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We describe a neural monitor of environmental and physiological resources that informs effort expenditure. Depending on resources and environmental stability, serotonergic and dopaminergic neuromodulations favor different behavioral controls that are organized in corticostriatal loops. This broader perspective produces some suggestions and questions that may not be covered by the foraging approach to vigor of Shadmehr and Ahmed (2020).

Cognitive control is crucially involved in making (dis)honest decisions. However, the precise nature of this role has been hotly debated. Is honesty an intuitive response, or is will power needed to override an intuitive inclination to cheat? A reconciliation of these conflicting views proposes that cognitive control enables dishonest participants to be honest, whereas it allows those who are generally honest to cheat. Thus, cognitive control does not promote (dis)honesty per se; it depends on one's moral default. In the present study, we tested this proposal using electroencephalograms in humans (males and females) in combination with an independent localizer (Stroop task) to mitigate the problem of reverse inference. Our analysis revealed that the neural signature evoked by cognitive control demands in the Stroop task can be used to estimate (dis)honest choices in an independent cheating task, providing converging evidence that cognitive control can indeed help honest participants to cheat, whereas it facilitates honesty for cheaters. SIGNIFICANCE STATEMENT Dishonesty causes enormous economic losses. To target dishonesty with interventions, a rigorous understanding of the underlying cognitive mechanisms is required. A recent study found that cognitive control enables honest participants to cheat, whereas it helps cheaters to be honest. However, it is evident that a single study does not suffice as support for a novel hypothesis. Therefore, we tested the replicability of this finding using a different modality (EEG instead of fMRI) together with an independent localizer task to avoid reverse inference. We find that the same neural signature evoked by cognitive control demands in the localizer task can be used to estimate (dis)honesty in an independent cheating task, establishing converging evidence that the effect of cognitive control indeed depends on a person's moral default.

There is a long-standing debate regarding the cognitive nature of (dis)honesty: Is honesty an automatic response or does it require willpower in the form of cognitive control in order to override an automatic dishonest response. In a recent study (Speer et al., 2020), we proposed a reconciliation of these opposing views by showing that activity in areas associated with cognitive control, particularly the inferior frontal gyrus (IFG), helped dishonest participants to be honest, whereas it enabled cheating for honest participants. These findings suggest that cognitive control is not needed to be honest or dishonest per se but that it depends on an individual’s moral default. However, while our findings provided insights into the role of cognitive control in overriding a moral default, they did not reveal whether overriding honest default behavior (non-habitual dishonesty) is the same as overriding dishonest default behavior (non-habitual honesty) at the neural level. This speaks to the question as to whether cognitive control mechanisms are domain-general or may be context specific. To address this, we applied multivariate pattern analysis to compare neural patterns of non-habitual honesty to non-habitual dishonesty. We found that these choices are differently encoded in the IFG, suggesting that engaging cognitive control to follow the norm (that cheating is wrong) fundamentally differs from applying control to violate this norm.

Wat is de toegevoegde waarde van het toepassen van neurowetenschappelijke methoden zoals EEG en fMRI in marketing? Kunnen we emoties meten in de hersenen? Kunnen we merkassociaties aflezen uit het brein? Kunnen we met hersenreacties koopgedrag beter voorspellen? In dit artikel geven we antwoord op deze vragen aan de hand van enkele voorbeelden uit ons eigen werk, waarin we machine-learning technieken combineren met neuroimaging methoden. Ten slotte geven we een voorzet over wat de toekomst kan gaan brengen voor neuromarketing.

In this chapter we propose a theory in which behavior (broadly comprising relevant cognition, emotion, and behavior) and physiology are coordinated and integrated by a number of separate behavioral and physiological programs, for convenience termed here biobehavioral programs.