A team of researchers from the Mind, Brain, and Behavior Research Center (CIMCYC) at the University of Granada, in collaboration with the University of Castilla-La Mancha, has conducted a study that sheds light on the close relationship between parental stress and the daily performance of children with neurodevelopmental disorders. The study provides scientific evidence on a daily reality for many families, demonstrating that the health of caregivers is intrinsically linked to the level of autonomy and functional development of the children in their care.

Researchers at Istituto Italiano di Tecnologia (IIT-Italian Institute of Technology) have developed an innovative microscopy technique capable of improving the observation of living cells. The study, published in the journal Optics Letters, paves the way for a more in-depth analysis of numerous biological processes without the need for contrast agents. The next step will be to enhance this technique using artificial intelligence, opening the door to a new generation of optical microscopy methods capable of combining direct imaging with innovative molecular information.

Three researchers from the Faculty of Humanities, Communication and Documentation at the Carlos III University of Madrid (UC3M), Jesús Bermejo, Michele Curnis and Ana Mejón, have been selected in the latest call for applications for the Ramón Areces Foundation's Digital Humanities Research Grants Program. The projects stand out for their use of disruptive technologies such as artificial intelligence, enriched digitization, and chronotope mapping to advance knowledge of the archaeology, history, and culture of the Castilian Middle Ages and the Spanish film industry, respectively.

“End-of-life experiences” is the theme of the 2026 edition of the “Behind and Beyond the Brain” Symposium, promoted by the Bial Foundation, which will take place from April 8 to 11 at Casa do Médico, in Porto, Portugal, and for which registrations are now open. The symposium aims to foster interdisciplinary dialogue between different approaches — scientific, philosophical, and cultural — to explore what is scientifically known about the biological processes that occur when life ends, how different cultures interpret death, and whether the experience of death can alter our understanding of reality.

This study presents a transfer learning–based method for predicting train-induced environmental vibration. The method applies data fusion to combine physics-based numerical simulations and limited measurement data within a neural network. It reduces the heavy reliance of conventional machine learning–based models on scarce and costly field measurements while achieving improved prediction accuracy.