be properly present only in humans.

Pothos & Busemeyer (P&B) argue how key concepts of quantum probability, for example, order/context, interference, superposition, and entanglement, can be used in cognitive modeling. Here, we suggest that these concepts can be extended to analyze neurophysiological measurements of cognitive tasks in humans, especially in functional neuroimaging investigations of large-scale brain networks.

I argue that the overly simplistic scenarios discussed by Pothos & Busemeyer (P&B) establish at best that quantum probability theory (QPT) is a logical possibility allowing distinct predictions from classical probability theory (CPT). The article fails, however, to provide convincing evidence for the proposal that QPT offers unique insights regarding cognition and the nature of human rationality.

Second person social cognition cannot be restricted to dyadic interactions between two persons (the “I” and the “you”). Many instances of social communication are triadic, and involve a third person (the “him/her/it”), which is the object of the interaction. We discuss neuropsychological and brain imaging data showing that triadic interactions involve dedicated brain networks distinct from those of dyadic interactions.

Multilevel wayfinding research in environmental psychology and architecture exhibits a strong compatibility with Jeffery et al.'s “bicoded” representation of space. We identify a need for capturing verticality in spatial analysis techniques such as space syntax and argue for investigating inter-individual differences in the ability to mentally integrate the cognitive maps of separate floors in buildings.

We argue that maximising utility does not promote survival. Hence, there is no reason to expect people to modulate effort according to a task's opportunity costs. There is also no reason why our evaluation of the marginal opportunity costs of tasks should predictably rise with repetition. Thus, the opportunity cost model cannot explain why tasks typically become harder over time.