Research Article

Computational and neurobiological foundations of leadership decisions

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Science  03 Aug 2018:
Vol. 361, Issue 6401, eaat0036
DOI: 10.1126/science.aat0036

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Leadership and responsibility

Leadership of groups is of paramount importance and pervades almost every aspect of society. Leadership research has rarely used computational modeling or neuroimaging techniques to examine mechanistic or neurobiological underpinnings of leadership choices. Edelson et al. found empirically and theoretically that the choice to lead rests on a metacognitive process (see the Perspective by Fleming and Bang). Individuals who showed less “responsibility aversion” had higher leadership scores. A computational model combining signal detection theory with prospect theory provided a mechanistic understanding of this preference. Neuroimaging experiments showed how the key theoretical concepts are encoded in the activity and connectivity of a brain network that comprises the medial prefrontal cortex, the superior temporal gyrus, the temporal parietal junction, and the anterior insula.

Science, this issue p. 467; see also p. eaat0036

Structured Abstract


Decisions as diverse as committing soldiers to the battlefield or picking a school for your child share a basic attribute: assuming responsibility for the outcome of others. This responsibility is inherent in the roles of prime ministers and generals, as well as in the more quotidian roles of firm managers, schoolteachers, and parents. Here we identify the underlying behavioral, computational, and neurobiological mechanisms that determine the choice to assume responsibility over others.


We developed a decision paradigm in which an individual can delegate decision-making power about a choice between a risky and a safe option to their group or keep the right to decide: In the “self” trials, only the individual’s payoff is at stake, whereas in the “group” trials, each group member’s payoff is affected. We combined models from perceptual and value-based decision-making to es­timate each individual’s personal utility for every available action in order to tease apart potential motivations for choosing to “lead” or “follow.” We also used brain imaging to examine the neurobiological basis of leadership choices.


The large majority of the subjects display responsibility aversion (see figure, left panel), that is, their willingness to choose between the risky and the safe option is lower in the group trials relative to the self trials, independent of basic preferences toward risk, losses, ambiguity, social preferences, or intrinsic valuations of decision rights. Furthermore, our findings indicate that responsibility aversion is not associated with the overall frequency of keeping or delegating decision-making power. Rather, responsibility aversion is driven by a second-order cognitive process reflecting an increase in the demand for certainty about what constitutes the best choice when others’ welfare is affected. Individuals who are less responsibility averse have higher questionnaire-based and real-life leadership scores. The center panel of the figure shows the correlation between predicted and observed leadership scores in a new, independent sample. Our analyses of the dynamic interactions between brain regions demonstrate the importance of information flow between brain regions involved in computing separate components of the choice to understanding leadership decisions and individual differences in responsibility aversion.


The driving forces behind people’s choices to lead or follow are very important but largely unknown. We identify responsibility aversion as a key determinant of the willingness to lead. Moreover, it is predictive of both survey-based and real-life leadership scores. These results sug­gest that many people associate a psychological cost with assuming responsibility for others’ outcomes. Individual differences in the perception of, and willingness to bear, responsibility as the price of leadership may determine who will strive toward leadership roles and, moreover, are associated with how well they perform as leaders.

Our computational model provides a conceptual framework for the decision to assume responsibility for others’ outcomes as well as insights into the cognitive and neural mechanisms driving this choice process. This framework applies to many different leadership types, including authoritarian leaders, who make most decisions themselves, and egalitarian leaders, who frequently seek a group consensus. We believe that such a theoretical foundation is critical for a precise understanding of the nature and consequences of leadership.

Frequency, out-of-sample predictive power, and computational foundations of responsibility aversion.

(Left) Responsibility aversion differs widely across individuals. (Center) These individual differences in responsibility aversion can be used to predict leadership scores in a new, independent sample. (Right) The lead-versus-defer decision process is illustrated. The black curve shows the proportion of defer choices increasing when the subjective-value difference between actions approaches zero (dashed line). This pattern holds in both self and group trials. What changes is where people set deferral thresholds (orange, self; blue, group), which determine when they are most likely to defer. More responsibility-averse individuals show a larger shift in the deferral thresholds, which our computational model links to increased demand for certainty about the best course of action when faced with assuming responsibility for others. r, Spearman rank correlation coefficient.


Leaders must take responsibility for others and thus affect the well-being of individuals, organizations, and nations. We identify the effects of responsibility on leaders’ choices at the behavioral and neurobiological levels and document the widespread existence of responsibility aversion, that is, a reduced willingness to make decisions if the welfare of others is at stake. In mechanistic terms, basic preferences toward risk, loss, and ambiguity do not explain responsibility aversion, which, instead, is driven by a second-order cognitive process reflecting an increased demand for certainty about the best choice when others’ welfare is affected. Finally, models estimating levels of information flow between brain regions that process separate choice components provide the first step in understanding the neurobiological basis of individual variability in responsibility aversion and leadership scores.

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