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While prediction errors (PE) have been established to drive learning through adaptation of internal models, the role of model-compliant events in predictive processing is less clear. Checkpoints (CP) were recently introduced as points in time where expected sensory input resolved ambiguity regarding the validity of the internal model. Conceivably, these events serve as on-line reference points for model evaluation, particularly in uncertain contexts. Evidence from fMRI has shown functional similarities of CP and PE to be independent of event-related surprise, raising the important question of how these event classes relate to one another. Consequently, the aim of the present study was to characterise the functional relationship of checkpoints and prediction errors in a serial pattern detection task using electroencephalography (EEG). Specifically, we first hypothesised a joint P3b component of both event classes to index recourse to the internal model (compared to non-informative standards, STD). Second, we assumed the mismatch signal of PE to be reflected in an N400 component when compared to CP. Event-related findings supported these hypotheses. We suggest that while model adaptation is instigated by prediction errors, checkpoints are similarly used for model evaluation. Intriguingly, behavioural subgroup analyses showed that the exploitation of potentially informative reference points may depend on initial cue learning: Strict reliance on cue-based predictions may result in less attentive processing of these reference points, thus impeding upregulation of response gain that would prompt flexible model adaptation. Overall, present results highlight the role of checkpoints as model-compliant, informative reference points and stimulate important research questions about their processing as function of learning und uncertainty.
According to a popular stereotype, women are better at multitasking than men, but empirical evidence for gender differences in multitasking performance is mixed. Previous work has focused on specific aspects of multitasking or has not considered gender differences in abilities contributing to multitasking performance. We therefore tested gender differences (N = 96, 50% female) in sequential (i.e., task switching) and concurrent (i.e., dual tasking) multitasking, while controlling for possible gender differences in working memory, processing speed, spatial abilities, and fluid intelligence. Applying two standard experimental paradigms allowed us to test multitasking abilities across five different empirical indices (i.e., performance costs) for both reaction time (RT) and accuracy measures, respectively. Multitasking resulted in substantial performance costs across all experimental conditions without a single significant gender difference in any of these ten measures, even when controlling for gender differences in underlying cognitive abilities. Thus, our results do not confirm the widespread stereotype that women are better at multitasking than men at least in the popular sequential and concurrent multitasking settings used in the present study.