Processing of facial expressions goes beyond simple pattern recognition. To elucidate this problem, Niedenthal et al. offer a model that identifies multiple embodied and disembodied routes for expression processing, and spell out conditions triggering use of different routes. I elaborate on this model by discussing recent research on emotional recognition in individuals with autism, who can use multiple routes of emotion processing, and consequently can show atypical and typical patterns of embodied simulation and mimicry.

In this response, I offer some specific examples of neural workings, discuss the uncertainty of reverse inference, place neural reuse in developmental and cultural context, further differentiate reuse from plasticity, and clarify my position on embodied cognition. The concept of local neural workings is further refined, and some different varieties of reuse are identified. Finally, I lay out some opportunities for future research, and discuss some of the clinical implications of reuse in more detail.

The pivotal problem of comorbidity research lies in the psychometric foundation it rests on, that is, latent variable theory, in which a mental disorder is viewed as a latent variable that causes a constellation of symptoms. From this perspective, comorbidity is a (bi)directional relationship between multiple latent variables. We argue that such a latent variable perspective encounters serious problems in the study of comorbidity, and offer a radically different conceptualization in terms of a network approach, where comorbidity is hypothesized to arise from direct relations between symptoms of multiple disorders. We propose a method to visualize comorbidity networks and, based on an empirical network for major depression and generalized anxiety, we argue that this approach generates realistic hypotheses about pathways to comorbidity, overlapping symptoms, and diagnostic boundaries, that are not naturally accommodated by latent variable models: Some pathways to comorbidity through the symptom space are more likely than others; those pathways generally have the same direction (i.e., from symptoms of one disorder to symptoms of the other); overlapping symptoms play an important role in comorbidity; and boundaries between diagnostic categories are necessarily fuzzy.

We discuss the latent variables construct, particularly in regard to the following: that latent variables are considered as the sole explanatory factor of a disorder; that pragmatic concerns are ignored; and that the relationship of these variables to biological markers is not addressed. Further, we comment on the relationship between bridge symptoms and causality, and discuss the proposal in relationship to other constructs (endophenotypes, connectionist-inspired networks).

The set of 30 stimulating commentaries on our target article helps to define the areas of our initial position that should be reiterated or else made clearer and, more importantly, the ways in which moderators of and extensions to the SIMS can be imagined. In our response, we divide the areas of discussion into (1) a clarification of our meaning of “functional,” (2) a consideration of our proposed categories of smiles, (3) a reminder about the role of top-down processes in the interpretation of smile meaning in SIMS, (4) an evaluation of the role of eye contact in the interpretation of facial expression of emotion, and (5) an assessment of the possible moderators of the core SIMS model. We end with an appreciation of the proposed extensions to the model, and note that the future of research on the problem of the smile appears to us to be assured.

It has often been suggested that people's ordinary capacities for understanding the world make use of much the same methods one might find in a formal scientific investigation. A series of recent experimental results offer a challenge to this widely-held view, suggesting that people's moral judgments can actually influence the intuitions they hold both in folk psychology and in causal cognition. The present target article distinguishes two basic approaches to explaining such effects. One approach would be to say that the relevant competencies are entirely non-moral but that some additional factor (conversational pragmatics, performance error, etc.) then interferes and allows people's moral judgments to affect their intuitions. Another approach would be to say that moral considerations truly do figure in workings of the competencies themselves. I argue that the data available now favor the second of these approaches over the first.

Knobe's argument rests on a way of distinguishing performance errors from the competencies that delimit our cognitive architecture. We argue that other sorts of evidence than those that he appeals to are needed to illuminate the boundaries of our folk capacities in ways that would support his conclusions.

Although the network model represents a promising new approach to conceptualizing comorbidity in psychiatric diagnosis, the model applies most directly to Axis I symptom disorders; the degree to which the model generalizes to Axis II disorders remains open to question. This commentary addresses that issue, discussing opportunities and challenges in applying the network model to DSM-diagnosed personality pathology.

Knobe argues in his target article that asymmetries in intentionality judgments can be explained by the view that concepts such as intentionality are suffused with moral considerations. We believe that the “culpable control” model of blame can account both for Knobe's side effect findings and for findings that do not involve side effects.

Network analysis is a promising step forward in efforts to align psychological assessment with explanatory theory in psychological science. The implications of Cramer et al.'s analysis are quite general. Networks analysis may illuminate functional relations not only among observable behaviors that comprise psychological disorders, but among cognitive and affective processes that causally contribute to everyday experience and action.

We agree with Cramer et al.'s goal of the discovery of causal relationships, but we argue that the authors' characterization of latent variable models (as deployed for such purposes) overlooks a wealth of extant possibilities. We provide a preliminary analysis of their data, using existing algorithms for causal inference and for the specification of latent variable models.

Scientific inquiry possibly shares with people's ordinary understanding the same evolutionary determinants, and affect-laden intuitions that shape moral judgments also play a decisive role in decision-making, planning, and scientific reasoning. Therefore, if ordinary understanding does differ from scientific inquiry, the reason does not reside in the fact that the former (but not the latter) is endowed with moral considerations.

Psychological traits and disorders are often interrelated through shared genetic influences. A combination of maximum-likelihood structural equation modelling and multidimensional scaling enables us to open a window onto the genetic architecture at the symptom level, rather than at the level of latent genetic factors. We illustrate this approach using a study of cognitive abilities involving over 5,000 pairs of twins.

In this commentary we suggest that asymmetries in reasoning associated with moral judgment do not necessarily invalidate a theory-theory account of naïve psychological reasoning. The asymmetries may reflect a core knowledge assumption that human nature is prosocial, an assumption that heightens vigilance for antisocial dispositions, which in turn leads to differing assumptions about what is the presumed topic of conversation.

Knobe argues that people's judgments of the moral status of a side-effect of action influence their assessment of whether the side-effect is intentional. I tested this hypothesis using vignettes akin to Knobe's but involving economically or eudaimonistically (wellness-related) negative side-effects. My results show that it is people's sense of what agents deserve, and not the moral status of side-effects, that drives intuition.

The network approach proposed by Cramer et al. suggests fascinating new directions of research on mental disorders. Research is needed to find evidence for the causal power of symptoms, to examine symptoms thoroughly, to investigate individual differences in edge strength, to discover etiological processes for each symptom, and to determine whether and why symptoms cohere into distinct mental disorders.

Knobe's laudable conclusion that we make sense of our social world based on moral considerations requires a development account of human thought and a theoretical framework. We outline a view that such a moral framework must be rooted in social interaction.

Cramer et al. make a good case for reconceptualizing comorbid psychopathologies in terms of complex network theory. We suggest the need for an extension of their network model to include reference to latent causes. We also draw attention to a neglected approach to theory appraisal that might usefully be incorporated into the methodology of network theory.