Any complete theory of speaking must take the dialogical function of language use into account. Pickering & Garrod (P&G) make some progress on this point. However, we question whether their interactive alignment model is the optimal approach. In this commentary, we specifically criticize (1) their notion of alignment being implemented through priming, and (2) their claim that self-monitoring can occur at all levels of linguistic representation.

Conversational partners' representations may be less aligned than they appear even when interlocutors believe they have successfully understood each other, as data from a series of experiments on surveys about facts and behaviors suggest. Although the goal of a mechanistic psychology of dialogue is laudable, the ultimate model is likely to require far greater specification of individual and contextual variability.

Pickering & Garrod's (P&G's) mechanistic account of dialogue assumes that linguistic alignment between interlocutors takes place automatically, without using cognitive resources. However, even the most basic processes of speech perception depend on resource use. The lack of invariant mapping between input patterns and interpretations in dialogue, as in speech perception, may require controlled, rather than automatic, processing.

Pickering & Garrod's (P&G's) model is an innovative and important step in the study of naturalistic language. However, the simplicity of its mechanisms for dialogue coordination may be overstated and the hypothesized direct priming channel between interlocutors' situation models is questionable. A complete specification of the model will require more investigation of the role of top-down inhibition among representations.

The interactive-alignment model of dialogue provides an account of dialogue at the level of explanation normally associated with cognitive psychology. We develop our claim that interlocutors align their mental models via priming at many levels of linguistic representation, explicate our notion of automaticity, defend the minimal role of “other modeling,” and discuss the relationship between monologue and dialogue. The account can be applied to social and developmental psychology, and would benefit from computational modeling.

Little is known about how to generate plausible new scientific ideas. So it is noteworthy that 12 years of self-experimentation led to the discovery of several surprising cause-effect relationships and suggested a new theory of weight control, an unusually high rate of new ideas. The cause-effect relationships were: (1) Seeing faces in the morning on television decreased mood in the evening (>10 hrs later) and improved mood the next day (>24 hrs later), yet had no detectable effect before that (0–10 hrs later). The effect was strongest if the faces were life-sized and at a conversational distance. Travel across time zones reduced the effect for a few weeks. (2) Standing 8 hours per day reduced early awakening and made sleep more restorative, even though more standing was associated with less sleep. (3) Morning light (1 hr/day) reduced early awakening and made sleep more restorative. (4) Breakfast increased early awakening. (5) Standing and morning light together eliminated colds (upper respiratory tract infections) for more than 5 years. (6) Drinking lots of water, eating low-glycemic-index foods, and eating sushi each caused a modest weight loss. (7) Drinking unflavored fructose water caused a large weight loss that has lasted more than 1 year. While losing weight, hunger was much less than usual. Unflavored sucrose water had a similar effect. The new theory of weight control, which helped discover this effect, assumes that flavors associated with calories raise the body-fat set point: The stronger the association, the greater the increase. Between meals the set point declines. Self-experimentation lasting months or years seems to be a good way to generate plausible new ideas.

The design and interpretation of self-experimentation need to be integrated with existing scientific knowledge. Otherwise observations on oneself cannot make a creative contribution to the advance of empirical understanding.

There are two sorts of scientists: Dionysians, who rely on intuition, and Apollonians, who are more systematic. Self-experimentation is a Dionysian approach that is likely to open new lines of research. Unfortunately, the Dionysian approach does not allow one to predict the results of experiments. That is one reason why self-experimentation is not popular among granting agencies.

The case for the value of self-experimentation in advancing science is convincing. Important features of the method include (1) repeated measures of individual behavior, over extended time, to discover cause/effect relations, and (2) vivid graphical presentations. Large-scale research on Pavlovian conditioning and weight control is needed because verification could result in easy and inexpensive mitigation of a serious public health problem.

The target article is important not only for black-box studies, but also for those interested in tracing cognitive processing and/or subjective experience (via systematic self-observation). I provide two examples taken from my own research. I then proceed to discuss how best to analyze data from the n = 1 study, which has a factorial design.

Self-experimentation is a valuable companion to self-management in the benefit of pharmaco-cognitive-behavior combination therapies. However, data on individuals participating as active therapeutic agents are sparse. Smoking cessation therapy is an example. Roberts' self-experimentation suggests trying more diversity in research to generate new ideas. This may inform current approaches to the cessation of smoking.

Self-surveillance and self-experimentation are of concern to everyone interested in finding out the factors that increase one's risk of stroke from <8% to nearly 100%; one also thereby contributes to transdisciplinary science.

According to a multivariate approach on creativity, self-experimentation may well provide many of the conditions that allow for new ideas to occur. This research method is valuable in particular because the researcher's high level of participation in the search for a solution fosters the involvement of the necessary cognitive skills and conative traits.

Examination of the target article for its relevance to the analysis of private behavior leads to three concerns: the absence of a new methodology for studying private behavior, the undisclosed possibility of interactions, and insufficient attention to the social context of idea generation. Regardless of these concerns, a larger issue remains: Can a science of n = 1 be credible?

We argue that the self-experimentation espoused by Roberts as a means of generating new ideas, particularly in the area of mood, may be confounded by the experimental procedure eliciting those affective changes. We further suggest that ideas might be better generated through contact with a broad range of people, rather than in isolation.

One important lesson of Roberts' target article may be potentially obscured for some by the title's reference to “self-experimentation.” At the core of this work, the key investigative resource is sustained and systematic observation, not experimentation, and it is deployed in a fashion not necessarily restricted to self-examination. There is an important reminder here of a strategically important, but neglected, relationship between observation and experiment.

A self-experiment by Roberts found that watching faces on early morning television triggered a delayed rhythm in mood. This surprising result is compared with previous research on circadian rhythms in mood. I argue that Roberts' dual oscillator model and theory of Stone-Age living may not provide the explanation. I also discuss the implications of self-experiments for scientific practices.

According to Roberts, self-experimentation is a viable tool for idea generation in the behavioral sciences. Here we discuss some limitations of this assertion, as well as particular design and data-analytic shortcomings of his experiments.

Self-experimentation is uncommon in the decision sciences, but mental experiments are common; for example, intuition and introspection are often used by theoretical economists as justifications for their models. While introspection can be useful for the generation of ideas, it can also be overused and become a comfortable illusion for the theorist and an obstacle for science.

The topics discussed in this response are in four broad areas: (1) Idea generation, including the failure to discuss and teach idea generation and how to nurture new ideas (sect. R2), sources of ideas worth testing with self-experimentation (sect. R3), and unusual features of the situation that may have increased the discovery rate (sect. R4); (2) Miscellaneous methodological issues, such as the value of mental experiments (sect. R5) and the limitations of double-blind experiments (sect. R6); (3) Subject-matter issues, including the relationship of this work to other evolutionary psychology studies and a new way to test evolutionary explanations (sect. R7), as well as questions about the mood results (sect. R8) and the weight results (sect. R9); and (4) Self-experimentation, including its difficulty (sect. R10) and future (sect. R11).