This study provides important insights into how working memory shapes perceptual decisions, using a dual-task design, continuous mouse tracking, and hierarchical Bayesian modeling. By dissociating ...

This study uses a Bayesian framework to characterize latent brain state dynamics associated with memory encoding and performance in children, as measured with functional magnetic resonance imaging.

Introduction Cerebral palsy (CP) is a non-progressive condition involving movement and muscle tone difficulties due to injury to the developing brain. Most cases arise around birth, but a smaller ...

As social media becomes the core domain of information interaction in the era of big data, the emotional information contained in the vast amount of user-generated content provides an unprecedented ...

Researchers from the University of Maryland, Lawrence Livermore, Columbia and TogetherAI have developed a training technique that triples LLM inference speed without auxiliary models or infrastructure ...

With reported 3x speed gains and limited degradation in output quality, the method targets one of the biggest pain points in production AI systems: latency at scale.

The intersection of artificial intelligence and mechanistic neuroscience is rapidly transforming our understanding of neural systems. While AI ...

High-throughput sequencing, single-cell technologies, and large-scale population studies have transformed genetics and genomics into data-intensive ...