The research programs of empirical aesthetics and neuroaesthetics have reflected deep concerns about viewers' sensitivities to artworks' historical contexts by investigating the impact of two factors on art perception: viewers' developmental (and educational) histories and the contextual histories of artworks. These considerations are consistent with data demonstrating that art perception is underwritten by dynamically reconfigured and evolutionarily adapted neural and psychological mechanisms.

Applying a non-developmental evolutionary metatheory to understanding the evolution of psychological capacities leads to the creation of models that mischaracterize developmental processes, misattribute genes as the source of developmental information, and ignore the myriad developmental and contextual factors involved in human decision-making. Using an evolutionary systems perspective, we argue that revenge and forgiveness cannot be understood apart from the development of foundational human psychological capacities and the contexts under which they develop.

McCullough et al. argue that revenge has a future-oriented function, that is, to deter future harms by changing other individuals' incentives toward the self. Recent research has shown that people seek revenge even when harms are unintentional. This commentary reports these results and proposes that revenge may also serve to reduce the immediate psychological pain resulting from unfair treatment.

I propose that in at least some cases, objects of artistic appreciation are best thought of not simply as causes of artistic appreciation, but as parts of the cognitive machinery that drives aesthetic appreciation. In effect, this is to say that aesthetic appreciation operates via extended cognitive systems.

In this commentary, I propose that horizontal and vertical dimensions of space are represented together inside a common metrics mechanism located in the parietal cortex. Importantly, this network is also involved in the processing of number magnitudes and environment-directed actions. Altogether, the evidence suggests that different magnitude dimensions could be intertwined with the horizontality and verticality of our world representation.

Rapid eye movement (REM) dreaming results in “emotionally intelligent encoding,” according to the target article. Building on this, we argue that elaborative encoding alters emotional processing of upcoming events and thereby functions as prospective emotion regulation. After elaborative encoding, future events are appraised differently and result in a redirected emotional response. Disturbed elaborative encoding might be relevant for emotional dysregulation in psychopathology.

There are aspects of schizophrenia that pose challenges for Clark's model. These include: (1) evidence for excitatory activity underlying self-organizing neural ensembles that support coordinating functions, and their impairment in schizophrenia; (2) evidence regarding hallucinations that suggest they are not due to excessive prediction error; and (3) the critical role of emotional factors as setting conditions for delusion formation.

Pickering & Garrod (P&G) explain dialogue dynamics in terms of forward modeling and prediction-by-simulation mechanisms. Their theory dissolves a strict segregation between production and comprehension processes, and it links dialogue to action-based theories of joint action. We propose that the theory can also incorporate intentional strategies that increase communicative success: for example, signaling strategies that help remaining predictable and forming common ground.

Critics of the target article objected to our account of art appreciators' sensitivity to art-historical contexts and functions, the relations among the modes of artistic appreciation, and the weaknesses of aesthetic science. To rebut these objections and justify our program, we argue that the current neglect of sensitivity to art-historical contexts persists as a result of a pervasive aesthetic–artistic confound; we further specify our claim that basic exposure and the design stance are necessary conditions of artistic understanding; and we explain why many experimental studies do not belong to a psycho-historical science of art.

For action systems, the critical task is to predict what will happen next. In language, however, the critical task is not to predict the next auditory event but to extract meaning. Reducing language to an action system, and putting prediction at center, mistakenly marginalizes our core capacity to communicate the novel and unpredictable.

The approach Clark labels “action-oriented predictive processing” treats all cognition as part of a system of on-line control. This ignores other important aspects of animal, human, and robot intelligence. He contrasts it with an alleged “mainstream” approach that also ignores the depth and variety of AI/Robotic research. I don't think the theory presented is worth taking seriously as a complete model, even if there is much that it explains.

In this response, we address eight issues concerning our proposal that human minds contain adaptations for revenge and forgiveness. Specifically, we discuss (a) the inferences that are and are not licensed by patterns of contemporary behavioral data in the context of the adaptationist approach; (b) the theoretical pitfalls of conflating proximate and ultimate causation; (c) the role of development in the production of adaptations; (d) the implications of proposing that the brain's cognitive systems are fundamentally computational in nature; (e) our preferred method for considering the role of individual differences in computational systems; (f) applications of our proposal to understanding conflicts between groups; (g) the possible implications of our views for understanding the operation of contemporary criminal justice systems; and (h) the question of whether people ever “genuinely” forgive.

Jeffery et al. propose a non-uniform representation of three-dimensional space during navigation. Fittingly, we recently revealed asymmetries between horizontal and vertical path integration in humans. We agree that representing navigation in more than two dimensions increases computational load and suggest that tendencies to maintain upright head posture may help constrain computational processing, while distorting neural representation of three-dimensional navigation.

Can ancient art of memory (AAOM) principles explain the function of dreaming? The analysis of self-experience in dreams suggests that the answer is no: The phenomenal dream self lacks certain dimensions that are crucial for the efficacy of AAOM in wakefulness. However, the comparison between dreams and AAOM may be fruitful by suggesting new perspectives for the study of lucid dreaming as well an altered perspective on the efficacy of AAOM itself.

Pickering & Garrod's (P&G's) integrated model of production and comprehension includes no explicit role for nonlinguistic cognitive processes. Yet, how domain-general cognitive functions contribute to language processing has become clearer with well-specified theories and supporting data. We therefore believe that their account can benefit by incorporating functions like working memory and cognitive control into a unified model of language processing.

I argued that rapid eye movement (REM) dreaming is elaborative emotional encoding for episodic memories, sharing many features with the ancient art of memory (AAOM). In this framework, during non–rapid eye movement (NREM), dream scenes enable junctions between episodic networks in the cortex and are retained by the hippocampus as indices for retrieval. The commentaries, which varied in tone from patent enthusiasm to edgy scepticism, fall into seven natural groups: debate over the contribution of the illustrative dream and disputes over the nature of dreaming (discussed in sect. R1); how the framework extends to creativity, psychopathology, and sleep disturbances (sect. R2); the compatibility of the REM dream encoding function with emotional de-potentiation (sect. R3); scepticism over similarities between REM dreaming and the AAOM (sect. R4); the function of NREM dreams in the sleep cycle (sect. R5); the fit of the junction hypothesis with current knowledge of cortical networks (sect. R6); and whether the hypothesis is falsifiable (including methodological challenges and evidence against the hypothesis) (sect. R7). Although the groups in sections R1–R6 appear quite disparate, I argue they all follow from the associative nature of dreaming.

Existing studies have proposed that humans preferentially memorize buildings as a collection of floors. Yet this might stem from the fact that environments were also explored by floors. We have studied this potential bias with a learning and recognition experiment. We have detected a positive influence of the learning route – by floors, and also crucially by columns – on spatial memory performances.

What makes humans moral beings? This question can be understood either as a proximate “how” question or as an ultimate “why” question. The “how” question is about the mental and social mechanisms that produce moral judgments and interactions, and has been investigated by psychologists and social scientists. The “why” question is about the fitness consequences that explain why humans have morality, and has been discussed by evolutionary biologists in the context of the evolution of cooperation. Our goal here is to contribute to a fruitful articulation of such proximate and ultimate explanations of human morality. We develop an approach to morality as an adaptation to an environment in which individuals were in competition to be chosen and recruited in mutually advantageous cooperative interactions. In this environment, the best strategy is to treat others with impartiality and to share the costs and benefits of cooperation equally. Those who offer less than others will be left out of cooperation; conversely, those who offer more will be exploited by their partners. In line with this mutualistic approach, the study of a range of economic games involving property rights, collective actions, mutual help and punishment shows that participants' distributions aim at sharing the costs and benefits of interactions in an impartial way. In particular, the distribution of resources is influenced by effort and talent, and the perception of each participant's rights on the resources to be distributed.

It is often helpful to distinguish between a theory (Marr's computational level) and a specific implementation of that theory (Marr's physical level). However, in the target article, a single implementation of predictive coding is presented as if this were the theory of predictive coding itself. Other implementations of predictive coding have been formulated which can explain additional neurobiological phenomena.