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Mapping the genetic landscape of psychiatric disorders with the MiXeR toolset
No full textPsychiatric disorders have complex genetic architectures with substantial genetic overlap across conditions, which may partially explain their high levels of comorbidity. This presents significant challenges to research. Genome-wide association studies (GWASs) have uncovered hundreds of loci associated with single disorders, but the genetic landscape of psychiatric disorders has remained largely obscure. Moving beyond the conventional infinitesimal model, uni-, bi-, and trivariate MiXeR tools, applied to GWAS summary statistics, has enabled us to more comprehensively describe the genetic architecture of complex disorders and traits and their overlap. Furthermore, the GSA-MiXeR tool improves biological interpretation of GWAS findings to better elucidate causal mechanisms. Here, we outline the methodology that underlies the MiXeR tools together with instructions for their optimal use. We review results from studies that have investigated the genetic architecture of psychiatric disorders and their overlap using the MiXeR toolset. These studies have revealed generally high polygenicity and low discoverability among psychiatric disorders, particularly in contrast to somatic disorders. There is also pervasive genetic overlap across psychiatric disorders and behavioral traits, while their overlap with somatic traits is smaller, consistent with differences in polygenicity. Finally, GSA-MiXeR has quantified the contribution of gene sets to the heritability of psychiatric disorders, prioritizing small, biologically coherent gene sets. Together, these findings have implications for our understanding of the complex relationships between psychiatric disorders and related traits. MiXeR tools have provided new insights into the genetic architecture of psychiatric disorders, generating a better understanding of their underlying biological mechanisms and potential for clinical utility.</p
Mapping curvature domains in human V4 using CBV-sensitive layer-fMRI at 3T
No full textINTRODUCTION: A full understanding of how we see our world remains a fundamental research question in vision neuroscience. While topographic profiling has allowed us to identify different visual areas, the exact functional characteristics and organization of areas up in the visual hierarchy (beyond V1 & V2) is still debated. It is hypothesized that visual area V4 represents a vital intermediate stage of processing spatial and curvature information preceding object recognition. Advancements in magnetic resonance imaging hardware and acquisition techniques (e.g., non-BOLD functional MRI) now permits the capture of cortical layer-specific functional properties and organization of the human brain (including the visual system) at high precision. METHODS: Here, we use functional cerebral blood volume measures to study the modularity in how responses to contours (curvature) are organized within area V4 of the human brain. To achieve this at 3 Tesla (a clinically relevant field strength) we utilize optimized high-resolution 3D-Echo Planar Imaging (EPI) Vascular Space Occupancy (VASO) measurements. RESULTS: Data here provide the first evidence of curvature domains in human V4 that are consistent with previous findings from non-human primates. We show that VASO and BOLD tSNR maps for functional imaging align with high field equivalents, with robust time series of changes to visual stimuli measured across the visual cortex. V4 curvature preference maps for VASO show strong modular organization compared to BOLD imaging contrast. It is noted that BOLD has a much lower sensitivity (due to known venous vasculature weightings) and specificity to stimulus contrast. We show evidence that curvature domains persist across the cortical depth. The work advances our understanding of the role of mid-level area V4 in human processing of curvature and shape features. IMPACT: Knowledge of how the functional architecture and hierarchical integration of local contours (curvature) contribute to formation of shapes can inform computational models of object recognition. Techniques described here allow for quantification of individual differences in functional architecture of mid-level visual areas to help drive a better understanding of how changes in functional brain organization relate to difference in visual perception
A dance with interactions:The design of dynamic biomaterials to advance corneal therapies
No full textMind in motion:untangling motor and cognitive domains in schizophrenia spectrum disorders
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Werktaken als indicator van vraag en aanbod op de Nederlandse arbeidsmarkt
No full textDe Nederlandse arbeidsmarkt is in beweging, door onder andere de energietransitie, technologische ontwikkeling en internationale handel. Daarnaast verandert de inhoud van bestaande banen. De Nederlandse Skills Survey (NSS) biedt een uniek en integraal beeld van de ontwikkelingen in de arbeidsvraag en het arbeidsaanbod. Deze survey meet sinds 2012 het belang van werktaken en de effectiviteit waarmee deze worden uitgevoerd. Werkgelegenheidsontwikkelingen gaan hand in hand met veranderingen in het belang van werktaken in de periode 2012-2024. De arbeidsvraag groeit met name in beroepen waarin interpersoonlijke vaardigheden en probleemoplossend vermogen van belang zijn
Tech Won’t Save Us: Climate Crisis, Techno-Optimism, and International Law
No full textThis article critiques the narrative that technological innovations can solve the climate crisis. It argues that technology is important for addressing environmental challenges, but on its own it cannot tackle the broader socioeconomic factors contributing to global ecological degradation. The article examines techno-optimism in international (environmental) law, illustrating its persistent focus on technological solutions from early treaties to contemporary policy agreements. By analysing the limitations of technology – particularly electric vehicles and bioenergy with carbon capture and storage – the article reveals how adherence to the techno-optimist narrative leads international law to undervalue the need for structural changes in our socioeconomic system. The article argues for a shift from the techno-optimist narrative to an ecological one, reflecting the urgent need to redefine development beyond economic growth and technological advancement
Synthetic media and reality engineering: policy solutions for the EU
No full textIn this policy brief, I explore synthetic media: digital artefacts created entirely with generative artificial intelligence (GenAI). These can be visual, auditory, audiovisual or textual, such as deepfake videos or output from large language models (LLMs), such as ChatGPT. Due to the rapid developments in GenAI technology, it is becoming increasingly easy for anyone to engineer a ‘reality’ with synthetic media. Unlike traditional forms of forgery, synthetic media require no source and are algorithmically crafted. This makes them powerful tools for both creativity and deception.Synthetic media are everywhere, from viral social media hoaxes to malicious deepfake campaigns. In 2024, fake images of celebrities at the Met Gala fooled millions, while realistically-sounding deepfake robocalls tried to disrupt primary elections in the United States. Such misuses fuel a growing social epistemic crisis, eroding trust in democratic processes by blurring the line between fact and fiction. The real threat lies not just in the convincing nature of synthetic media but in their rapid spread across digital platforms, particularly very large online platforms (VLOPs). Understanding these dynamics is essential to mitigating harm at both individual and societal levels.This brief offers several policy recommendations to address these challenges under the EU Digital Services Act (DSA) and AI Act.Key proposals are:Fortifying investments in digital forensics for early detection of harmful, deceptive media.Holding social media platforms accountable for enabling and amplifying synthetic media.Building public resilience through psychological inoculation strategies. These policies address synthetic media, their enablers, and their societal impact responsibly—without throwing the baby out with the bath water. As such, the policy recommendations support safeguarding creativity and democratic integrity while fortifying trust and safety in the digital age
Perception of Emotions in Human and Robot Faces: Is the Eye Region Enough?
No full textThe increased interest in developing next-gen social robots has raised questions about the factors affecting the perception of robot emotions. This study investigates the impact of robot appearances (human-like, mechanical) and face regions (full-face, eye-region) on human perception of robot emotions. A between-subjects user study (N = 305) was conducted where participants were asked to identify the emotions being displayed in videos of robot faces, as well as a human baseline. Our findings reveal three important insights for effective social robot face design in Human-Robot Interaction (HRI): Firstly, robots equipped with a back-projected, fully animated face – regardless of whether they are more human-like or more mechanical-looking – demonstrate a capacity for emotional expression comparable to that of humans. Secondly, the recognition accuracy of emotional expressions in both humans and robots declines when only the eye region is visible. Lastly, within the constraint of only the eye region being visible, robots with more human-like features significantly enhance emotion recognition.</p