FAIR, safe and high-quality data: The data infrastructure and accessibility of the YOUth cohort study.

The YOUth cohort study aims to be a trailblazer for open science. Being a large-scale, longitudinal cohort following children in their development from gestation until early adulthood, YOUth collects a vast amount of data through a variety of research techniques. Data are collected through multiple platforms, including facilities managed by Utrecht University and the University Medical Center Utrecht. In order to facilitate appropriate use of its data by research organizations and researchers, YOUth aims to produce high-quality, FAIR data while safeguarding the privacy of participants. This requires an extensive data infrastructure, set up by collaborative efforts of researchers, data managers, IT departments, and the Utrecht University Library. In the spirit of open science, YOUth will share its experience and expertise in setting up a high-quality research data infrastructure for sensitive cohort data. This paper describes the technical aspects of our data and data infrastructure, and the steps taken throughout the study to produce and safely store FAIR and high-quality data. Finally, we will reflect on the organizational aspects that are conducive to the success of setting up such an enterprise, and we consider the financial challenges posed by individual studies investing in sustainable science.

Visualizing mental representations in schizophrenia patients: A reverse correlation approach.

Schizophrenia patients have difficulties recognizing emotional states from faces, in particular those with negative valence, with severe consequences for daily life. What do these patients see in their minds eye, when they think of a face expressing a particular emotion or trait? The content of such mental representations can shed light into the nature of their deficits, but are usually inaccessible. For the first time, we explored the applicability of reverse correlation, which has been successfully used to visualize mental representations in healthy populations, to visualize mental representations in schizophrenia patients. We investigated mental representations of trustworthy faces, a primary dimension of social face evaluation that is highly correlated with valence. Patients (n = 23) and healthy controls (n = 34) classified images of noise-distorted faces as 'trustworthy', 'untrustworthy' or 'neutral'. We visualized their mental representations of these concepts by averaging the noise patterns based on their classifications. These visualizations were then rated on trustworthiness by an independent sample of participants. Patients were able to perform the reverse correlation task, with response times and biases similar to those of healthy controls, and the obtained images vividly reflected the respective constructs of interest. However, there were no significant differences between the ratings of the visualizations of patients and controls. Conclusion: These novel findings provide a proof of principle that the reverse correlation technique can be applied to investigate mental representations in schizophrenia patients.