Individual and life-span differences in charitable giving are an important economic force, yet the underlying motives are not well understood. In an adult, life-span sample, we assessed manifestations of prosocial tendencies across three different measurement domains: (a) psychological self-report measures, (b) actual giving choices, and (c) fMRI-derived, neural signals of “pure altruism”. The latter expressed individuals’ activity in valuation areas when charities received money compared to when oneself received money and thus reflected an altruistic concern for others. Results based both on structural equation modeling and unit-weighted aggregate scores revealed a strong higher-order General Benevolence dimension that accounted for variability across all measurement domains. The fact that the neural measures likely reflect pure altruistic tendencies indicates that General Benevolence is based on a genuine concern for others. Furthermore, General Benevolence exhibited a robust increase across the adult life-span, potentially providing one important explanation for why older adults typically contribute more to the public good than young adults.

Task-switch costs and in particular the switch-cost asymmetry (i.e., the larger costs of switching to a dominant than a non-dominant task) are usually explained in terms of trial-to-trial carry-over of task-specific control settings. Here we argue that task switches are just one example of situations that trigger a transition from working-memory maintenance to updating, thereby opening working memory to interference from long-term memory. We used a new paradigm that requires selecting a spatial location either on the basis of a central cue (i.e., endogenous control of attention) or a peripheral, sudden onset (i.e., exogenous control of attention). We found a strong cost asymmetry that occurred even after short interruptions of otherwise single-task blocks (Exp. 1-3), but that was much stronger when participants had experienced the competing task under conditions of conflict (Exp. 1-2). Experiment 3 showed that the asymmetric costs were due to interruptions per se, rather than to associative interference tied to specific interruption activities. Experiment 4 generalized the basic pattern across interruptions varying in length or control demands and Experiment 5 across primary tasks with response-selection conflict rather than attentional conflict. Combined, the results support a model in which costs of selecting control settings arise when (a) potentially interfering memory traces have been encoded in long-term memory and (b) working-memory is forced from a maintenance mode into an updating mode (e.g., through task interruptions), thereby allowing unwanted retrieval of the encoded memory traces.

Models of action control assume that attentional control settings regulate the processing of lower-level stimulus/response representations. Yet, little is known about how exactly control and sensory/response representations relate to each other to produce goal-directed behavior. Addressing this question requires time-resolved information about the strength of the different, potentially overlapping representations, on a trial-by-trial basis. Using a cued task-switching paradigm, we show that information about relevant representations can be extracted through decoding analyses from the scalp electrophysiological signal (EEG) with high temporal resolution. Peaks in representational strength—indexed through decoding accuracy—proceeded from superficial task cues, to stimulus locations, to features/responses. In addition, attentional-set representations were prominent throughout almost the entire processing cascade. Trial-by-trial analyses provided detailed information about when and to what degree different representations predict performance, with attentional settings emerging as a strong and consistent predictor of within-individual and across-individual variability in performance. Also, the strength of attentional sets was related to target representations early in the post-stimulus period and to feature/response representations at a later period, suggesting control of successive, lower-level representations in a concurrent manner. These results demonstrate a powerful approach towards uncovering different stages of information processing and their relative importance for performance.

Conflict-adaptation effects (i.e., reduced response-time costs on high-conflict trials following high-conflict trials) supposedly represent our cognitive system’s ability to regulate itself according to current processing demands. However, currently it is not clear whether these effects reflect conflict-triggered, active regulation, or passive carry-over of previous-trial control settings. We used eye movements to examine whether the degree of experienced conflict modulates conflict-adaptation effects, as the conflict-triggered regulation view predicts. Across two experiments in which participants had to identify a target stimulus based on an endogenous cue while––on conflict trials––having to resist a sudden-onset distractor, we found a clear indication of conflict adaptation. This adaptation effect disappeared however, when participants inadvertently fixated the sudden-onset distractor on the previous trial––that is, when they experienced a high degree of conflict. This pattern of results suggests that conflict adaptation can be explained parsimoniously in terms of a broader memory process that retains recently adopted control settings across trials.

Trial-to-trial carry-over of task sets (i.e., task-set inertia) is often considered as a primary reason for task-switch costs. Yet, we know little about the dynamics of such carry-over effects, in particular how much they are driven by the most recent trial rather than characterized by a more continuous memory gradient. Using eye-tracking, we examined in a 3-task, task-switching paradigm whether there is a greater probability of non-target fixations to stimuli associated with the previously relevant attentional set than to those associated with the less-recent set. Indeed, we found strong evidence for more interference (expressed in terms of non-target fixations) from recent than from less-recent tasks and that in particular the interference from pre-switch trials contributes substantially to the overall pattern of response-time switch costs. Moreover, task-set carry-over was dominated by the most-recent trial when subjects could expect task repetitions (with a 33% switch rate). In comparison, when tasks were selected randomly (with a 66% switch rate), interference from the most recent trial decreased, whereas interference from less-recent trials increased. In sum, carry-over interference dynamics were characterized both by a gradual recency gradient and expectations about task-transition probabilities. Beyond that there was little evidence for a unique role of the most-recent trial.