Contagious behaviors such as yawning and itching/scratching have mirror-like properties and clearly defined stimulus and motor parameters; they are also relatively easy to study and should be part of the debate about mirror neurons and the neurological mechanisms of social behavior. The broadly tuned, multimodal stimuli of contagious behavior challenge present accounts of mirror mechanisms that focus on specific, mirrored acts.

The presence of overwhelming amounts of information in our big-data era society is growing. Globalisation is increasingly giving these solicitations (regarding information) a more social aspect causing behavioural changes. While restricting my focus on this aspect of the Bentley et al article, I address related medical questions and pin-point the conceptual interest of the roadmap given therein.

The negative valence model of political orientation proposed by Hibbing et al. is comprehensive and thought-provoking. We agree that there is compelling research linking threat to conservative political beliefs. However, we propose that further research is needed before it can be concluded that negative valence, rather than arousal more generally, underlies the psychological motivations to endorse conservative political belief.

Investigations of biases and experiential effects on social learning, social information use, and mirror systems can usefully inform one another. Unconstrained learning is predicted to shape mirror systems when the optimal response to an observed act varies, but constraints may emerge when immediate error-free responses are required and evolutionary or developmental history reliably predicts the optimal response. Given the power of associative learning, such constraints may be rare.

Self-reported opinions and judgments may be more rooted in expressive biases than in cognitive processing biases, and ultimately operate within a broader behavioral style for advertising the capacity – versus the trustworthiness – dimension of human reciprocity potential. Our analyses of facial expression judgments of likely voters are consistent with this thesis, and directly contradict one major prediction from the authors' “negativity-bias” model.

Transparency is a fundamental concept in the target article by Bentley et al. But the text gives cryptic, inconclusive and sometimes conflicting suggestions as to what transparency consists of. Consequently, it is insufficiently clear what the north–south axis of the map of collective behaviour actually represents, or how to order behaviours by transparency.

Cook et al. argue that mirror neurons originate in sensorimotor associative learning and that their function is determined by their origin. Both these claims are hard to accept. It is here suggested that a major role in the origin of the mirror mechanism is played by top-down connections rather than by associative learning.

The past few years have shown a major rise in network analysis of “big data” sets in the social sciences, revealing non-obvious patterns of organization and dynamic principles. We speculate that the dependency dimension – individuality versus sociality – might offer important insights into the dynamics of neurons and neuronal ensembles. Connectomic neural analyses, informed by social network theory, may be helpful in understanding underlying fundamental principles of brain organization.

Hibbing et al. use evolutionarily derived logic to suggest that political attitudes are related to responses to negative features of the environment. We suggest that the authors focus too narrowly on the negative and contend, instead, that a more comprehensive evolutionary approach focusing on people's responses to threats and opportunities will better account for variation in political attitudes.

A broad, multidisciplinary empirical literature reports that individual-level differences in psychology and biology map onto variation in political orientation. In our target article we argued that negativity bias can explain a surprisingly large share of these findings. The commentators generally support the negativity bias hypothesis but suggest theoretical and empirical revisions and refinements. In this response, we organize these proposals, suggestions, and criticisms into four thematic categories and assess their potential for furthering theories and empirical investigations of the bases for individual-variation in political ideology.

Like Cook et al., we suggest that mirror neurons are a fascinating product of cross-modal learning. As predicted by an associative account, responses in motor regions are observed for novel and/or abstract visual stimuli such as point-light and android movements. Domain-specific mirror responses also emerge as a function of audiomotor expertise that is slowly acquired over years of intensive training.

While Bentley et al.’s model is very appealing, in this commentary we argue that researchers interested in big data and collective behavior, including the way humans make decisions, must account for the emotional factor. We investigate how daily choice of activities is influenced by emotions. Results indicate that mood significantly predicts people's decisions about what to do next, stressing the importance of emotional state on decision-making.

We apply Bentley et al.’s theoretical framework to better understand gender discrimination in online labor markets. Although such settings are designed to encourage employer behavior in the northwest corner of Homo economicus, actual online hiring decisions tend to drift southeast into a “confirmation bias plus weak feedback loops” pattern of discrimination based on inaccurate social stereotypes.

Neonatal imitation should not exclusively be considered at the population-level; instead, we propose that inconsistent findings regarding its occurrence result from important individual differences in imitative responses. We also highlight what we consider to be a false dichotomy of genetic versus learning accounts of the development of mirror neurons, and instead suggest a more parsimonious epigenetic perspective.

Commentators have tended to focus on the conceptual framework of our article, the contrast between genetic and associative accounts of mirror neurons, and to challenge it with additional possibilities rather than empirical data. This makes the empirically focused comments especially valuable. The mirror neuron debate is replete with ideas; what it needs now are system-level theories and careful experiments – tests and testability.

Social influence and payoff transparency interact with each other to influence decision making. Social influence masks payoff transparency, and lacking transparency drives people to seek social influence. Moreover, our survey supports our claim by showing that social influence and payoff transparency correlate with each other (r(53) = –.71). Bentley et al.’s model can be revised to accommodate the covariance.

In a recent New York Times column (April 15, 2013), David Brooks discussed how the big-data agenda lacks a coherent framework of social theory – a deficiency that the Bentley, O'Brien, and Brock (henceforth BOB) model was meant to overcome. Or, stated less pretentiously, the model was meant as a first step in that direction – a map that hopefully would serve as a minimal, practical, and accessible framework that behavioral scientists could use to analyze big data. Rather than treating big data as a record of, and also a predictor of, where and when certain behaviors might take place, the BOB model is interested in what big data reveal about how decisions are being made, how collective behavior evolves from daily to decadal time scales, and how this varies across communities.