Why does performing certain tasks cause the aversive experience of mental effort and concomitant deterioration in task performance? One explanation posits a physical resource that is depleted over time. We propose an alternative explanation that centers on mental representations of the costs and benefits associated with task performance. Specifically, certain computational mechanisms, especially those associated with executive function, can be deployed for only a limited number of simultaneous tasks at any given moment. Consequently, the deployment of these computational mechanisms carries an opportunity cost – that is, the next-best use to which these systems might be put. We argue that the phenomenology of effort can be understood as the felt output of these cost/benefit computations. In turn, the subjective experience of effort motivates reduced deployment of these computational mechanisms in the service of the present task. These opportunity cost representations, then, together with other cost/benefit calculations, determine effort expended and, everything else equal, result in performance reductions. In making our case for this position, we review alternative explanations for both the phenomenology of effort associated with these tasks and for performance reductions over time. Likewise, we review the broad range of relevant empirical results from across sub-disciplines, especially psychology and neuroscience. We hope that our proposal will help to build links among the diverse fields that have been addressing similar questions from different perspectives, and we emphasize ways in which alternative models might be empirically distinguished.

Additional evidence is presented concerning the anisotropy between vertical and horizontal encoding, which emerges from studies of human perception and cognition of space in plane mirror reflections. Moreover, it is suggested that the non-metric characteristic of polarization – that Jeffery et al. discuss with respect to gravity – is not limited to the vertical dimension.

While the target article provides a glowing account for the excitement in the field, we stress that hierarchical predictive learning in the brain requires sparseness of the representation. We also question the relation between Bayesian cognitive processes and hierarchical generative models as discussed by the target article.

Pickering & Garrod (P&G) propose that inner speech monitoring is subserved by predictions stemming from fast forward modeling. In this commentary, we question this alignment of language prediction with the inner speech monitor. We wonder how the speech monitor can function so efficiently if it is based on incomplete representations.

To the extent that acting fairly is in an individual's long-term interest, short-term impulses to cheat present a self-control problem. The only effective solution is to interpret the problem as a variant of repeated prisoner's dilemma, with each choice as a test case predicting future choices. Moral choice appears to be the product of a contract because it comes from self-enforcing intertemporal cooperation.

Pickering & Garrod's (P&G's) theory could be modified to describe how listeners rapidly incorporate context to generate predictions about speech despite inter-talker variability. However, in order to do so, the content of “impoverished” predicted percepts must be expanded to include phonetic information. Further, the way listeners identify and represent inter-talker differences and subsequently determine which prediction method to use would require further specification.

The target article sketched and explored a mechanism (action-oriented predictive processing) most plausibly associated with core forms of cortical processing. In assessing the attractions and pitfalls of the proposal we should keep that element distinct from larger, though interlocking, issues concerning the nature of adaptive organization in general.

Animals navigate through three-dimensional environments, but we argue that the way they encode three-dimensional spatial information is shaped by how they use the vertical component of space. We agree with Jeffery et al. that the representation of three-dimensional space in vertebrates is probably bicoded (with separation of the plane of locomotion and its orthogonal axis), but we believe that their suggestion that the vertical axis is stored “contextually” (that is, not containing distance or direction metrics usable for novel computations) is unlikely, and as yet unsupported. We describe potential experimental protocols that could clarify these differences in opinion empirically.

Self-control is a necessary component of subjective effort, but it depends only on farsighted motivation, with no additional, depletable resource. The aversiveness of boring tasks probably comes from their interference with endogenous reward, a new and potentially controversial concept. The self-control needed to stick with any kind of aversive experience increases as the values of the competing motives draw closer together.

Any evolved disposition for fairness and cooperation would not replace but merely compete with selfish and other antisocial impulses. Therefore, we propose that human cooperation and fairness depend on self-regulation. Evidence shows reductions in fairness and other prosocial tendencies when self-regulation fails.

We agree with Pickering & Garrod's (P&G's) claim that theories of language processing must address the interconnection of language production and comprehension. However, we have two concerns: First, the central notion of context when predicting what another person will say is underspecified. Second, it is not clear that P&G's dual-mechanism model captures the data better than a single-mechanism model would.

The process of partner selection reflects ethnographic realities where cooperative rewards obtain that would otherwise be lost to loners. Baumard et al. neglect frequency-dependent processes exemplified by games of coordination. Such games can produce multiple equilibria that may or may not include fair outcomes. Additional, group-selection processes are required to produce the outcomes predicted by the models.

Jeffery et al. extensively and thoroughly describe how different species navigate through a three-dimensional environment. Undeniably, the world offers numerous three-dimensional opportunities. However, we argue that for most navigation tasks a two-dimensional representation is nevertheless sufficient, as physical conditions and limitations such as gravity, thermoclines, or layers of earth encountered in a specific situation provide the very elevation data the navigating individual needs.

The cognitive impairments shown by brain-damaged patients emphasize the role of task difficulty as a major determinant for performance. We discuss the proposal of Kurzban et al. in light of our findings on right-hemisphere–damaged patients, who show increasing awareness deficits for the contralesional hemispace when engaged with resource-consuming dual tasks. This phenomenon is readily explained by the assumption of unspecific depletable resources.

Classical (Bayesian) probability (CP) theory has led to an influential research tradition for modeling cognitive processes. Cognitive scientists have been trained to work with CP principles for so long that it is hard even to imagine alternative ways to formalize probabilities. However, in physics, quantum probability (QP) theory has been the dominant probabilistic approach for nearly 100 years. Could QP theory provide us with any advantages in cognitive modeling as well? Note first that both CP and QP theory share the fundamental assumption that it is possible to model cognition on the basis of formal, probabilistic principles. But why consider a QP approach? The answers are that (1) there are many well-established empirical findings (e.g., from the influential Tversky, Kahneman research tradition) that are hard to reconcile with CP principles; and (2) these same findings have natural and straightforward explanations with quantum principles. In QP theory, probabilistic assessment is often strongly context- and order-dependent, individual states can be superposition states (that are impossible to associate with specific values), and composite systems can be entangled (they cannot be decomposed into their subsystems). All these characteristics appear perplexing from a classical perspective. However, our thesis is that they provide a more accurate and powerful account of certain cognitive processes. We first introduce QP theory and illustrate its application with psychological examples. We then review empirical findings that motivate the use of quantum theory in cognitive theory, but also discuss ways in which QP and CP theories converge. Finally, we consider the implications of a QP theory approach to cognition for human rationality.

Though Kurzban et al.'s model explains a considerable set of empirical findings, it cannot accommodate other results without relying on extra assumptions. We offer an addition to the model, and suggest that cost-benefit analyses themselves depend on executive function, and therefore can be biased. The adapted model allows for explaining depletion effects, as well as their reversals, documented in the literature.

Our target article proposed that language production and comprehension are interwoven, with speakers making predictions of their own utterances and comprehenders making predictions of other people's utterances at different linguistic levels. Here, we respond to comments about such issues as cognitive architecture and its neural basis, learning and development, monitoring, the nature of forward models, communicative intentions, and dialogue.

Baumard et al. attribute morality to a naturally selected propensity to share costs and benefits of cooperation fairly. But how does mundane mutualism relate to transcendent notions of morality critical to creating cultures and civilizations? Humans often make their greatest exertions for an idea they form of their group. Primary social identity is bounded by sacred values, which drive individuals to promote their group through non-rational commitment to actions independently of likely risks and rewards.

We support the authors' claims, except that we point out that also quantum structure different from quantum probability abundantly plays a role in human cognition. We put forward several elements to illustrate our point, mentioning entanglement, contextuality, interference, and emergence as effects, and states, observables, complex numbers, and Fock space as specific mathematical structures.