Goal-directed behaviour requires humans to constantly manage and switch between multiple, independent and conflicting sources of information. Conventional cognitive control tasks, however, only feature one task and one source of distraction. Therefore, it is unclear how control is allocated in multidimensional environments. To address this question, we developed a multidimensional task-set interference paradigm, in which people need to manage distraction from three independent dimensions. We use this task to test whether people adapt to previous conflict by enhancing task-relevant information or suppressing task-irrelevant information. Three experiments provided strong evidence for the latter hypothesis. Moreover, control adaptation was highly dimension specific. Conflict from a given dimension only affected processing of that same dimension on subsequent trials, with no evidence for generalization. A new neural network model shows that our results can only be simulated when including multiple independent conflict-detector units. Our results call for an update to classic models of cognitive control and their neurocomputational underpinnings.

Autism spectrum disorder (ASD) is clinically heterogeneous, with ongoing debates about phenotypic differences between boys and girls. Understanding these differences, particularly at the age of first symptom onset, is critical for advancing early detection, uncovering aetiological mechanisms and improving interventions. Leveraging the Get SET Early programme, we analysed a cohort of 2,618 toddlers (mean age: ~27 months) through cross-sectional, longitudinal and clustering analyses, performed using statistical and machine learning approaches, to assess sex differences in groups with ASD, developmental delay and typical development across standardized and experimental measures, including eye tracking. The results revealed no significant sex differences in toddlers with ASD across 17 of 18 measures, including symptom severity based on the Autism Diagnostic Observation Schedule, receptive and expressive language based on the Mullen Scales of Early Learning and social attention based on the GeoPref eye-tracking test. In contrast, girls with typical development outperformed boys on several measures. Subtyping analyses stratifying toddlers into low, medium and high clusters similarly showed virtually no sex differences in ASD. Overall, our findings suggest that phenotypic sex differences are minimal or non-existent in those with ASD at the time of first symptom onset.

Human vision is mediated by a complex interconnected network of cortical brain areas that jointly represent visual information. Although these areas are increasingly understood in isolation, their representational relationships remain unclear. Here we developed relational neural control and used it to investigate the representational relationships for univariate and multivariate functional magnetic resonance imaging (fMRI) responses of areas across the visual cortex. Through relational neural control, we generated and explored in silico fMRI responses for large numbers of images, discovering controlling images that align or disentangle responses across areas, thus indicating their shared or unique representational content. This revealed a typical network-level configuration of representational relationships in which shared or unique representational content varied on the basis of cortical distance, categorical selectivity and position within the visual hierarchy. Closing the empirical cycle, we validated the in silico discoveries on in vivo fMRI responses from independent participants. Together, this reveals how visual areas jointly represent the world as an interconnected network.

Social norms approaches have been widely applied in health promotion as a cost-effective behaviour-change strategy, but have been little evaluated as a whole. We conducted a pre-registered systematic review and meta-analysis of randomized controlled trials using social norms messaging in developed countries targeted at changing health behaviours among 16+-year-olds to evaluate their effectiveness. Relevant studies were identified through searches in PsycINFO, Medline, Embase, Web of Science, TRIP, Cochrane and grey literature sources. Risk of bias was assessed independently by two reviewers using the Cochrane RoB 2 tool. A random-effects meta-analysis standardized effect sizes to Cohen’s d, assessed heterogeneity with I² and applied robust Bayesian meta-analysis to adjust for publication bias. Searches resulted in 89 studies (n = 85,759), which exhibited a small effect of social norms messaging on health behaviours (Cohen’s d = 0.1, 95% confidence interval (CI) [0.09, 0.19], P < 0.001). However, this effect disappeared after controlling for publication bias. We conducted moderator analyses, finding no significant differences from the overall effect for different types of social norms message, delivery modalities, health domains or target populations. The review is limited by the lack of studies assessing whether normative information changed participant perceptions, inconsistent use of manipulation checks, and high heterogeneity across studies in terms of target behaviour, population and intervention delivery, affecting the robustness of conclusions. Our analysis suggests that when appropriately controlling for publication bias, social norms messages are not effective at improving health behaviours. Thus, future attempts at improving public health should focus on alternative approaches.

We experience surprise when reality conflicts with our expectations. When we encounter such expectation violations in psychological tasks and daily life, are we experiencing completely different forms of surprise? Or is surprise a fundamental psychological process with shared neural bases across contexts? To address this question, we identified a brain network model, the surprise edge-fluctuation-based predictive model (EFPM), whose regional interaction dynamics measured with functional magnetic resonance imaging (fMRI) predicted surprise in an adaptive learning task. The same model generalized to predict surprise as a separate group of individuals watched suspenseful basketball games and as a third group watched videos violating psychological expectations. The surprise EFPM also uniquely predicts surprise, capturing expectation violations better than models built from other brain networks, fMRI measures and behavioural metrics. These results suggest that shared neurocognitive processes underlie surprise across contexts and that distinct experiences can be translated into the common space of brain dynamics.

People form impressions of one another in a split second from faces. However, people also infer others' momentary mental states on the basis of context-for example, one might infer that somebody feels encouraged from the fact that they are receiving constructive feedback. How do trait judgements of faces influence these context-based mental state inferences? In this Registered Report, we asked participants to infer the mental states of unfamiliar people, identified by their neutral faces, under specific contexts. To increase generalizability, we representatively sampled all stimuli from inclusive sets using computational methods. We tested four hypotheses: that trait impressions of faces (1) are correlated with subsequent mental state inferences in a range of contexts, (2) alter the dimensional space that underlies mental state inferences, (3) are associated with specific mental state dimensions in this space and (4) causally influence mental state inferences. We found evidence in support of all hypotheses.