Environmental risks are communicated through experiential formats, such as pictures, videos, and virtual reality simulations, and descriptive formats, such as hazard maps and graphs, yet the neural systems engaged by these formats remain unclear. We acquired functional magnetic resonance imaging data from 45 healthy adults while they viewed first-person three-dimensional computer-generated flood videos and official flood maps, along with matched non-flood controls, in a within-subject 2 × 2 factorial design. Participants rated subjective fear after each stimulus. Neural responses were characterized using whole-brain general linear model analyses, anatomically defined region-of-interest analyses, and group independent component analysis. Flood videos produced a greater flood-related increase in subjective fear than flood maps. Relative to maps, videos elicited stronger flood-related responses in bilateral occipito-temporal and temporo-parietal cortices, sensorimotor and cingulate regions, pulvinar nuclei, and the cerebellum; the region-of-interest analysis further revealed greater right amygdala activation. In contrast, flood maps showed greater flood-related responses in bilateral frontal and parietal regions, including dorsolateral prefrontal and intraparietal areas commonly implicated in cognitive control and symbolic-spatial processing. Independent component analysis indicated that the video-favoring interaction was predominantly expressed in a single component overlapping regions commonly associated with perceptual and salience processing, whereas the map-favoring interaction was distributed across multiple components, including components resembling frontoparietal control networks. Taken together, these regional and network-level differences were broadly consistent with the hypothesized distinction between experiential and descriptive risk processing. The two formats may therefore offer complementary routes for flood-risk communication.
Agile methods continue to gain popularity. In particular, the Scrum method appears to be on the verge of becoming a de-facto standard in the industry, leading the so called Agile movement. While there are success stories and recommendations, there is little scientifically valid evidence of the challenges in the adoptio...
A. Marchenko, P. Abrahamsson· Agile Conference· 59 citations· ⚡11
A comprehensive taxonomy of the challenges faced when a medium-scale organization decided to adopt software platforms is provided, namely: business challenges, organizational challenges, technical challenges, and people challenges.
Yaser Ghanam, F. Maurer, P. Abrahamsson· Information and Software Tec...· 41 citations· ⚡3
It is shown that high article processing charges are not sufficiently justified by the publishers, which often lack transparency and may prevent authors from adopting OA.
D. Graziotin, Xiaofeng Wang, P. Abrahamsson· Scientometrics· 21 citations· ⚡1
MCGLPPI, a novel geometric representation learning framework that combines graph neural networks (GNNs) with the MARTINI molecular coarse-grained (CG) model to predict overall PPI properties accurately and efficiently, offers an effective and efficient solution for PPI overall property predictions.
Yang Yue, Shu Li, Yihua Cheng et al.· bioRxiv· 15 citations
PepPCBench enables a robust evaluation of PFNN-based methods and supports their continued development for peptide-protein structure prediction, and highlights the influence of peptide length, conformational flexibility, and training set similarity on prediction accuracy.
Si-Long Zhai, Huifeng Zhao, Ji-Ke Wang et al.· Journal of Chemical Informat...· 13 citations· ⚡1
OmniMol is presented, a framework using hypergraphs to improve predictions of molecular properties, addressing challenges of imperfect data annotation and enhancing model explainability, and achieves state-of-the-art performance in properties prediction.
Assistant Professor Pat Pataranutaporn describes a new interface that lets everyday users glimpse inside an AI's neural network before their chatbot ever says a word.
Microsoft Research Blog· microsoft.comJul 13, 2026
Cryptographic code supports vital protections in modern computing systems. Learn how a new method helps verify code as developers write it while preserving speed and adaptability as it gets implemented and evolves. The post Verifying Rust cryptography in SymCrypt, from standards to code appeared first on Microsoft Research.
MIT News · Artificial Intelligence· news.mit.eduJul 6, 2026
PhD student Rachel Sava, winner of the Envisioning the Future of Computing Prize, explores transformative improvements and dystopian risks of neural technology.