This paper presents a computational model of how the brain uses predictions and prior knowledge to filter and interpret sensory information. While the model shows promise in explaining existing behavioral and brain imaging data, it's …
Researchers developed FastGxC, a computational method that finds genes whose activity changes depending on tissue or cell type context—a key mechanism in disease risk. The tool is a million times faster than existing approaches and …
Researchers created a computational model that simulates how fruit fly larvae move, navigate, and learn—combining physics-based locomotion with neural circuits and behavior. This tool could help neuroscientists test theories about how brains control behavior without …
Researchers trained artificial intelligence models to automatically identify different kidney cell structures using a simple imaging technique, without needing stains or labels. This tool could help scientists understand how kidneys age and develop better tests …
Researchers created a mathematical model showing how two inhibitor proteins (Dickkopf) and Wnt signalling interact to form Hydra's body axis through mutual inhibition rather than the classical activator-inhibitor mechanism. This provides a mechanistic blueprint for …
This meta-analysis of 80 brain imaging studies identifies which research methods reliably detect the neural circuits involved in delay discounting—the tendency to prefer immediate rewards over future ones. The findings suggest that future studies should …
This meta-analysis of 45 neuroimaging studies (1,273 participants) identified distinct brain regions that process rewards and task difficulty separately, then integrate them to decide whether mental effort is worth the reward. The findings clarify how …
Researchers used AI agents to reanalyze millions of existing molecular datasets (methylation and RNA sequencing) through the lens of aging clocks, discovering over 500 interventions that appear to reduce biological age—including drugs like ouabain and …