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SummaryData analysis workflows in many scientific domains have become increasingly complex and flexible. To assess the impact of this flexibility on functional magnetic resonance imaging (fMRI) results, the same dataset was independently analyzed by 70 teams, testing nine ex-ante hypotheses. The flexibility of analytic approaches is exemplified by the fact that no two teams chose identical workflows to analyze the data. This flexibility resulted in sizeable variation in hypothesis test results, even for teams whose statistical maps were highly correlated at intermediate stages of their analysis pipeline. Variation in reported results was related to several aspects of analysis methodology. Importantly, meta-analytic approaches that aggregated information across teams yielded significant consensus in activated regions across teams. Furthermore, prediction markets of researchers in the field revealed an overestimation of the likelihood of significant findings, even by researchers with direct knowledge of the dataset. Our findings show that analytic flexibility can have substantial effects on scientific conclusions, and demonstrate factors related to variability in fMRI. The results emphasize the importance of validating and sharing complex analysis workflows, and demonstrate the need for multiple analyses of the same data. Potential approaches to mitigate issues related to analytical variability are discussed.

When choosing actions, humans have to balance carefully between different task demands. On the one hand, they should perform tasks repeatedly to avoid frequent and effortful switching between different tasks. On the other hand, subjects have to retain their flexibility to adapt to changes in external task demands such as switching away from an increasingly difficult task. Here, we developed a difficulty-based choice task to investigate how subjects voluntarily select task-sets in predictably changing environments. Subjects were free to choose 1 of the 3 task-sets on a trial-by-trial basis, while the task difficulty changed dynamically over time. Subjects self-sequenced their behavior in this environment while we measured brain responses with functional magnetic resonance imaging (fMRI). Using multivariate decoding, we found that task choices were encoded in the medial prefrontal cortex (dorso-medial prefrontal cortex, dmPFC, and dorsal anterior cingulate cortex, dACC). The same regions were found to encode task difficulty, a major factor influencing choices. Importantly, the present paradigm allowed us to disentangle the neural code for task choices and task difficulty, ensuring that activation patterns in dmPFC/dACC independently encode these 2 factors. This finding provides new evidence for the importance of the dmPFC/dACC for task-selection and motivational functions in highly dynamic environments.

Rewards obtained from specific behaviors can and do change across time. To adapt to such conditions, humans need to represent and update associations between behaviors and their outcomes. Much previous work focused on how rewards affect the processing of specific tasks. However, abstract associations between multiple potential behaviors and multiple rewards are an important basis for adaptation as well. In this experiment, we directly investigated which brain areas represent associations between multiple tasks and rewards, using time-resolved multivariate pattern analysis of functional magnetic resonance imaging data. Importantly, we were able to dissociate neural signals reflecting task-reward associations from those related to task preparation and reward expectation processes, variables that were often correlated in previous research. We hypothesized that brain regions involved in processing tasks and/or rewards will be involved in processing associations between them. Candidate areas included the dorsal anterior cingulate cortex, which is involved in associating simple actions and rewards, and the parietal cortex, which has been shown to represent task rules and action values. Our results indicate that local spatial activation patterns in the inferior parietal cortex indeed represent task-reward associations. Interestingly, the parietal cortex flexibly changes its content of representation within trials. It first represents task-reward associations, later switching to process tasks and rewards directly. These findings highlight the importance of the inferior parietal cortex in associating behaviors with their outcomes and further show that it can flexibly reconfigure its function within single trials.

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Alternating between two tasks is effortful and impairs performance. Previous fMRI studies have found increased activity in frontoparietal cortex when task switching is required. One possibility is that the additional control demands for switch trials are met by strengthening task representations in the human brain. Alternatively, on switch trials, the residual representation of the previous task might impede the buildup of a neural task representation. This would predict weaker task representations on switch trials, thus also explaining the performance costs. To test this, male and female participants were cued to perform one of two similar tasks, with the task being repeated or switched between successive trials. Multivoxel pattern analysis was used to test which regions encode the tasks and whether this encoding differs between switch and repeat trials. As expected, we found information about task representations in frontal and parietal cortex, but there was no difference in the decoding accuracy of task-related information between switch and repeat trials. Using cross-classification, we found that the frontoparietal cortex encodes tasks using a generalizable spatial pattern in switch and repeat trials. Therefore, task representations in frontal and parietal cortex are largely switch independent. We found no evidence that neural information about task representations in these regions can explain behavioral costs usually associated with task switching. Alternating between two tasks is effortful and slows down performance. One possible explanation is that the representations in the human brain need time to build up and are thus weaker on switch trials, explaining performance costs. Alternatively, task representations might even be enhanced to overcome the previous task. Here, we used a combination of fMRI and a brain classifier to test whether the additional control demands under switching conditions lead to an increased or decreased strength of task representations in frontoparietal brain regions. We found that task representations are not modulated significantly by switching processes and generalize across switching conditions. Therefore, task representations in the human brain cannot account for the performance costs associated with alternating between tasks.

Most people believe in free will. Whether this belief is warranted or not, free will beliefs (FWB) are foundational for many legal systems and reducing FWB has effects on behavior from the motor to the social level. This raises the important question as to which specific FWB people hold. There are many different ways to conceptualize free will, and some might see physical determinism as a threat that might reduce FWB, while others might not. Here, we investigate lay FWB in a large, representative, replicated online survey study in the US and Singapore (n = 1800), assessing differences in FWB with unprecedented depth within and between cultures. Specifically, we assess the relation of FWB, as measured using the Free Will Inventory, to determinism, dualism and related concepts like libertarianism and compatibilism. We find that libertarian, compatibilist, and dualist, intuitions were related to FWB, but that these intuitions were often logically inconsistent. Importantly, direct comparisons suggest that dualism was more predictive of FWB than other intuitions. Thus, believing in free will goes hand-in-hand with a belief in a non-physical mind. Highlighting the importance of dualism for FWB impacts academic debates on free will, which currently largely focus on its relation to determinism. Our findings also shed light on how recent (neuro)scientific findings might impact FWB. Demonstrating physical determinism in the brain need not have a strong impact on FWB, due to a wide-spread belief in dualism.

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